evaluation_results_wrong.csv

q_idx,variant,query,data_services,pipeline,output,output_json,example_query,example_pipeline
q0,0,Give me the serial number of camera 1 and camera 2 of all the diecutters in the factory.,"brief_description: Data service that, given the id of a camera1, provides a frame captured from that camera1. - detailed_description: Data service that, given the id of a camera1, provides a frame captured from that camera1.
        In general instances of camera1 point downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera1 (an integer) and returns a frame captured from that camera1 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera1 is 123, then the data service would be called as follows:
        camera1_id = 123
        frame = GetFrameFromCamera1.call(camera1_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int'] - output_values: ['frame:np.matrix'] - module: camera1 - class_name: GetFrameFromCamera1brief_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors and provide the type of error. - detailed_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors.
        Recall that a camera1 is a camera device that points downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera1 to use and the frame captured from that camera1.
        It returns a boolean value, True if the frame contains a cardboard with errors, False otherwise.
        Also it returns a integer value, 0 if the frame does not contain errors, 1 if the errors are of type hole and 2 if the errors are of type fold. 

        Example usage:
        - If frame is a variable containing the frame captured from the camera1 with id 123, then the data service would be called as follows:
        camera1_id = 123
        contains_errors, type_errors = DetectErrorsInCardboardUsingCamera1.call(camera1_id=123, frame=frame)

        Things to keep in mind:
        - The output is a tuple of boolean and integer, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool', 'error_type:int'] - module: camera1 - class_name: DetectErrorsInCardboardUsingCamera1brief_description: Data service that, given the id of a camera2, provides a frame captured from that camera2. - detailed_description: Data service that, given the id of a camera2, provides a frame captured from that camera2.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera2 (an integer) and returns a frame captured from that camera2 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera2 is 123, then the data service would be called as follows:
        camera2_id = 123
        frame = GetFrameFromCamera2.call(camera2_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int'] - output_values: ['frame:np.matrix'] - module: camera2 - class_name: GetFrameFromCamera2brief_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors. - detailed_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera2 to use and the frame captured from that camera2 that contains a stack of cardboards.
        It returns a boolean value, True if the frame contains a stack of cardboards with errors, False otherwise.

        Example usage:
        - If frame is a variable containing the frame captured from the camera2 with id 123, then the data service would be called as follows:
        camera2_id = 123
        contains_errors, error_type = DetectErrorsInCardboardStack.call(camera2_id=123, frame=frame)

        Things to keep in mind:
        - The output value is a boolean, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool'] - module: camera2 - class_name: DetectErrorsInCardboardStackUsingCamera2brief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera1 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera1.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera1)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera1:int'] - module: database - class_name: GetSerialCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera2 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera2.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera2)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera2:int'] - module: database - class_name: GetSerialCamera2IdFromDiecutterIdbrief_description: Data service that provides the list of id of the diecutters installed in the factory. - detailed_description: Data service that provides the id of the diecutter installed in the factory.
        The data service relies on the management database of the cardboard factory to provide the list of diecutter id.
        The data service takes no parameter and returns a list of integers, which are the id of the diecutters installed in the factory.

        Example usage:
        - The data service would be called as follows:
        diecutters_id = GetDiecuttersIdOfFactory.call()
        # assuming the diecutters id are [1, 2, 3]
        print(diecutters_id)  # [1, 2, 3]

        Things to keep in mind:
        - The diecutters id is a list of integers, so avoid trying to access it as a dictionary. - input_parameters: [] - output_values: ['diecutters_id:list'] - module: database - class_name: GetDiecuttersIdOfFactorybrief_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter.
        The data service relies on the management database of the cardboard factory to provide the chip id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the chip id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=123)
        # assuming the chip id is 456
        print(chip_id)  # 456

        Things to keep in mind:
        - The chip id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['chip_id:int'] - module: database - class_name: GetDiecutterChipIdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera1 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera1 id is 456
        print(camera1_id)  # 456

        Things to keep in mind:
        - The camera1 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera1_id:int'] - module: database - class_name: GetCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera2 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera2 id is 456
        print(camera2_id)  # 456

        Things to keep in mind:
        - The camera2 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera2_id:int'] - module: database - class_name: GetCamera2IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter.
        The data service relies on the management database of the cardboard factory to provide the session id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the current session id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=123)
        # assuming the session id is 456
        print(session_id)  # 456

        Things to keep in mind:
        - The session id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['session_id:int'] - module: database - class_name: GetCurrentSessionIdFromDiecutterIdbrief_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip. - detailed_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip.
        In general each diecutter has exactly one chip embedded into it, and each chip is uniquely identified by an integer id. 
        This means that the chip id has a one-to-one correspondence with the id of the diecutter, but those two ids may not be the same.
        This data service takes a single parameter, namely the id of the chip (an integer) and returns a single dictionary containing the current speed, temperature and number of rotations of the diecutter it is attached to.
        The keys of the dictionary are ""speed"", ""temperature"" and ""rotations"". 
        
        Example usage:
        - If the id of the chip is 123, then the data service would be called as follows:
        chip_id = 123
        current_data = GetCurrentData.call(chip_id=123)
        # get the current speed, temperature and number of rotations
        current_speed = data[""speed""]
        current_temperature = data[""temperature""]
        current_rotations = data[""rotations""]
    
        Things to keep in mind:
        - The refresh rate of the data is 1 second, i.e. the data is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - Note that the values in the dictionary represents the current values of the speed, etc. of the diecutter, they are not aggregated values.
        - Remember that the output value is a dictionary with the above specified keys, so avoid trying to access it using keys not in the above example. - input_parameters: ['chip_id:int'] - output_values: ['diecutter_current_data:dict'] - module: diecutter - class_name: GetCurrentDataFromChip","from data_services.database import GetDiecuttersIdOfFactory
from data_services.database import GetSerialCamera1IdFromDiecutterId
from data_services.database import GetSerialCamera2IdFromDiecutterId
import threading

def pipeline_function():
    diecutters_id = GetDiecuttersIdOfFactory.call()
    results = []

    def fetch_camera_serials(diecutter_id):
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=diecutter_id)
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)
        results.append({
            'diecutter_id': diecutter_id,
            'serial_camera1': serial_camera1,
            'serial_camera2': serial_camera2
        })

    threads = []
    for diecutter_id in diecutters_id:
        thread = threading.Thread(target=fetch_camera_serials, args=(diecutter_id,))
        threads.append(thread)
        thread.start()

    for thread in threads:
        thread.join()

    return results","+----+----------------+------------------+------------------+
|    |   diecutter_id |   serial_camera1 |   serial_camera2 |
|----+----------------+------------------+------------------|
|  0 |          60494 |           659422 |           228852 |
|  1 |          65125 |           452726 |           169015 |
|  2 |          15306 |           762265 |           217913 |
|  3 |          43936 |           120083 |           855200 |
|  4 |          77013 |           284217 |           681195 |
|  5 |          73691 |           622256 |           483483 |
+----+----------------+------------------+------------------+","[{'diecutter_id': 60494, 'serial_camera1': 659422, 'serial_camera2': 228852}, {'diecutter_id': 65125, 'serial_camera1': 452726, 'serial_camera2': 169015}, {'diecutter_id': 15306, 'serial_camera1': 762265, 'serial_camera2': 217913}, {'diecutter_id': 43936, 'serial_camera1': 120083, 'serial_camera2': 855200}, {'diecutter_id': 77013, 'serial_camera1': 284217, 'serial_camera2': 681195}, {'diecutter_id': 73691, 'serial_camera1': 622256, 'serial_camera2': 483483}]",Given 88888404 serial number tell me the type of camera and the diecutter it is installed on.,"from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.database import GetCamera2IdFromDiecutterId
from data_services.database import GetCurrentSessionIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
from data_services.camera2 import GetFrameFromCamera2
from data_services.camera2 import DetectErrorsInCardboardStackUsingCamera2
import threading
import time

def pipeline_function():
    diecutter_id = 14
    n_stacks = 30

    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=diecutter_id)
    camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)

    def check_error(camera2_id, frame, card_errors_res):
        has_error, error_type = DetectErrorsInCardboardStackUsingCamera2.call(camera2_id=camera2_id, frame=frame)
        card_errors_res['has_error'] = has_error
        card_errors_res['error_type'] = error_type
    
    def retrieve_diecutter_data(chip_id, diecutter_info_res):
        current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
        diecutter_info_res.update(current_data)

    results = []
    for _ in range(n_stacks):
        frame = GetFrameFromCamera2.call(camera2_id=camera2_id)
        timestamp = time.time()
        card_errors_res = {}
        card_errors = threading.Thread(target=check_error, args=(camera2_id, frame, card_errors_res))
        diecutter_info_res = {}
        diecutter_info = threading.Thread(target=retrieve_diecutter_data, args=(chip_id, diecutter_info_res))
        card_errors.start()
        diecutter_info.start()
        card_errors.join()
        diecutter_info.join()
        if card_errors_res['has_error']:
            result_row = {
                'timestamp': time.strftime(""%Y-%m-%d %H:%M:%S"", time.gmtime(timestamp)),
                'session_id': session_id,
                'error_type': card_errors_res['error_type'],
                'speed': diecutter_info_res['speed'],
                'temperature': diecutter_info_res['temperature'],
                'rotations': diecutter_info_res['rotations']
            }
            results.append(result_row)

    return results
"
q0,1,Provide a list of serial numbers for camera 1 and camera 2 from every diecutter within the factory.,"brief_description: Data service that, given the id of a camera1, provides a frame captured from that camera1. - detailed_description: Data service that, given the id of a camera1, provides a frame captured from that camera1.
        In general instances of camera1 point downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera1 (an integer) and returns a frame captured from that camera1 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera1 is 123, then the data service would be called as follows:
        camera1_id = 123
        frame = GetFrameFromCamera1.call(camera1_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int'] - output_values: ['frame:np.matrix'] - module: camera1 - class_name: GetFrameFromCamera1brief_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors and provide the type of error. - detailed_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors.
        Recall that a camera1 is a camera device that points downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera1 to use and the frame captured from that camera1.
        It returns a boolean value, True if the frame contains a cardboard with errors, False otherwise.
        Also it returns a integer value, 0 if the frame does not contain errors, 1 if the errors are of type hole and 2 if the errors are of type fold. 

        Example usage:
        - If frame is a variable containing the frame captured from the camera1 with id 123, then the data service would be called as follows:
        camera1_id = 123
        contains_errors, type_errors = DetectErrorsInCardboardUsingCamera1.call(camera1_id=123, frame=frame)

        Things to keep in mind:
        - The output is a tuple of boolean and integer, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool', 'error_type:int'] - module: camera1 - class_name: DetectErrorsInCardboardUsingCamera1brief_description: Data service that, given the id of a camera2, provides a frame captured from that camera2. - detailed_description: Data service that, given the id of a camera2, provides a frame captured from that camera2.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera2 (an integer) and returns a frame captured from that camera2 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera2 is 123, then the data service would be called as follows:
        camera2_id = 123
        frame = GetFrameFromCamera2.call(camera2_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int'] - output_values: ['frame:np.matrix'] - module: camera2 - class_name: GetFrameFromCamera2brief_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors. - detailed_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera2 to use and the frame captured from that camera2 that contains a stack of cardboards.
        It returns a boolean value, True if the frame contains a stack of cardboards with errors, False otherwise.

        Example usage:
        - If frame is a variable containing the frame captured from the camera2 with id 123, then the data service would be called as follows:
        camera2_id = 123
        contains_errors, error_type = DetectErrorsInCardboardStack.call(camera2_id=123, frame=frame)

        Things to keep in mind:
        - The output value is a boolean, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool'] - module: camera2 - class_name: DetectErrorsInCardboardStackUsingCamera2brief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera1 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera1.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera1)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera1:int'] - module: database - class_name: GetSerialCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera2 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera2.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera2)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera2:int'] - module: database - class_name: GetSerialCamera2IdFromDiecutterIdbrief_description: Data service that provides the list of id of the diecutters installed in the factory. - detailed_description: Data service that provides the id of the diecutter installed in the factory.
        The data service relies on the management database of the cardboard factory to provide the list of diecutter id.
        The data service takes no parameter and returns a list of integers, which are the id of the diecutters installed in the factory.

        Example usage:
        - The data service would be called as follows:
        diecutters_id = GetDiecuttersIdOfFactory.call()
        # assuming the diecutters id are [1, 2, 3]
        print(diecutters_id)  # [1, 2, 3]

        Things to keep in mind:
        - The diecutters id is a list of integers, so avoid trying to access it as a dictionary. - input_parameters: [] - output_values: ['diecutters_id:list'] - module: database - class_name: GetDiecuttersIdOfFactorybrief_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter.
        The data service relies on the management database of the cardboard factory to provide the chip id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the chip id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=123)
        # assuming the chip id is 456
        print(chip_id)  # 456

        Things to keep in mind:
        - The chip id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['chip_id:int'] - module: database - class_name: GetDiecutterChipIdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera1 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera1 id is 456
        print(camera1_id)  # 456

        Things to keep in mind:
        - The camera1 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera1_id:int'] - module: database - class_name: GetCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera2 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera2 id is 456
        print(camera2_id)  # 456

        Things to keep in mind:
        - The camera2 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera2_id:int'] - module: database - class_name: GetCamera2IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter.
        The data service relies on the management database of the cardboard factory to provide the session id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the current session id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=123)
        # assuming the session id is 456
        print(session_id)  # 456

        Things to keep in mind:
        - The session id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['session_id:int'] - module: database - class_name: GetCurrentSessionIdFromDiecutterIdbrief_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip. - detailed_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip.
        In general each diecutter has exactly one chip embedded into it, and each chip is uniquely identified by an integer id. 
        This means that the chip id has a one-to-one correspondence with the id of the diecutter, but those two ids may not be the same.
        This data service takes a single parameter, namely the id of the chip (an integer) and returns a single dictionary containing the current speed, temperature and number of rotations of the diecutter it is attached to.
        The keys of the dictionary are ""speed"", ""temperature"" and ""rotations"". 
        
        Example usage:
        - If the id of the chip is 123, then the data service would be called as follows:
        chip_id = 123
        current_data = GetCurrentData.call(chip_id=123)
        # get the current speed, temperature and number of rotations
        current_speed = data[""speed""]
        current_temperature = data[""temperature""]
        current_rotations = data[""rotations""]
    
        Things to keep in mind:
        - The refresh rate of the data is 1 second, i.e. the data is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - Note that the values in the dictionary represents the current values of the speed, etc. of the diecutter, they are not aggregated values.
        - Remember that the output value is a dictionary with the above specified keys, so avoid trying to access it using keys not in the above example. - input_parameters: ['chip_id:int'] - output_values: ['diecutter_current_data:dict'] - module: diecutter - class_name: GetCurrentDataFromChip","from data_services.database import GetDiecuttersIdOfFactory
from data_services.database import GetSerialCamera1IdFromDiecutterId
from data_services.database import GetSerialCamera2IdFromDiecutterId
import threading

def pipeline_function():
    diecutters_id = GetDiecuttersIdOfFactory.call()
    
    def fetch_camera_serials(diecutter_id, results):
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=diecutter_id)
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)
        results.append({
            'diecutter_id': diecutter_id,
            'serial_camera1': serial_camera1,
            'serial_camera2': serial_camera2
        })
    
    results = []
    threads = []
    for diecutter_id in diecutters_id:
        thread = threading.Thread(target=fetch_camera_serials, args=(diecutter_id, results))
        threads.append(thread)
        thread.start()
    
    for thread in threads:
        thread.join()
    
    return results","+----+----------------+------------------+------------------+
|    |   diecutter_id |   serial_camera1 |   serial_camera2 |
|----+----------------+------------------+------------------|
|  0 |          60494 |           659422 |           228852 |
|  1 |          65125 |           452726 |           169015 |
|  2 |          15306 |           762265 |           217913 |
|  3 |          43936 |           120083 |           855200 |
|  4 |          77013 |           284217 |           681195 |
|  5 |          73691 |           622256 |           483483 |
+----+----------------+------------------+------------------+","[{'diecutter_id': 60494, 'serial_camera1': 659422, 'serial_camera2': 228852}, {'diecutter_id': 65125, 'serial_camera1': 452726, 'serial_camera2': 169015}, {'diecutter_id': 15306, 'serial_camera1': 762265, 'serial_camera2': 217913}, {'diecutter_id': 43936, 'serial_camera1': 120083, 'serial_camera2': 855200}, {'diecutter_id': 77013, 'serial_camera1': 284217, 'serial_camera2': 681195}, {'diecutter_id': 73691, 'serial_camera1': 622256, 'serial_camera2': 483483}]",Given 88888404 serial number tell me the type of camera and the diecutter it is installed on.,"from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.database import GetCamera2IdFromDiecutterId
from data_services.database import GetCurrentSessionIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
from data_services.camera2 import GetFrameFromCamera2
from data_services.camera2 import DetectErrorsInCardboardStackUsingCamera2
import threading
import time

def pipeline_function():
    diecutter_id = 14
    n_stacks = 30

    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=diecutter_id)
    camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)

    def check_error(camera2_id, frame, card_errors_res):
        has_error, error_type = DetectErrorsInCardboardStackUsingCamera2.call(camera2_id=camera2_id, frame=frame)
        card_errors_res['has_error'] = has_error
        card_errors_res['error_type'] = error_type
    
    def retrieve_diecutter_data(chip_id, diecutter_info_res):
        current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
        diecutter_info_res.update(current_data)

    results = []
    for _ in range(n_stacks):
        frame = GetFrameFromCamera2.call(camera2_id=camera2_id)
        timestamp = time.time()
        card_errors_res = {}
        card_errors = threading.Thread(target=check_error, args=(camera2_id, frame, card_errors_res))
        diecutter_info_res = {}
        diecutter_info = threading.Thread(target=retrieve_diecutter_data, args=(chip_id, diecutter_info_res))
        card_errors.start()
        diecutter_info.start()
        card_errors.join()
        diecutter_info.join()
        if card_errors_res['has_error']:
            result_row = {
                'timestamp': time.strftime(""%Y-%m-%d %H:%M:%S"", time.gmtime(timestamp)),
                'session_id': session_id,
                'error_type': card_errors_res['error_type'],
                'speed': diecutter_info_res['speed'],
                'temperature': diecutter_info_res['temperature'],
                'rotations': diecutter_info_res['rotations']
            }
            results.append(result_row)

    return results
"
q0,2,Provide the serial numbers for camera 1 and camera 2 from every diecutter within the factory.,"brief_description: Data service that, given the id of a camera1, provides a frame captured from that camera1. - detailed_description: Data service that, given the id of a camera1, provides a frame captured from that camera1.
        In general instances of camera1 point downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera1 (an integer) and returns a frame captured from that camera1 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera1 is 123, then the data service would be called as follows:
        camera1_id = 123
        frame = GetFrameFromCamera1.call(camera1_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int'] - output_values: ['frame:np.matrix'] - module: camera1 - class_name: GetFrameFromCamera1brief_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors and provide the type of error. - detailed_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors.
        Recall that a camera1 is a camera device that points downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera1 to use and the frame captured from that camera1.
        It returns a boolean value, True if the frame contains a cardboard with errors, False otherwise.
        Also it returns a integer value, 0 if the frame does not contain errors, 1 if the errors are of type hole and 2 if the errors are of type fold. 

        Example usage:
        - If frame is a variable containing the frame captured from the camera1 with id 123, then the data service would be called as follows:
        camera1_id = 123
        contains_errors, type_errors = DetectErrorsInCardboardUsingCamera1.call(camera1_id=123, frame=frame)

        Things to keep in mind:
        - The output is a tuple of boolean and integer, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool', 'error_type:int'] - module: camera1 - class_name: DetectErrorsInCardboardUsingCamera1brief_description: Data service that, given the id of a camera2, provides a frame captured from that camera2. - detailed_description: Data service that, given the id of a camera2, provides a frame captured from that camera2.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera2 (an integer) and returns a frame captured from that camera2 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera2 is 123, then the data service would be called as follows:
        camera2_id = 123
        frame = GetFrameFromCamera2.call(camera2_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int'] - output_values: ['frame:np.matrix'] - module: camera2 - class_name: GetFrameFromCamera2brief_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors. - detailed_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera2 to use and the frame captured from that camera2 that contains a stack of cardboards.
        It returns a boolean value, True if the frame contains a stack of cardboards with errors, False otherwise.

        Example usage:
        - If frame is a variable containing the frame captured from the camera2 with id 123, then the data service would be called as follows:
        camera2_id = 123
        contains_errors, error_type = DetectErrorsInCardboardStack.call(camera2_id=123, frame=frame)

        Things to keep in mind:
        - The output value is a boolean, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool'] - module: camera2 - class_name: DetectErrorsInCardboardStackUsingCamera2brief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera1 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera1.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera1)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera1:int'] - module: database - class_name: GetSerialCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera2 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera2.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera2)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera2:int'] - module: database - class_name: GetSerialCamera2IdFromDiecutterIdbrief_description: Data service that provides the list of id of the diecutters installed in the factory. - detailed_description: Data service that provides the id of the diecutter installed in the factory.
        The data service relies on the management database of the cardboard factory to provide the list of diecutter id.
        The data service takes no parameter and returns a list of integers, which are the id of the diecutters installed in the factory.

        Example usage:
        - The data service would be called as follows:
        diecutters_id = GetDiecuttersIdOfFactory.call()
        # assuming the diecutters id are [1, 2, 3]
        print(diecutters_id)  # [1, 2, 3]

        Things to keep in mind:
        - The diecutters id is a list of integers, so avoid trying to access it as a dictionary. - input_parameters: [] - output_values: ['diecutters_id:list'] - module: database - class_name: GetDiecuttersIdOfFactorybrief_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter.
        The data service relies on the management database of the cardboard factory to provide the chip id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the chip id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=123)
        # assuming the chip id is 456
        print(chip_id)  # 456

        Things to keep in mind:
        - The chip id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['chip_id:int'] - module: database - class_name: GetDiecutterChipIdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera1 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera1 id is 456
        print(camera1_id)  # 456

        Things to keep in mind:
        - The camera1 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera1_id:int'] - module: database - class_name: GetCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera2 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera2 id is 456
        print(camera2_id)  # 456

        Things to keep in mind:
        - The camera2 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera2_id:int'] - module: database - class_name: GetCamera2IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter.
        The data service relies on the management database of the cardboard factory to provide the session id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the current session id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=123)
        # assuming the session id is 456
        print(session_id)  # 456

        Things to keep in mind:
        - The session id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['session_id:int'] - module: database - class_name: GetCurrentSessionIdFromDiecutterIdbrief_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip. - detailed_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip.
        In general each diecutter has exactly one chip embedded into it, and each chip is uniquely identified by an integer id. 
        This means that the chip id has a one-to-one correspondence with the id of the diecutter, but those two ids may not be the same.
        This data service takes a single parameter, namely the id of the chip (an integer) and returns a single dictionary containing the current speed, temperature and number of rotations of the diecutter it is attached to.
        The keys of the dictionary are ""speed"", ""temperature"" and ""rotations"". 
        
        Example usage:
        - If the id of the chip is 123, then the data service would be called as follows:
        chip_id = 123
        current_data = GetCurrentData.call(chip_id=123)
        # get the current speed, temperature and number of rotations
        current_speed = data[""speed""]
        current_temperature = data[""temperature""]
        current_rotations = data[""rotations""]
    
        Things to keep in mind:
        - The refresh rate of the data is 1 second, i.e. the data is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - Note that the values in the dictionary represents the current values of the speed, etc. of the diecutter, they are not aggregated values.
        - Remember that the output value is a dictionary with the above specified keys, so avoid trying to access it using keys not in the above example. - input_parameters: ['chip_id:int'] - output_values: ['diecutter_current_data:dict'] - module: diecutter - class_name: GetCurrentDataFromChip","from data_services.database import GetDiecuttersIdOfFactory
from data_services.database import GetSerialCamera1IdFromDiecutterId
from data_services.database import GetSerialCamera2IdFromDiecutterId
import threading

def pipeline_function():
    diecutters_id = GetDiecuttersIdOfFactory.call()
    results = []
    
    def fetch_camera_serials(diecutter_id, results):
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=diecutter_id)
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)
        results.append({
            'diecutter_id': diecutter_id,
            'serial_camera1': serial_camera1,
            'serial_camera2': serial_camera2
        })
    
    threads = []
    for diecutter_id in diecutters_id:
        thread = threading.Thread(target=fetch_camera_serials, args=(diecutter_id, results))
        threads.append(thread)
        thread.start()
    
    for thread in threads:
        thread.join()
    
    return results","+----+----------------+------------------+------------------+
|    |   diecutter_id |   serial_camera1 |   serial_camera2 |
|----+----------------+------------------+------------------|
|  0 |          60494 |           659422 |           228852 |
|  1 |          65125 |           452726 |           169015 |
|  2 |          15306 |           762265 |           217913 |
|  3 |          43936 |           120083 |           855200 |
|  4 |          77013 |           284217 |           681195 |
|  5 |          73691 |           622256 |           483483 |
+----+----------------+------------------+------------------+","[{'diecutter_id': 60494, 'serial_camera1': 659422, 'serial_camera2': 228852}, {'diecutter_id': 65125, 'serial_camera1': 452726, 'serial_camera2': 169015}, {'diecutter_id': 15306, 'serial_camera1': 762265, 'serial_camera2': 217913}, {'diecutter_id': 43936, 'serial_camera1': 120083, 'serial_camera2': 855200}, {'diecutter_id': 77013, 'serial_camera1': 284217, 'serial_camera2': 681195}, {'diecutter_id': 73691, 'serial_camera1': 622256, 'serial_camera2': 483483}]",Given 88888404 serial number tell me the type of camera and the diecutter it is installed on.,"from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.database import GetCamera2IdFromDiecutterId
from data_services.database import GetCurrentSessionIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
from data_services.camera2 import GetFrameFromCamera2
from data_services.camera2 import DetectErrorsInCardboardStackUsingCamera2
import threading
import time

def pipeline_function():
    diecutter_id = 14
    n_stacks = 30

    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=diecutter_id)
    camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)

    def check_error(camera2_id, frame, card_errors_res):
        has_error, error_type = DetectErrorsInCardboardStackUsingCamera2.call(camera2_id=camera2_id, frame=frame)
        card_errors_res['has_error'] = has_error
        card_errors_res['error_type'] = error_type
    
    def retrieve_diecutter_data(chip_id, diecutter_info_res):
        current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
        diecutter_info_res.update(current_data)

    results = []
    for _ in range(n_stacks):
        frame = GetFrameFromCamera2.call(camera2_id=camera2_id)
        timestamp = time.time()
        card_errors_res = {}
        card_errors = threading.Thread(target=check_error, args=(camera2_id, frame, card_errors_res))
        diecutter_info_res = {}
        diecutter_info = threading.Thread(target=retrieve_diecutter_data, args=(chip_id, diecutter_info_res))
        card_errors.start()
        diecutter_info.start()
        card_errors.join()
        diecutter_info.join()
        if card_errors_res['has_error']:
            result_row = {
                'timestamp': time.strftime(""%Y-%m-%d %H:%M:%S"", time.gmtime(timestamp)),
                'session_id': session_id,
                'error_type': card_errors_res['error_type'],
                'speed': diecutter_info_res['speed'],
                'temperature': diecutter_info_res['temperature'],
                'rotations': diecutter_info_res['rotations']
            }
            results.append(result_row)

    return results
"
q0,3,Provide the serial numbers for both camera one and camera two from every diecutter within the plant.,"brief_description: Data service that, given the id of a camera1, provides a frame captured from that camera1. - detailed_description: Data service that, given the id of a camera1, provides a frame captured from that camera1.
        In general instances of camera1 point downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera1 (an integer) and returns a frame captured from that camera1 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera1 is 123, then the data service would be called as follows:
        camera1_id = 123
        frame = GetFrameFromCamera1.call(camera1_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int'] - output_values: ['frame:np.matrix'] - module: camera1 - class_name: GetFrameFromCamera1brief_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors and provide the type of error. - detailed_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors.
        Recall that a camera1 is a camera device that points downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera1 to use and the frame captured from that camera1.
        It returns a boolean value, True if the frame contains a cardboard with errors, False otherwise.
        Also it returns a integer value, 0 if the frame does not contain errors, 1 if the errors are of type hole and 2 if the errors are of type fold. 

        Example usage:
        - If frame is a variable containing the frame captured from the camera1 with id 123, then the data service would be called as follows:
        camera1_id = 123
        contains_errors, type_errors = DetectErrorsInCardboardUsingCamera1.call(camera1_id=123, frame=frame)

        Things to keep in mind:
        - The output is a tuple of boolean and integer, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool', 'error_type:int'] - module: camera1 - class_name: DetectErrorsInCardboardUsingCamera1brief_description: Data service that, given the id of a camera2, provides a frame captured from that camera2. - detailed_description: Data service that, given the id of a camera2, provides a frame captured from that camera2.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera2 (an integer) and returns a frame captured from that camera2 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera2 is 123, then the data service would be called as follows:
        camera2_id = 123
        frame = GetFrameFromCamera2.call(camera2_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int'] - output_values: ['frame:np.matrix'] - module: camera2 - class_name: GetFrameFromCamera2brief_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors. - detailed_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera2 to use and the frame captured from that camera2 that contains a stack of cardboards.
        It returns a boolean value, True if the frame contains a stack of cardboards with errors, False otherwise.

        Example usage:
        - If frame is a variable containing the frame captured from the camera2 with id 123, then the data service would be called as follows:
        camera2_id = 123
        contains_errors, error_type = DetectErrorsInCardboardStack.call(camera2_id=123, frame=frame)

        Things to keep in mind:
        - The output value is a boolean, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool'] - module: camera2 - class_name: DetectErrorsInCardboardStackUsingCamera2brief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera1 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera1.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera1)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera1:int'] - module: database - class_name: GetSerialCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera2 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera2.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera2)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera2:int'] - module: database - class_name: GetSerialCamera2IdFromDiecutterIdbrief_description: Data service that provides the list of id of the diecutters installed in the factory. - detailed_description: Data service that provides the id of the diecutter installed in the factory.
        The data service relies on the management database of the cardboard factory to provide the list of diecutter id.
        The data service takes no parameter and returns a list of integers, which are the id of the diecutters installed in the factory.

        Example usage:
        - The data service would be called as follows:
        diecutters_id = GetDiecuttersIdOfFactory.call()
        # assuming the diecutters id are [1, 2, 3]
        print(diecutters_id)  # [1, 2, 3]

        Things to keep in mind:
        - The diecutters id is a list of integers, so avoid trying to access it as a dictionary. - input_parameters: [] - output_values: ['diecutters_id:list'] - module: database - class_name: GetDiecuttersIdOfFactorybrief_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter.
        The data service relies on the management database of the cardboard factory to provide the chip id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the chip id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=123)
        # assuming the chip id is 456
        print(chip_id)  # 456

        Things to keep in mind:
        - The chip id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['chip_id:int'] - module: database - class_name: GetDiecutterChipIdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera1 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera1 id is 456
        print(camera1_id)  # 456

        Things to keep in mind:
        - The camera1 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera1_id:int'] - module: database - class_name: GetCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera2 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera2 id is 456
        print(camera2_id)  # 456

        Things to keep in mind:
        - The camera2 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera2_id:int'] - module: database - class_name: GetCamera2IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter.
        The data service relies on the management database of the cardboard factory to provide the session id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the current session id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=123)
        # assuming the session id is 456
        print(session_id)  # 456

        Things to keep in mind:
        - The session id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['session_id:int'] - module: database - class_name: GetCurrentSessionIdFromDiecutterIdbrief_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip. - detailed_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip.
        In general each diecutter has exactly one chip embedded into it, and each chip is uniquely identified by an integer id. 
        This means that the chip id has a one-to-one correspondence with the id of the diecutter, but those two ids may not be the same.
        This data service takes a single parameter, namely the id of the chip (an integer) and returns a single dictionary containing the current speed, temperature and number of rotations of the diecutter it is attached to.
        The keys of the dictionary are ""speed"", ""temperature"" and ""rotations"". 
        
        Example usage:
        - If the id of the chip is 123, then the data service would be called as follows:
        chip_id = 123
        current_data = GetCurrentData.call(chip_id=123)
        # get the current speed, temperature and number of rotations
        current_speed = data[""speed""]
        current_temperature = data[""temperature""]
        current_rotations = data[""rotations""]
    
        Things to keep in mind:
        - The refresh rate of the data is 1 second, i.e. the data is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - Note that the values in the dictionary represents the current values of the speed, etc. of the diecutter, they are not aggregated values.
        - Remember that the output value is a dictionary with the above specified keys, so avoid trying to access it using keys not in the above example. - input_parameters: ['chip_id:int'] - output_values: ['diecutter_current_data:dict'] - module: diecutter - class_name: GetCurrentDataFromChip","from data_services.database import GetDiecuttersIdOfFactory
from data_services.database import GetSerialCamera1IdFromDiecutterId
from data_services.database import GetSerialCamera2IdFromDiecutterId
import threading

def pipeline_function():
    diecutters_id = GetDiecuttersIdOfFactory.call()
    results = []

    def fetch_camera_serials(diecutter_id):
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=diecutter_id)
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)
        results.append({
            'diecutter_id': diecutter_id,
            'serial_camera1': serial_camera1,
            'serial_camera2': serial_camera2
        })

    threads = []
    for diecutter_id in diecutters_id:
        thread = threading.Thread(target=fetch_camera_serials, args=(diecutter_id,))
        threads.append(thread)
        thread.start()

    for thread in threads:
        thread.join()

    return results","+----+----------------+------------------+------------------+
|    |   diecutter_id |   serial_camera1 |   serial_camera2 |
|----+----------------+------------------+------------------|
|  0 |          60494 |           659422 |           228852 |
|  1 |          65125 |           452726 |           169015 |
|  2 |          15306 |           762265 |           217913 |
|  3 |          43936 |           120083 |           855200 |
|  4 |          77013 |           284217 |           681195 |
|  5 |          73691 |           622256 |           483483 |
+----+----------------+------------------+------------------+","[{'diecutter_id': 60494, 'serial_camera1': 659422, 'serial_camera2': 228852}, {'diecutter_id': 65125, 'serial_camera1': 452726, 'serial_camera2': 169015}, {'diecutter_id': 15306, 'serial_camera1': 762265, 'serial_camera2': 217913}, {'diecutter_id': 43936, 'serial_camera1': 120083, 'serial_camera2': 855200}, {'diecutter_id': 77013, 'serial_camera1': 284217, 'serial_camera2': 681195}, {'diecutter_id': 73691, 'serial_camera1': 622256, 'serial_camera2': 483483}]",Given 88888404 serial number tell me the type of camera and the diecutter it is installed on.,"from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.database import GetCamera2IdFromDiecutterId
from data_services.database import GetCurrentSessionIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
from data_services.camera2 import GetFrameFromCamera2
from data_services.camera2 import DetectErrorsInCardboardStackUsingCamera2
import threading
import time

def pipeline_function():
    diecutter_id = 14
    n_stacks = 30

    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=diecutter_id)
    camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)

    def check_error(camera2_id, frame, card_errors_res):
        has_error, error_type = DetectErrorsInCardboardStackUsingCamera2.call(camera2_id=camera2_id, frame=frame)
        card_errors_res['has_error'] = has_error
        card_errors_res['error_type'] = error_type
    
    def retrieve_diecutter_data(chip_id, diecutter_info_res):
        current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
        diecutter_info_res.update(current_data)

    results = []
    for _ in range(n_stacks):
        frame = GetFrameFromCamera2.call(camera2_id=camera2_id)
        timestamp = time.time()
        card_errors_res = {}
        card_errors = threading.Thread(target=check_error, args=(camera2_id, frame, card_errors_res))
        diecutter_info_res = {}
        diecutter_info = threading.Thread(target=retrieve_diecutter_data, args=(chip_id, diecutter_info_res))
        card_errors.start()
        diecutter_info.start()
        card_errors.join()
        diecutter_info.join()
        if card_errors_res['has_error']:
            result_row = {
                'timestamp': time.strftime(""%Y-%m-%d %H:%M:%S"", time.gmtime(timestamp)),
                'session_id': session_id,
                'error_type': card_errors_res['error_type'],
                'speed': diecutter_info_res['speed'],
                'temperature': diecutter_info_res['temperature'],
                'rotations': diecutter_info_res['rotations']
            }
            results.append(result_row)

    return results
"
q0,4,List the serial numbers for camera 1 and camera 2 associated with each diecutter throughout the factory.,"brief_description: Data service that, given the id of a camera1, provides a frame captured from that camera1. - detailed_description: Data service that, given the id of a camera1, provides a frame captured from that camera1.
        In general instances of camera1 point downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera1 (an integer) and returns a frame captured from that camera1 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera1 is 123, then the data service would be called as follows:
        camera1_id = 123
        frame = GetFrameFromCamera1.call(camera1_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int'] - output_values: ['frame:np.matrix'] - module: camera1 - class_name: GetFrameFromCamera1brief_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors and provide the type of error. - detailed_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors.
        Recall that a camera1 is a camera device that points downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera1 to use and the frame captured from that camera1.
        It returns a boolean value, True if the frame contains a cardboard with errors, False otherwise.
        Also it returns a integer value, 0 if the frame does not contain errors, 1 if the errors are of type hole and 2 if the errors are of type fold. 

        Example usage:
        - If frame is a variable containing the frame captured from the camera1 with id 123, then the data service would be called as follows:
        camera1_id = 123
        contains_errors, type_errors = DetectErrorsInCardboardUsingCamera1.call(camera1_id=123, frame=frame)

        Things to keep in mind:
        - The output is a tuple of boolean and integer, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool', 'error_type:int'] - module: camera1 - class_name: DetectErrorsInCardboardUsingCamera1brief_description: Data service that, given the id of a camera2, provides a frame captured from that camera2. - detailed_description: Data service that, given the id of a camera2, provides a frame captured from that camera2.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera2 (an integer) and returns a frame captured from that camera2 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera2 is 123, then the data service would be called as follows:
        camera2_id = 123
        frame = GetFrameFromCamera2.call(camera2_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int'] - output_values: ['frame:np.matrix'] - module: camera2 - class_name: GetFrameFromCamera2brief_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors. - detailed_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera2 to use and the frame captured from that camera2 that contains a stack of cardboards.
        It returns a boolean value, True if the frame contains a stack of cardboards with errors, False otherwise.

        Example usage:
        - If frame is a variable containing the frame captured from the camera2 with id 123, then the data service would be called as follows:
        camera2_id = 123
        contains_errors, error_type = DetectErrorsInCardboardStack.call(camera2_id=123, frame=frame)

        Things to keep in mind:
        - The output value is a boolean, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool'] - module: camera2 - class_name: DetectErrorsInCardboardStackUsingCamera2brief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera1 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera1.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera1)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera1:int'] - module: database - class_name: GetSerialCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera2 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera2.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera2)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera2:int'] - module: database - class_name: GetSerialCamera2IdFromDiecutterIdbrief_description: Data service that provides the list of id of the diecutters installed in the factory. - detailed_description: Data service that provides the id of the diecutter installed in the factory.
        The data service relies on the management database of the cardboard factory to provide the list of diecutter id.
        The data service takes no parameter and returns a list of integers, which are the id of the diecutters installed in the factory.

        Example usage:
        - The data service would be called as follows:
        diecutters_id = GetDiecuttersIdOfFactory.call()
        # assuming the diecutters id are [1, 2, 3]
        print(diecutters_id)  # [1, 2, 3]

        Things to keep in mind:
        - The diecutters id is a list of integers, so avoid trying to access it as a dictionary. - input_parameters: [] - output_values: ['diecutters_id:list'] - module: database - class_name: GetDiecuttersIdOfFactorybrief_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter.
        The data service relies on the management database of the cardboard factory to provide the chip id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the chip id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=123)
        # assuming the chip id is 456
        print(chip_id)  # 456

        Things to keep in mind:
        - The chip id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['chip_id:int'] - module: database - class_name: GetDiecutterChipIdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera1 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera1 id is 456
        print(camera1_id)  # 456

        Things to keep in mind:
        - The camera1 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera1_id:int'] - module: database - class_name: GetCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera2 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera2 id is 456
        print(camera2_id)  # 456

        Things to keep in mind:
        - The camera2 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera2_id:int'] - module: database - class_name: GetCamera2IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter.
        The data service relies on the management database of the cardboard factory to provide the session id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the current session id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=123)
        # assuming the session id is 456
        print(session_id)  # 456

        Things to keep in mind:
        - The session id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['session_id:int'] - module: database - class_name: GetCurrentSessionIdFromDiecutterIdbrief_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip. - detailed_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip.
        In general each diecutter has exactly one chip embedded into it, and each chip is uniquely identified by an integer id. 
        This means that the chip id has a one-to-one correspondence with the id of the diecutter, but those two ids may not be the same.
        This data service takes a single parameter, namely the id of the chip (an integer) and returns a single dictionary containing the current speed, temperature and number of rotations of the diecutter it is attached to.
        The keys of the dictionary are ""speed"", ""temperature"" and ""rotations"". 
        
        Example usage:
        - If the id of the chip is 123, then the data service would be called as follows:
        chip_id = 123
        current_data = GetCurrentData.call(chip_id=123)
        # get the current speed, temperature and number of rotations
        current_speed = data[""speed""]
        current_temperature = data[""temperature""]
        current_rotations = data[""rotations""]
    
        Things to keep in mind:
        - The refresh rate of the data is 1 second, i.e. the data is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - Note that the values in the dictionary represents the current values of the speed, etc. of the diecutter, they are not aggregated values.
        - Remember that the output value is a dictionary with the above specified keys, so avoid trying to access it using keys not in the above example. - input_parameters: ['chip_id:int'] - output_values: ['diecutter_current_data:dict'] - module: diecutter - class_name: GetCurrentDataFromChip","from data_services.database import GetDiecuttersIdOfFactory
from data_services.database import GetSerialCamera1IdFromDiecutterId
from data_services.database import GetSerialCamera2IdFromDiecutterId
import threading

def pipeline_function():
    diecutters_id = GetDiecuttersIdOfFactory.call()
    
    def fetch_camera_serials(diecutter_id, results):
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=diecutter_id)
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)
        results.append({
            'diecutter_id': diecutter_id,
            'serial_camera1': serial_camera1,
            'serial_camera2': serial_camera2
        })
    
    results = []
    threads = []
    for diecutter_id in diecutters_id:
        thread = threading.Thread(target=fetch_camera_serials, args=(diecutter_id, results))
        threads.append(thread)
        thread.start()
    
    for thread in threads:
        thread.join()
    
    return results","+----+----------------+------------------+------------------+
|    |   diecutter_id |   serial_camera1 |   serial_camera2 |
|----+----------------+------------------+------------------|
|  0 |          60494 |           659422 |           228852 |
|  1 |          65125 |           452726 |           169015 |
|  2 |          15306 |           762265 |           217913 |
|  3 |          43936 |           120083 |           855200 |
|  4 |          77013 |           284217 |           681195 |
|  5 |          73691 |           622256 |           483483 |
+----+----------------+------------------+------------------+","[{'diecutter_id': 60494, 'serial_camera1': 659422, 'serial_camera2': 228852}, {'diecutter_id': 65125, 'serial_camera1': 452726, 'serial_camera2': 169015}, {'diecutter_id': 15306, 'serial_camera1': 762265, 'serial_camera2': 217913}, {'diecutter_id': 43936, 'serial_camera1': 120083, 'serial_camera2': 855200}, {'diecutter_id': 77013, 'serial_camera1': 284217, 'serial_camera2': 681195}, {'diecutter_id': 73691, 'serial_camera1': 622256, 'serial_camera2': 483483}]",Given 88888404 serial number tell me the type of camera and the diecutter it is installed on.,"from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.database import GetCamera2IdFromDiecutterId
from data_services.database import GetCurrentSessionIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
from data_services.camera2 import GetFrameFromCamera2
from data_services.camera2 import DetectErrorsInCardboardStackUsingCamera2
import threading
import time

def pipeline_function():
    diecutter_id = 14
    n_stacks = 30

    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=diecutter_id)
    camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)

    def check_error(camera2_id, frame, card_errors_res):
        has_error, error_type = DetectErrorsInCardboardStackUsingCamera2.call(camera2_id=camera2_id, frame=frame)
        card_errors_res['has_error'] = has_error
        card_errors_res['error_type'] = error_type
    
    def retrieve_diecutter_data(chip_id, diecutter_info_res):
        current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
        diecutter_info_res.update(current_data)

    results = []
    for _ in range(n_stacks):
        frame = GetFrameFromCamera2.call(camera2_id=camera2_id)
        timestamp = time.time()
        card_errors_res = {}
        card_errors = threading.Thread(target=check_error, args=(camera2_id, frame, card_errors_res))
        diecutter_info_res = {}
        diecutter_info = threading.Thread(target=retrieve_diecutter_data, args=(chip_id, diecutter_info_res))
        card_errors.start()
        diecutter_info.start()
        card_errors.join()
        diecutter_info.join()
        if card_errors_res['has_error']:
            result_row = {
                'timestamp': time.strftime(""%Y-%m-%d %H:%M:%S"", time.gmtime(timestamp)),
                'session_id': session_id,
                'error_type': card_errors_res['error_type'],
                'speed': diecutter_info_res['speed'],
                'temperature': diecutter_info_res['temperature'],
                'rotations': diecutter_info_res['rotations']
            }
            results.append(result_row)

    return results
"
q0,5,Provide a list showing the serial numbers for camera 1 and camera 2 associated with every diecutter within the factory.,"brief_description: Data service that, given the id of a camera1, provides a frame captured from that camera1. - detailed_description: Data service that, given the id of a camera1, provides a frame captured from that camera1.
        In general instances of camera1 point downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera1 (an integer) and returns a frame captured from that camera1 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera1 is 123, then the data service would be called as follows:
        camera1_id = 123
        frame = GetFrameFromCamera1.call(camera1_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int'] - output_values: ['frame:np.matrix'] - module: camera1 - class_name: GetFrameFromCamera1brief_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors and provide the type of error. - detailed_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors.
        Recall that a camera1 is a camera device that points downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera1 to use and the frame captured from that camera1.
        It returns a boolean value, True if the frame contains a cardboard with errors, False otherwise.
        Also it returns a integer value, 0 if the frame does not contain errors, 1 if the errors are of type hole and 2 if the errors are of type fold. 

        Example usage:
        - If frame is a variable containing the frame captured from the camera1 with id 123, then the data service would be called as follows:
        camera1_id = 123
        contains_errors, type_errors = DetectErrorsInCardboardUsingCamera1.call(camera1_id=123, frame=frame)

        Things to keep in mind:
        - The output is a tuple of boolean and integer, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool', 'error_type:int'] - module: camera1 - class_name: DetectErrorsInCardboardUsingCamera1brief_description: Data service that, given the id of a camera2, provides a frame captured from that camera2. - detailed_description: Data service that, given the id of a camera2, provides a frame captured from that camera2.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera2 (an integer) and returns a frame captured from that camera2 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera2 is 123, then the data service would be called as follows:
        camera2_id = 123
        frame = GetFrameFromCamera2.call(camera2_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int'] - output_values: ['frame:np.matrix'] - module: camera2 - class_name: GetFrameFromCamera2brief_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors. - detailed_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera2 to use and the frame captured from that camera2 that contains a stack of cardboards.
        It returns a boolean value, True if the frame contains a stack of cardboards with errors, False otherwise.

        Example usage:
        - If frame is a variable containing the frame captured from the camera2 with id 123, then the data service would be called as follows:
        camera2_id = 123
        contains_errors, error_type = DetectErrorsInCardboardStack.call(camera2_id=123, frame=frame)

        Things to keep in mind:
        - The output value is a boolean, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool'] - module: camera2 - class_name: DetectErrorsInCardboardStackUsingCamera2brief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera1 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera1.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera1)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera1:int'] - module: database - class_name: GetSerialCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera2 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera2.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera2)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera2:int'] - module: database - class_name: GetSerialCamera2IdFromDiecutterIdbrief_description: Data service that provides the list of id of the diecutters installed in the factory. - detailed_description: Data service that provides the id of the diecutter installed in the factory.
        The data service relies on the management database of the cardboard factory to provide the list of diecutter id.
        The data service takes no parameter and returns a list of integers, which are the id of the diecutters installed in the factory.

        Example usage:
        - The data service would be called as follows:
        diecutters_id = GetDiecuttersIdOfFactory.call()
        # assuming the diecutters id are [1, 2, 3]
        print(diecutters_id)  # [1, 2, 3]

        Things to keep in mind:
        - The diecutters id is a list of integers, so avoid trying to access it as a dictionary. - input_parameters: [] - output_values: ['diecutters_id:list'] - module: database - class_name: GetDiecuttersIdOfFactorybrief_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter.
        The data service relies on the management database of the cardboard factory to provide the chip id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the chip id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=123)
        # assuming the chip id is 456
        print(chip_id)  # 456

        Things to keep in mind:
        - The chip id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['chip_id:int'] - module: database - class_name: GetDiecutterChipIdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera1 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera1 id is 456
        print(camera1_id)  # 456

        Things to keep in mind:
        - The camera1 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera1_id:int'] - module: database - class_name: GetCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera2 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera2 id is 456
        print(camera2_id)  # 456

        Things to keep in mind:
        - The camera2 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera2_id:int'] - module: database - class_name: GetCamera2IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter.
        The data service relies on the management database of the cardboard factory to provide the session id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the current session id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=123)
        # assuming the session id is 456
        print(session_id)  # 456

        Things to keep in mind:
        - The session id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['session_id:int'] - module: database - class_name: GetCurrentSessionIdFromDiecutterIdbrief_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip. - detailed_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip.
        In general each diecutter has exactly one chip embedded into it, and each chip is uniquely identified by an integer id. 
        This means that the chip id has a one-to-one correspondence with the id of the diecutter, but those two ids may not be the same.
        This data service takes a single parameter, namely the id of the chip (an integer) and returns a single dictionary containing the current speed, temperature and number of rotations of the diecutter it is attached to.
        The keys of the dictionary are ""speed"", ""temperature"" and ""rotations"". 
        
        Example usage:
        - If the id of the chip is 123, then the data service would be called as follows:
        chip_id = 123
        current_data = GetCurrentData.call(chip_id=123)
        # get the current speed, temperature and number of rotations
        current_speed = data[""speed""]
        current_temperature = data[""temperature""]
        current_rotations = data[""rotations""]
    
        Things to keep in mind:
        - The refresh rate of the data is 1 second, i.e. the data is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - Note that the values in the dictionary represents the current values of the speed, etc. of the diecutter, they are not aggregated values.
        - Remember that the output value is a dictionary with the above specified keys, so avoid trying to access it using keys not in the above example. - input_parameters: ['chip_id:int'] - output_values: ['diecutter_current_data:dict'] - module: diecutter - class_name: GetCurrentDataFromChip","from data_services.database import GetDiecuttersIdOfFactory
from data_services.database import GetSerialCamera1IdFromDiecutterId
from data_services.database import GetSerialCamera2IdFromDiecutterId
import threading

def pipeline_function():
    diecutters_id = GetDiecuttersIdOfFactory.call()
    
    def fetch_camera_serials(diecutter_id, results):
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=diecutter_id)
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)
        results.append({
            'diecutter_id': diecutter_id,
            'serial_camera1': serial_camera1,
            'serial_camera2': serial_camera2
        })
    
    results = []
    threads = []
    for diecutter_id in diecutters_id:
        thread = threading.Thread(target=fetch_camera_serials, args=(diecutter_id, results))
        threads.append(thread)
        thread.start()
    
    for thread in threads:
        thread.join()
    
    return results","+----+----------------+------------------+------------------+
|    |   diecutter_id |   serial_camera1 |   serial_camera2 |
|----+----------------+------------------+------------------|
|  0 |          60494 |           659422 |           228852 |
|  1 |          65125 |           452726 |           169015 |
|  2 |          15306 |           762265 |           217913 |
|  3 |          43936 |           120083 |           855200 |
|  4 |          77013 |           284217 |           681195 |
|  5 |          73691 |           622256 |           483483 |
+----+----------------+------------------+------------------+","[{'diecutter_id': 60494, 'serial_camera1': 659422, 'serial_camera2': 228852}, {'diecutter_id': 65125, 'serial_camera1': 452726, 'serial_camera2': 169015}, {'diecutter_id': 15306, 'serial_camera1': 762265, 'serial_camera2': 217913}, {'diecutter_id': 43936, 'serial_camera1': 120083, 'serial_camera2': 855200}, {'diecutter_id': 77013, 'serial_camera1': 284217, 'serial_camera2': 681195}, {'diecutter_id': 73691, 'serial_camera1': 622256, 'serial_camera2': 483483}]",Given 88888404 serial number tell me the type of camera and the diecutter it is installed on.,"from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.database import GetCamera2IdFromDiecutterId
from data_services.database import GetCurrentSessionIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
from data_services.camera2 import GetFrameFromCamera2
from data_services.camera2 import DetectErrorsInCardboardStackUsingCamera2
import threading
import time

def pipeline_function():
    diecutter_id = 14
    n_stacks = 30

    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=diecutter_id)
    camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)

    def check_error(camera2_id, frame, card_errors_res):
        has_error, error_type = DetectErrorsInCardboardStackUsingCamera2.call(camera2_id=camera2_id, frame=frame)
        card_errors_res['has_error'] = has_error
        card_errors_res['error_type'] = error_type
    
    def retrieve_diecutter_data(chip_id, diecutter_info_res):
        current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
        diecutter_info_res.update(current_data)

    results = []
    for _ in range(n_stacks):
        frame = GetFrameFromCamera2.call(camera2_id=camera2_id)
        timestamp = time.time()
        card_errors_res = {}
        card_errors = threading.Thread(target=check_error, args=(camera2_id, frame, card_errors_res))
        diecutter_info_res = {}
        diecutter_info = threading.Thread(target=retrieve_diecutter_data, args=(chip_id, diecutter_info_res))
        card_errors.start()
        diecutter_info.start()
        card_errors.join()
        diecutter_info.join()
        if card_errors_res['has_error']:
            result_row = {
                'timestamp': time.strftime(""%Y-%m-%d %H:%M:%S"", time.gmtime(timestamp)),
                'session_id': session_id,
                'error_type': card_errors_res['error_type'],
                'speed': diecutter_info_res['speed'],
                'temperature': diecutter_info_res['temperature'],
                'rotations': diecutter_info_res['rotations']
            }
            results.append(result_row)

    return results
"
q0,6,Provide the serial numbers for cameras one and two from every diecutter in the plant.,"brief_description: Data service that, given the id of a camera1, provides a frame captured from that camera1. - detailed_description: Data service that, given the id of a camera1, provides a frame captured from that camera1.
        In general instances of camera1 point downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera1 (an integer) and returns a frame captured from that camera1 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera1 is 123, then the data service would be called as follows:
        camera1_id = 123
        frame = GetFrameFromCamera1.call(camera1_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int'] - output_values: ['frame:np.matrix'] - module: camera1 - class_name: GetFrameFromCamera1brief_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors and provide the type of error. - detailed_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors.
        Recall that a camera1 is a camera device that points downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera1 to use and the frame captured from that camera1.
        It returns a boolean value, True if the frame contains a cardboard with errors, False otherwise.
        Also it returns a integer value, 0 if the frame does not contain errors, 1 if the errors are of type hole and 2 if the errors are of type fold. 

        Example usage:
        - If frame is a variable containing the frame captured from the camera1 with id 123, then the data service would be called as follows:
        camera1_id = 123
        contains_errors, type_errors = DetectErrorsInCardboardUsingCamera1.call(camera1_id=123, frame=frame)

        Things to keep in mind:
        - The output is a tuple of boolean and integer, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool', 'error_type:int'] - module: camera1 - class_name: DetectErrorsInCardboardUsingCamera1brief_description: Data service that, given the id of a camera2, provides a frame captured from that camera2. - detailed_description: Data service that, given the id of a camera2, provides a frame captured from that camera2.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera2 (an integer) and returns a frame captured from that camera2 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera2 is 123, then the data service would be called as follows:
        camera2_id = 123
        frame = GetFrameFromCamera2.call(camera2_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int'] - output_values: ['frame:np.matrix'] - module: camera2 - class_name: GetFrameFromCamera2brief_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors. - detailed_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera2 to use and the frame captured from that camera2 that contains a stack of cardboards.
        It returns a boolean value, True if the frame contains a stack of cardboards with errors, False otherwise.

        Example usage:
        - If frame is a variable containing the frame captured from the camera2 with id 123, then the data service would be called as follows:
        camera2_id = 123
        contains_errors, error_type = DetectErrorsInCardboardStack.call(camera2_id=123, frame=frame)

        Things to keep in mind:
        - The output value is a boolean, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool'] - module: camera2 - class_name: DetectErrorsInCardboardStackUsingCamera2brief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera1 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera1.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera1)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera1:int'] - module: database - class_name: GetSerialCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera2 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera2.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera2)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera2:int'] - module: database - class_name: GetSerialCamera2IdFromDiecutterIdbrief_description: Data service that provides the list of id of the diecutters installed in the factory. - detailed_description: Data service that provides the id of the diecutter installed in the factory.
        The data service relies on the management database of the cardboard factory to provide the list of diecutter id.
        The data service takes no parameter and returns a list of integers, which are the id of the diecutters installed in the factory.

        Example usage:
        - The data service would be called as follows:
        diecutters_id = GetDiecuttersIdOfFactory.call()
        # assuming the diecutters id are [1, 2, 3]
        print(diecutters_id)  # [1, 2, 3]

        Things to keep in mind:
        - The diecutters id is a list of integers, so avoid trying to access it as a dictionary. - input_parameters: [] - output_values: ['diecutters_id:list'] - module: database - class_name: GetDiecuttersIdOfFactorybrief_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter.
        The data service relies on the management database of the cardboard factory to provide the chip id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the chip id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=123)
        # assuming the chip id is 456
        print(chip_id)  # 456

        Things to keep in mind:
        - The chip id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['chip_id:int'] - module: database - class_name: GetDiecutterChipIdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera1 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera1 id is 456
        print(camera1_id)  # 456

        Things to keep in mind:
        - The camera1 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera1_id:int'] - module: database - class_name: GetCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera2 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera2 id is 456
        print(camera2_id)  # 456

        Things to keep in mind:
        - The camera2 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera2_id:int'] - module: database - class_name: GetCamera2IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter.
        The data service relies on the management database of the cardboard factory to provide the session id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the current session id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=123)
        # assuming the session id is 456
        print(session_id)  # 456

        Things to keep in mind:
        - The session id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['session_id:int'] - module: database - class_name: GetCurrentSessionIdFromDiecutterIdbrief_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip. - detailed_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip.
        In general each diecutter has exactly one chip embedded into it, and each chip is uniquely identified by an integer id. 
        This means that the chip id has a one-to-one correspondence with the id of the diecutter, but those two ids may not be the same.
        This data service takes a single parameter, namely the id of the chip (an integer) and returns a single dictionary containing the current speed, temperature and number of rotations of the diecutter it is attached to.
        The keys of the dictionary are ""speed"", ""temperature"" and ""rotations"". 
        
        Example usage:
        - If the id of the chip is 123, then the data service would be called as follows:
        chip_id = 123
        current_data = GetCurrentData.call(chip_id=123)
        # get the current speed, temperature and number of rotations
        current_speed = data[""speed""]
        current_temperature = data[""temperature""]
        current_rotations = data[""rotations""]
    
        Things to keep in mind:
        - The refresh rate of the data is 1 second, i.e. the data is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - Note that the values in the dictionary represents the current values of the speed, etc. of the diecutter, they are not aggregated values.
        - Remember that the output value is a dictionary with the above specified keys, so avoid trying to access it using keys not in the above example. - input_parameters: ['chip_id:int'] - output_values: ['diecutter_current_data:dict'] - module: diecutter - class_name: GetCurrentDataFromChip","from data_services.database import GetDiecuttersIdOfFactory
from data_services.database import GetSerialCamera1IdFromDiecutterId
from data_services.database import GetSerialCamera2IdFromDiecutterId
import threading

def pipeline_function():
    diecutters_id = GetDiecuttersIdOfFactory.call()
    
    def fetch_camera_serials(diecutter_id, results):
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=diecutter_id)
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)
        results.append({
            'diecutter_id': diecutter_id,
            'serial_camera1': serial_camera1,
            'serial_camera2': serial_camera2
        })
    
    results = []
    threads = []
    for diecutter_id in diecutters_id:
        thread = threading.Thread(target=fetch_camera_serials, args=(diecutter_id, results))
        threads.append(thread)
        thread.start()
    
    for thread in threads:
        thread.join()
    
    return results","+----+----------------+------------------+------------------+
|    |   diecutter_id |   serial_camera1 |   serial_camera2 |
|----+----------------+------------------+------------------|
|  0 |          60494 |           659422 |           228852 |
|  1 |          65125 |           452726 |           169015 |
|  2 |          15306 |           762265 |           217913 |
|  3 |          43936 |           120083 |           855200 |
|  4 |          77013 |           284217 |           681195 |
|  5 |          73691 |           622256 |           483483 |
+----+----------------+------------------+------------------+","[{'diecutter_id': 60494, 'serial_camera1': 659422, 'serial_camera2': 228852}, {'diecutter_id': 65125, 'serial_camera1': 452726, 'serial_camera2': 169015}, {'diecutter_id': 15306, 'serial_camera1': 762265, 'serial_camera2': 217913}, {'diecutter_id': 43936, 'serial_camera1': 120083, 'serial_camera2': 855200}, {'diecutter_id': 77013, 'serial_camera1': 284217, 'serial_camera2': 681195}, {'diecutter_id': 73691, 'serial_camera1': 622256, 'serial_camera2': 483483}]",Given 88888404 serial number tell me the type of camera and the diecutter it is installed on.,"from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.database import GetCamera2IdFromDiecutterId
from data_services.database import GetCurrentSessionIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
from data_services.camera2 import GetFrameFromCamera2
from data_services.camera2 import DetectErrorsInCardboardStackUsingCamera2
import threading
import time

def pipeline_function():
    diecutter_id = 14
    n_stacks = 30

    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=diecutter_id)
    camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)

    def check_error(camera2_id, frame, card_errors_res):
        has_error, error_type = DetectErrorsInCardboardStackUsingCamera2.call(camera2_id=camera2_id, frame=frame)
        card_errors_res['has_error'] = has_error
        card_errors_res['error_type'] = error_type
    
    def retrieve_diecutter_data(chip_id, diecutter_info_res):
        current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
        diecutter_info_res.update(current_data)

    results = []
    for _ in range(n_stacks):
        frame = GetFrameFromCamera2.call(camera2_id=camera2_id)
        timestamp = time.time()
        card_errors_res = {}
        card_errors = threading.Thread(target=check_error, args=(camera2_id, frame, card_errors_res))
        diecutter_info_res = {}
        diecutter_info = threading.Thread(target=retrieve_diecutter_data, args=(chip_id, diecutter_info_res))
        card_errors.start()
        diecutter_info.start()
        card_errors.join()
        diecutter_info.join()
        if card_errors_res['has_error']:
            result_row = {
                'timestamp': time.strftime(""%Y-%m-%d %H:%M:%S"", time.gmtime(timestamp)),
                'session_id': session_id,
                'error_type': card_errors_res['error_type'],
                'speed': diecutter_info_res['speed'],
                'temperature': diecutter_info_res['temperature'],
                'rotations': diecutter_info_res['rotations']
            }
            results.append(result_row)

    return results
"
q0,7,Retrieve the serial numbers for camera 1 and camera 2 from every diecutter within the plant.,"brief_description: Data service that, given the id of a camera1, provides a frame captured from that camera1. - detailed_description: Data service that, given the id of a camera1, provides a frame captured from that camera1.
        In general instances of camera1 point downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera1 (an integer) and returns a frame captured from that camera1 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera1 is 123, then the data service would be called as follows:
        camera1_id = 123
        frame = GetFrameFromCamera1.call(camera1_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int'] - output_values: ['frame:np.matrix'] - module: camera1 - class_name: GetFrameFromCamera1brief_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors and provide the type of error. - detailed_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors.
        Recall that a camera1 is a camera device that points downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera1 to use and the frame captured from that camera1.
        It returns a boolean value, True if the frame contains a cardboard with errors, False otherwise.
        Also it returns a integer value, 0 if the frame does not contain errors, 1 if the errors are of type hole and 2 if the errors are of type fold. 

        Example usage:
        - If frame is a variable containing the frame captured from the camera1 with id 123, then the data service would be called as follows:
        camera1_id = 123
        contains_errors, type_errors = DetectErrorsInCardboardUsingCamera1.call(camera1_id=123, frame=frame)

        Things to keep in mind:
        - The output is a tuple of boolean and integer, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool', 'error_type:int'] - module: camera1 - class_name: DetectErrorsInCardboardUsingCamera1brief_description: Data service that, given the id of a camera2, provides a frame captured from that camera2. - detailed_description: Data service that, given the id of a camera2, provides a frame captured from that camera2.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera2 (an integer) and returns a frame captured from that camera2 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera2 is 123, then the data service would be called as follows:
        camera2_id = 123
        frame = GetFrameFromCamera2.call(camera2_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int'] - output_values: ['frame:np.matrix'] - module: camera2 - class_name: GetFrameFromCamera2brief_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors. - detailed_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera2 to use and the frame captured from that camera2 that contains a stack of cardboards.
        It returns a boolean value, True if the frame contains a stack of cardboards with errors, False otherwise.

        Example usage:
        - If frame is a variable containing the frame captured from the camera2 with id 123, then the data service would be called as follows:
        camera2_id = 123
        contains_errors, error_type = DetectErrorsInCardboardStack.call(camera2_id=123, frame=frame)

        Things to keep in mind:
        - The output value is a boolean, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool'] - module: camera2 - class_name: DetectErrorsInCardboardStackUsingCamera2brief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera1 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera1.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera1)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera1:int'] - module: database - class_name: GetSerialCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera2 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera2.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera2)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera2:int'] - module: database - class_name: GetSerialCamera2IdFromDiecutterIdbrief_description: Data service that provides the list of id of the diecutters installed in the factory. - detailed_description: Data service that provides the id of the diecutter installed in the factory.
        The data service relies on the management database of the cardboard factory to provide the list of diecutter id.
        The data service takes no parameter and returns a list of integers, which are the id of the diecutters installed in the factory.

        Example usage:
        - The data service would be called as follows:
        diecutters_id = GetDiecuttersIdOfFactory.call()
        # assuming the diecutters id are [1, 2, 3]
        print(diecutters_id)  # [1, 2, 3]

        Things to keep in mind:
        - The diecutters id is a list of integers, so avoid trying to access it as a dictionary. - input_parameters: [] - output_values: ['diecutters_id:list'] - module: database - class_name: GetDiecuttersIdOfFactorybrief_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter.
        The data service relies on the management database of the cardboard factory to provide the chip id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the chip id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=123)
        # assuming the chip id is 456
        print(chip_id)  # 456

        Things to keep in mind:
        - The chip id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['chip_id:int'] - module: database - class_name: GetDiecutterChipIdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera1 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera1 id is 456
        print(camera1_id)  # 456

        Things to keep in mind:
        - The camera1 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera1_id:int'] - module: database - class_name: GetCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera2 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera2 id is 456
        print(camera2_id)  # 456

        Things to keep in mind:
        - The camera2 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera2_id:int'] - module: database - class_name: GetCamera2IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter.
        The data service relies on the management database of the cardboard factory to provide the session id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the current session id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=123)
        # assuming the session id is 456
        print(session_id)  # 456

        Things to keep in mind:
        - The session id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['session_id:int'] - module: database - class_name: GetCurrentSessionIdFromDiecutterIdbrief_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip. - detailed_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip.
        In general each diecutter has exactly one chip embedded into it, and each chip is uniquely identified by an integer id. 
        This means that the chip id has a one-to-one correspondence with the id of the diecutter, but those two ids may not be the same.
        This data service takes a single parameter, namely the id of the chip (an integer) and returns a single dictionary containing the current speed, temperature and number of rotations of the diecutter it is attached to.
        The keys of the dictionary are ""speed"", ""temperature"" and ""rotations"". 
        
        Example usage:
        - If the id of the chip is 123, then the data service would be called as follows:
        chip_id = 123
        current_data = GetCurrentData.call(chip_id=123)
        # get the current speed, temperature and number of rotations
        current_speed = data[""speed""]
        current_temperature = data[""temperature""]
        current_rotations = data[""rotations""]
    
        Things to keep in mind:
        - The refresh rate of the data is 1 second, i.e. the data is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - Note that the values in the dictionary represents the current values of the speed, etc. of the diecutter, they are not aggregated values.
        - Remember that the output value is a dictionary with the above specified keys, so avoid trying to access it using keys not in the above example. - input_parameters: ['chip_id:int'] - output_values: ['diecutter_current_data:dict'] - module: diecutter - class_name: GetCurrentDataFromChip","from data_services.database import GetDiecuttersIdOfFactory
from data_services.database import GetSerialCamera1IdFromDiecutterId
from data_services.database import GetSerialCamera2IdFromDiecutterId
import threading

def pipeline_function():
    diecutters_id = GetDiecuttersIdOfFactory.call()
    results = []
    
    def fetch_camera_serials(diecutter_id, results):
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=diecutter_id)
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)
        results.append({
            'diecutter_id': diecutter_id,
            'serial_camera1': serial_camera1,
            'serial_camera2': serial_camera2
        })
    
    threads = []
    for diecutter_id in diecutters_id:
        thread = threading.Thread(target=fetch_camera_serials, args=(diecutter_id, results))
        threads.append(thread)
        thread.start()
    
    for thread in threads:
        thread.join()
    
    return results","+----+----------------+------------------+------------------+
|    |   diecutter_id |   serial_camera1 |   serial_camera2 |
|----+----------------+------------------+------------------|
|  0 |          60494 |           659422 |           228852 |
|  1 |          65125 |           452726 |           169015 |
|  2 |          15306 |           762265 |           217913 |
|  3 |          43936 |           120083 |           855200 |
|  4 |          77013 |           284217 |           681195 |
|  5 |          73691 |           622256 |           483483 |
+----+----------------+------------------+------------------+","[{'diecutter_id': 60494, 'serial_camera1': 659422, 'serial_camera2': 228852}, {'diecutter_id': 65125, 'serial_camera1': 452726, 'serial_camera2': 169015}, {'diecutter_id': 15306, 'serial_camera1': 762265, 'serial_camera2': 217913}, {'diecutter_id': 43936, 'serial_camera1': 120083, 'serial_camera2': 855200}, {'diecutter_id': 77013, 'serial_camera1': 284217, 'serial_camera2': 681195}, {'diecutter_id': 73691, 'serial_camera1': 622256, 'serial_camera2': 483483}]",Given 88888404 serial number tell me the type of camera and the diecutter it is installed on.,"from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.database import GetCamera2IdFromDiecutterId
from data_services.database import GetCurrentSessionIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
from data_services.camera2 import GetFrameFromCamera2
from data_services.camera2 import DetectErrorsInCardboardStackUsingCamera2
import threading
import time

def pipeline_function():
    diecutter_id = 14
    n_stacks = 30

    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=diecutter_id)
    camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)

    def check_error(camera2_id, frame, card_errors_res):
        has_error, error_type = DetectErrorsInCardboardStackUsingCamera2.call(camera2_id=camera2_id, frame=frame)
        card_errors_res['has_error'] = has_error
        card_errors_res['error_type'] = error_type
    
    def retrieve_diecutter_data(chip_id, diecutter_info_res):
        current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
        diecutter_info_res.update(current_data)

    results = []
    for _ in range(n_stacks):
        frame = GetFrameFromCamera2.call(camera2_id=camera2_id)
        timestamp = time.time()
        card_errors_res = {}
        card_errors = threading.Thread(target=check_error, args=(camera2_id, frame, card_errors_res))
        diecutter_info_res = {}
        diecutter_info = threading.Thread(target=retrieve_diecutter_data, args=(chip_id, diecutter_info_res))
        card_errors.start()
        diecutter_info.start()
        card_errors.join()
        diecutter_info.join()
        if card_errors_res['has_error']:
            result_row = {
                'timestamp': time.strftime(""%Y-%m-%d %H:%M:%S"", time.gmtime(timestamp)),
                'session_id': session_id,
                'error_type': card_errors_res['error_type'],
                'speed': diecutter_info_res['speed'],
                'temperature': diecutter_info_res['temperature'],
                'rotations': diecutter_info_res['rotations']
            }
            results.append(result_row)

    return results
"
q0,8,Provide the serial numbers for cameras 1 and 2 from each diecutter throughout the factory.,"brief_description: Data service that, given the id of a camera1, provides a frame captured from that camera1. - detailed_description: Data service that, given the id of a camera1, provides a frame captured from that camera1.
        In general instances of camera1 point downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera1 (an integer) and returns a frame captured from that camera1 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera1 is 123, then the data service would be called as follows:
        camera1_id = 123
        frame = GetFrameFromCamera1.call(camera1_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int'] - output_values: ['frame:np.matrix'] - module: camera1 - class_name: GetFrameFromCamera1brief_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors and provide the type of error. - detailed_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors.
        Recall that a camera1 is a camera device that points downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera1 to use and the frame captured from that camera1.
        It returns a boolean value, True if the frame contains a cardboard with errors, False otherwise.
        Also it returns a integer value, 0 if the frame does not contain errors, 1 if the errors are of type hole and 2 if the errors are of type fold. 

        Example usage:
        - If frame is a variable containing the frame captured from the camera1 with id 123, then the data service would be called as follows:
        camera1_id = 123
        contains_errors, type_errors = DetectErrorsInCardboardUsingCamera1.call(camera1_id=123, frame=frame)

        Things to keep in mind:
        - The output is a tuple of boolean and integer, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool', 'error_type:int'] - module: camera1 - class_name: DetectErrorsInCardboardUsingCamera1brief_description: Data service that, given the id of a camera2, provides a frame captured from that camera2. - detailed_description: Data service that, given the id of a camera2, provides a frame captured from that camera2.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera2 (an integer) and returns a frame captured from that camera2 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera2 is 123, then the data service would be called as follows:
        camera2_id = 123
        frame = GetFrameFromCamera2.call(camera2_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int'] - output_values: ['frame:np.matrix'] - module: camera2 - class_name: GetFrameFromCamera2brief_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors. - detailed_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera2 to use and the frame captured from that camera2 that contains a stack of cardboards.
        It returns a boolean value, True if the frame contains a stack of cardboards with errors, False otherwise.

        Example usage:
        - If frame is a variable containing the frame captured from the camera2 with id 123, then the data service would be called as follows:
        camera2_id = 123
        contains_errors, error_type = DetectErrorsInCardboardStack.call(camera2_id=123, frame=frame)

        Things to keep in mind:
        - The output value is a boolean, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool'] - module: camera2 - class_name: DetectErrorsInCardboardStackUsingCamera2brief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera1 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera1.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera1)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera1:int'] - module: database - class_name: GetSerialCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera2 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera2.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera2)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera2:int'] - module: database - class_name: GetSerialCamera2IdFromDiecutterIdbrief_description: Data service that provides the list of id of the diecutters installed in the factory. - detailed_description: Data service that provides the id of the diecutter installed in the factory.
        The data service relies on the management database of the cardboard factory to provide the list of diecutter id.
        The data service takes no parameter and returns a list of integers, which are the id of the diecutters installed in the factory.

        Example usage:
        - The data service would be called as follows:
        diecutters_id = GetDiecuttersIdOfFactory.call()
        # assuming the diecutters id are [1, 2, 3]
        print(diecutters_id)  # [1, 2, 3]

        Things to keep in mind:
        - The diecutters id is a list of integers, so avoid trying to access it as a dictionary. - input_parameters: [] - output_values: ['diecutters_id:list'] - module: database - class_name: GetDiecuttersIdOfFactorybrief_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter.
        The data service relies on the management database of the cardboard factory to provide the chip id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the chip id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=123)
        # assuming the chip id is 456
        print(chip_id)  # 456

        Things to keep in mind:
        - The chip id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['chip_id:int'] - module: database - class_name: GetDiecutterChipIdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera1 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera1 id is 456
        print(camera1_id)  # 456

        Things to keep in mind:
        - The camera1 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera1_id:int'] - module: database - class_name: GetCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera2 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera2 id is 456
        print(camera2_id)  # 456

        Things to keep in mind:
        - The camera2 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera2_id:int'] - module: database - class_name: GetCamera2IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter.
        The data service relies on the management database of the cardboard factory to provide the session id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the current session id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=123)
        # assuming the session id is 456
        print(session_id)  # 456

        Things to keep in mind:
        - The session id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['session_id:int'] - module: database - class_name: GetCurrentSessionIdFromDiecutterIdbrief_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip. - detailed_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip.
        In general each diecutter has exactly one chip embedded into it, and each chip is uniquely identified by an integer id. 
        This means that the chip id has a one-to-one correspondence with the id of the diecutter, but those two ids may not be the same.
        This data service takes a single parameter, namely the id of the chip (an integer) and returns a single dictionary containing the current speed, temperature and number of rotations of the diecutter it is attached to.
        The keys of the dictionary are ""speed"", ""temperature"" and ""rotations"". 
        
        Example usage:
        - If the id of the chip is 123, then the data service would be called as follows:
        chip_id = 123
        current_data = GetCurrentData.call(chip_id=123)
        # get the current speed, temperature and number of rotations
        current_speed = data[""speed""]
        current_temperature = data[""temperature""]
        current_rotations = data[""rotations""]
    
        Things to keep in mind:
        - The refresh rate of the data is 1 second, i.e. the data is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - Note that the values in the dictionary represents the current values of the speed, etc. of the diecutter, they are not aggregated values.
        - Remember that the output value is a dictionary with the above specified keys, so avoid trying to access it using keys not in the above example. - input_parameters: ['chip_id:int'] - output_values: ['diecutter_current_data:dict'] - module: diecutter - class_name: GetCurrentDataFromChip","from data_services.database import GetDiecuttersIdOfFactory
from data_services.database import GetSerialCamera1IdFromDiecutterId
from data_services.database import GetSerialCamera2IdFromDiecutterId

def pipeline_function():
    diecutters_id = GetDiecuttersIdOfFactory.call()
    results = []
    
    for diecutter_id in diecutters_id:
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=diecutter_id)
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)
        results.append({
            'diecutter_id': diecutter_id,
            'serial_camera1': serial_camera1,
            'serial_camera2': serial_camera2
        })
    
    return results","+----+----------------+------------------+------------------+
|    |   diecutter_id |   serial_camera1 |   serial_camera2 |
|----+----------------+------------------+------------------|
|  0 |          60494 |           659422 |           228852 |
|  1 |          65125 |           452726 |           169015 |
|  2 |          15306 |           762265 |           217913 |
|  3 |          43936 |           120083 |           855200 |
|  4 |          77013 |           284217 |           681195 |
|  5 |          73691 |           622256 |           483483 |
+----+----------------+------------------+------------------+","[{'diecutter_id': 60494, 'serial_camera1': 659422, 'serial_camera2': 228852}, {'diecutter_id': 65125, 'serial_camera1': 452726, 'serial_camera2': 169015}, {'diecutter_id': 15306, 'serial_camera1': 762265, 'serial_camera2': 217913}, {'diecutter_id': 43936, 'serial_camera1': 120083, 'serial_camera2': 855200}, {'diecutter_id': 77013, 'serial_camera1': 284217, 'serial_camera2': 681195}, {'diecutter_id': 73691, 'serial_camera1': 622256, 'serial_camera2': 483483}]",Given 88888404 serial number tell me the type of camera and the diecutter it is installed on.,"from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.database import GetCamera2IdFromDiecutterId
from data_services.database import GetCurrentSessionIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
from data_services.camera2 import GetFrameFromCamera2
from data_services.camera2 import DetectErrorsInCardboardStackUsingCamera2
import threading
import time

def pipeline_function():
    diecutter_id = 14
    n_stacks = 30

    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=diecutter_id)
    camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)

    def check_error(camera2_id, frame, card_errors_res):
        has_error, error_type = DetectErrorsInCardboardStackUsingCamera2.call(camera2_id=camera2_id, frame=frame)
        card_errors_res['has_error'] = has_error
        card_errors_res['error_type'] = error_type
    
    def retrieve_diecutter_data(chip_id, diecutter_info_res):
        current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
        diecutter_info_res.update(current_data)

    results = []
    for _ in range(n_stacks):
        frame = GetFrameFromCamera2.call(camera2_id=camera2_id)
        timestamp = time.time()
        card_errors_res = {}
        card_errors = threading.Thread(target=check_error, args=(camera2_id, frame, card_errors_res))
        diecutter_info_res = {}
        diecutter_info = threading.Thread(target=retrieve_diecutter_data, args=(chip_id, diecutter_info_res))
        card_errors.start()
        diecutter_info.start()
        card_errors.join()
        diecutter_info.join()
        if card_errors_res['has_error']:
            result_row = {
                'timestamp': time.strftime(""%Y-%m-%d %H:%M:%S"", time.gmtime(timestamp)),
                'session_id': session_id,
                'error_type': card_errors_res['error_type'],
                'speed': diecutter_info_res['speed'],
                'temperature': diecutter_info_res['temperature'],
                'rotations': diecutter_info_res['rotations']
            }
            results.append(result_row)

    return results
"
q0,9,Provide the serial numbers for cameras 1 and 2 from every diecutter in the plant.,"brief_description: Data service that, given the id of a camera1, provides a frame captured from that camera1. - detailed_description: Data service that, given the id of a camera1, provides a frame captured from that camera1.
        In general instances of camera1 point downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera1 (an integer) and returns a frame captured from that camera1 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera1 is 123, then the data service would be called as follows:
        camera1_id = 123
        frame = GetFrameFromCamera1.call(camera1_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int'] - output_values: ['frame:np.matrix'] - module: camera1 - class_name: GetFrameFromCamera1brief_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors and provide the type of error. - detailed_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors.
        Recall that a camera1 is a camera device that points downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera1 to use and the frame captured from that camera1.
        It returns a boolean value, True if the frame contains a cardboard with errors, False otherwise.
        Also it returns a integer value, 0 if the frame does not contain errors, 1 if the errors are of type hole and 2 if the errors are of type fold. 

        Example usage:
        - If frame is a variable containing the frame captured from the camera1 with id 123, then the data service would be called as follows:
        camera1_id = 123
        contains_errors, type_errors = DetectErrorsInCardboardUsingCamera1.call(camera1_id=123, frame=frame)

        Things to keep in mind:
        - The output is a tuple of boolean and integer, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool', 'error_type:int'] - module: camera1 - class_name: DetectErrorsInCardboardUsingCamera1brief_description: Data service that, given the id of a camera2, provides a frame captured from that camera2. - detailed_description: Data service that, given the id of a camera2, provides a frame captured from that camera2.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera2 (an integer) and returns a frame captured from that camera2 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera2 is 123, then the data service would be called as follows:
        camera2_id = 123
        frame = GetFrameFromCamera2.call(camera2_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int'] - output_values: ['frame:np.matrix'] - module: camera2 - class_name: GetFrameFromCamera2brief_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors. - detailed_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera2 to use and the frame captured from that camera2 that contains a stack of cardboards.
        It returns a boolean value, True if the frame contains a stack of cardboards with errors, False otherwise.

        Example usage:
        - If frame is a variable containing the frame captured from the camera2 with id 123, then the data service would be called as follows:
        camera2_id = 123
        contains_errors, error_type = DetectErrorsInCardboardStack.call(camera2_id=123, frame=frame)

        Things to keep in mind:
        - The output value is a boolean, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool'] - module: camera2 - class_name: DetectErrorsInCardboardStackUsingCamera2brief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera1 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera1.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera1)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera1:int'] - module: database - class_name: GetSerialCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera2 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera2.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera2)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera2:int'] - module: database - class_name: GetSerialCamera2IdFromDiecutterIdbrief_description: Data service that provides the list of id of the diecutters installed in the factory. - detailed_description: Data service that provides the id of the diecutter installed in the factory.
        The data service relies on the management database of the cardboard factory to provide the list of diecutter id.
        The data service takes no parameter and returns a list of integers, which are the id of the diecutters installed in the factory.

        Example usage:
        - The data service would be called as follows:
        diecutters_id = GetDiecuttersIdOfFactory.call()
        # assuming the diecutters id are [1, 2, 3]
        print(diecutters_id)  # [1, 2, 3]

        Things to keep in mind:
        - The diecutters id is a list of integers, so avoid trying to access it as a dictionary. - input_parameters: [] - output_values: ['diecutters_id:list'] - module: database - class_name: GetDiecuttersIdOfFactorybrief_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter.
        The data service relies on the management database of the cardboard factory to provide the chip id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the chip id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=123)
        # assuming the chip id is 456
        print(chip_id)  # 456

        Things to keep in mind:
        - The chip id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['chip_id:int'] - module: database - class_name: GetDiecutterChipIdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera1 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera1 id is 456
        print(camera1_id)  # 456

        Things to keep in mind:
        - The camera1 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera1_id:int'] - module: database - class_name: GetCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera2 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera2 id is 456
        print(camera2_id)  # 456

        Things to keep in mind:
        - The camera2 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera2_id:int'] - module: database - class_name: GetCamera2IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter.
        The data service relies on the management database of the cardboard factory to provide the session id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the current session id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=123)
        # assuming the session id is 456
        print(session_id)  # 456

        Things to keep in mind:
        - The session id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['session_id:int'] - module: database - class_name: GetCurrentSessionIdFromDiecutterIdbrief_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip. - detailed_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip.
        In general each diecutter has exactly one chip embedded into it, and each chip is uniquely identified by an integer id. 
        This means that the chip id has a one-to-one correspondence with the id of the diecutter, but those two ids may not be the same.
        This data service takes a single parameter, namely the id of the chip (an integer) and returns a single dictionary containing the current speed, temperature and number of rotations of the diecutter it is attached to.
        The keys of the dictionary are ""speed"", ""temperature"" and ""rotations"". 
        
        Example usage:
        - If the id of the chip is 123, then the data service would be called as follows:
        chip_id = 123
        current_data = GetCurrentData.call(chip_id=123)
        # get the current speed, temperature and number of rotations
        current_speed = data[""speed""]
        current_temperature = data[""temperature""]
        current_rotations = data[""rotations""]
    
        Things to keep in mind:
        - The refresh rate of the data is 1 second, i.e. the data is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - Note that the values in the dictionary represents the current values of the speed, etc. of the diecutter, they are not aggregated values.
        - Remember that the output value is a dictionary with the above specified keys, so avoid trying to access it using keys not in the above example. - input_parameters: ['chip_id:int'] - output_values: ['diecutter_current_data:dict'] - module: diecutter - class_name: GetCurrentDataFromChip","from data_services.database import GetDiecuttersIdOfFactory
from data_services.database import GetSerialCamera1IdFromDiecutterId
from data_services.database import GetSerialCamera2IdFromDiecutterId

def pipeline_function():
    diecutters_id = GetDiecuttersIdOfFactory.call()
    results = []
    
    for diecutter_id in diecutters_id:
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=diecutter_id)
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)
        result = {
            'diecutter_id': diecutter_id,
            'serial_camera1': serial_camera1,
            'serial_camera2': serial_camera2
        }
        results.append(result)
    
    return results","+----+----------------+------------------+------------------+
|    |   diecutter_id |   serial_camera1 |   serial_camera2 |
|----+----------------+------------------+------------------|
|  0 |          60494 |           659422 |           228852 |
|  1 |          65125 |           452726 |           169015 |
|  2 |          15306 |           762265 |           217913 |
|  3 |          43936 |           120083 |           855200 |
|  4 |          77013 |           284217 |           681195 |
|  5 |          73691 |           622256 |           483483 |
+----+----------------+------------------+------------------+","[{'diecutter_id': 60494, 'serial_camera1': 659422, 'serial_camera2': 228852}, {'diecutter_id': 65125, 'serial_camera1': 452726, 'serial_camera2': 169015}, {'diecutter_id': 15306, 'serial_camera1': 762265, 'serial_camera2': 217913}, {'diecutter_id': 43936, 'serial_camera1': 120083, 'serial_camera2': 855200}, {'diecutter_id': 77013, 'serial_camera1': 284217, 'serial_camera2': 681195}, {'diecutter_id': 73691, 'serial_camera1': 622256, 'serial_camera2': 483483}]",Given 88888404 serial number tell me the type of camera and the diecutter it is installed on.,"from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.database import GetCamera2IdFromDiecutterId
from data_services.database import GetCurrentSessionIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
from data_services.camera2 import GetFrameFromCamera2
from data_services.camera2 import DetectErrorsInCardboardStackUsingCamera2
import threading
import time

def pipeline_function():
    diecutter_id = 14
    n_stacks = 30

    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=diecutter_id)
    camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)

    def check_error(camera2_id, frame, card_errors_res):
        has_error, error_type = DetectErrorsInCardboardStackUsingCamera2.call(camera2_id=camera2_id, frame=frame)
        card_errors_res['has_error'] = has_error
        card_errors_res['error_type'] = error_type
    
    def retrieve_diecutter_data(chip_id, diecutter_info_res):
        current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
        diecutter_info_res.update(current_data)

    results = []
    for _ in range(n_stacks):
        frame = GetFrameFromCamera2.call(camera2_id=camera2_id)
        timestamp = time.time()
        card_errors_res = {}
        card_errors = threading.Thread(target=check_error, args=(camera2_id, frame, card_errors_res))
        diecutter_info_res = {}
        diecutter_info = threading.Thread(target=retrieve_diecutter_data, args=(chip_id, diecutter_info_res))
        card_errors.start()
        diecutter_info.start()
        card_errors.join()
        diecutter_info.join()
        if card_errors_res['has_error']:
            result_row = {
                'timestamp': time.strftime(""%Y-%m-%d %H:%M:%S"", time.gmtime(timestamp)),
                'session_id': session_id,
                'error_type': card_errors_res['error_type'],
                'speed': diecutter_info_res['speed'],
                'temperature': diecutter_info_res['temperature'],
                'rotations': diecutter_info_res['rotations']
            }
            results.append(result_row)

    return results
"
q1,0,Generate a table containing the max speed of the diecutter with id 25 over a time span of 30 seconds.,"brief_description: Data service that, given the id of a camera1, provides a frame captured from that camera1. - detailed_description: Data service that, given the id of a camera1, provides a frame captured from that camera1.
        In general instances of camera1 point downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera1 (an integer) and returns a frame captured from that camera1 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera1 is 123, then the data service would be called as follows:
        camera1_id = 123
        frame = GetFrameFromCamera1.call(camera1_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int'] - output_values: ['frame:np.matrix'] - module: camera1 - class_name: GetFrameFromCamera1brief_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors and provide the type of error. - detailed_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors.
        Recall that a camera1 is a camera device that points downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera1 to use and the frame captured from that camera1.
        It returns a boolean value, True if the frame contains a cardboard with errors, False otherwise.
        Also it returns a integer value, 0 if the frame does not contain errors, 1 if the errors are of type hole and 2 if the errors are of type fold. 

        Example usage:
        - If frame is a variable containing the frame captured from the camera1 with id 123, then the data service would be called as follows:
        camera1_id = 123
        contains_errors, type_errors = DetectErrorsInCardboardUsingCamera1.call(camera1_id=123, frame=frame)

        Things to keep in mind:
        - The output is a tuple of boolean and integer, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool', 'error_type:int'] - module: camera1 - class_name: DetectErrorsInCardboardUsingCamera1brief_description: Data service that, given the id of a camera2, provides a frame captured from that camera2. - detailed_description: Data service that, given the id of a camera2, provides a frame captured from that camera2.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera2 (an integer) and returns a frame captured from that camera2 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera2 is 123, then the data service would be called as follows:
        camera2_id = 123
        frame = GetFrameFromCamera2.call(camera2_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int'] - output_values: ['frame:np.matrix'] - module: camera2 - class_name: GetFrameFromCamera2brief_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors. - detailed_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera2 to use and the frame captured from that camera2 that contains a stack of cardboards.
        It returns a boolean value, True if the frame contains a stack of cardboards with errors, False otherwise.

        Example usage:
        - If frame is a variable containing the frame captured from the camera2 with id 123, then the data service would be called as follows:
        camera2_id = 123
        contains_errors, error_type = DetectErrorsInCardboardStack.call(camera2_id=123, frame=frame)

        Things to keep in mind:
        - The output value is a boolean, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool'] - module: camera2 - class_name: DetectErrorsInCardboardStackUsingCamera2brief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera1 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera1.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera1)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera1:int'] - module: database - class_name: GetSerialCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera2 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera2.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera2)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera2:int'] - module: database - class_name: GetSerialCamera2IdFromDiecutterIdbrief_description: Data service that provides the list of id of the diecutters installed in the factory. - detailed_description: Data service that provides the id of the diecutter installed in the factory.
        The data service relies on the management database of the cardboard factory to provide the list of diecutter id.
        The data service takes no parameter and returns a list of integers, which are the id of the diecutters installed in the factory.

        Example usage:
        - The data service would be called as follows:
        diecutters_id = GetDiecuttersIdOfFactory.call()
        # assuming the diecutters id are [1, 2, 3]
        print(diecutters_id)  # [1, 2, 3]

        Things to keep in mind:
        - The diecutters id is a list of integers, so avoid trying to access it as a dictionary. - input_parameters: [] - output_values: ['diecutters_id:list'] - module: database - class_name: GetDiecuttersIdOfFactorybrief_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter.
        The data service relies on the management database of the cardboard factory to provide the chip id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the chip id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=123)
        # assuming the chip id is 456
        print(chip_id)  # 456

        Things to keep in mind:
        - The chip id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['chip_id:int'] - module: database - class_name: GetDiecutterChipIdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera1 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera1 id is 456
        print(camera1_id)  # 456

        Things to keep in mind:
        - The camera1 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera1_id:int'] - module: database - class_name: GetCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera2 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera2 id is 456
        print(camera2_id)  # 456

        Things to keep in mind:
        - The camera2 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera2_id:int'] - module: database - class_name: GetCamera2IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter.
        The data service relies on the management database of the cardboard factory to provide the session id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the current session id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=123)
        # assuming the session id is 456
        print(session_id)  # 456

        Things to keep in mind:
        - The session id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['session_id:int'] - module: database - class_name: GetCurrentSessionIdFromDiecutterIdbrief_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip. - detailed_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip.
        In general each diecutter has exactly one chip embedded into it, and each chip is uniquely identified by an integer id. 
        This means that the chip id has a one-to-one correspondence with the id of the diecutter, but those two ids may not be the same.
        This data service takes a single parameter, namely the id of the chip (an integer) and returns a single dictionary containing the current speed, temperature and number of rotations of the diecutter it is attached to.
        The keys of the dictionary are ""speed"", ""temperature"" and ""rotations"". 
        
        Example usage:
        - If the id of the chip is 123, then the data service would be called as follows:
        chip_id = 123
        current_data = GetCurrentData.call(chip_id=123)
        # get the current speed, temperature and number of rotations
        current_speed = data[""speed""]
        current_temperature = data[""temperature""]
        current_rotations = data[""rotations""]
    
        Things to keep in mind:
        - The refresh rate of the data is 1 second, i.e. the data is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - Note that the values in the dictionary represents the current values of the speed, etc. of the diecutter, they are not aggregated values.
        - Remember that the output value is a dictionary with the above specified keys, so avoid trying to access it using keys not in the above example. - input_parameters: ['chip_id:int'] - output_values: ['diecutter_current_data:dict'] - module: diecutter - class_name: GetCurrentDataFromChip","from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
import time

def pipeline_function():
    diecutter_id = 25
    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    
    max_speed = 0
    start_time = time.time()
    
    while time.time() - start_time < 30:
        current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
        current_speed = current_data[""speed""]
        if current_speed > max_speed:
            max_speed = current_speed
        time.sleep(1)  # Ensure we only collect data once per second
    
    result = [{'max_speed': max_speed}]
    return result","+----+-------------+
|    |   max_speed |
|----+-------------|
|  0 |           9 |
+----+-------------+",[{'max_speed': 9}],"Consider the diecutter with id 6, generate a table containing the average temperature computed over a time span of 1 minute.","from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.database import GetCamera2IdFromDiecutterId
from data_services.database import GetCurrentSessionIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
from data_services.camera2 import GetFrameFromCamera2
from data_services.camera2 import DetectErrorsInCardboardStackUsingCamera2
import threading
import time

def pipeline_function():
    diecutter_id = 14
    n_stacks = 30

    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=diecutter_id)
    camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)

    def check_error(camera2_id, frame, card_errors_res):
        has_error, error_type = DetectErrorsInCardboardStackUsingCamera2.call(camera2_id=camera2_id, frame=frame)
        card_errors_res['has_error'] = has_error
        card_errors_res['error_type'] = error_type
    
    def retrieve_diecutter_data(chip_id, diecutter_info_res):
        current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
        diecutter_info_res.update(current_data)

    results = []
    for _ in range(n_stacks):
        frame = GetFrameFromCamera2.call(camera2_id=camera2_id)
        timestamp = time.time()
        card_errors_res = {}
        card_errors = threading.Thread(target=check_error, args=(camera2_id, frame, card_errors_res))
        diecutter_info_res = {}
        diecutter_info = threading.Thread(target=retrieve_diecutter_data, args=(chip_id, diecutter_info_res))
        card_errors.start()
        diecutter_info.start()
        card_errors.join()
        diecutter_info.join()
        if card_errors_res['has_error']:
            result_row = {
                'timestamp': time.strftime(""%Y-%m-%d %H:%M:%S"", time.gmtime(timestamp)),
                'session_id': session_id,
                'error_type': card_errors_res['error_type'],
                'speed': diecutter_info_res['speed'],
                'temperature': diecutter_info_res['temperature'],
                'rotations': diecutter_info_res['rotations']
            }
            results.append(result_row)

    return results
"
q1,1,Construct a table displaying the highest speed of the diecutter identified by id 25 during a 30-second interval.,"brief_description: Data service that, given the id of a camera1, provides a frame captured from that camera1. - detailed_description: Data service that, given the id of a camera1, provides a frame captured from that camera1.
        In general instances of camera1 point downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera1 (an integer) and returns a frame captured from that camera1 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera1 is 123, then the data service would be called as follows:
        camera1_id = 123
        frame = GetFrameFromCamera1.call(camera1_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int'] - output_values: ['frame:np.matrix'] - module: camera1 - class_name: GetFrameFromCamera1brief_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors and provide the type of error. - detailed_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors.
        Recall that a camera1 is a camera device that points downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera1 to use and the frame captured from that camera1.
        It returns a boolean value, True if the frame contains a cardboard with errors, False otherwise.
        Also it returns a integer value, 0 if the frame does not contain errors, 1 if the errors are of type hole and 2 if the errors are of type fold. 

        Example usage:
        - If frame is a variable containing the frame captured from the camera1 with id 123, then the data service would be called as follows:
        camera1_id = 123
        contains_errors, type_errors = DetectErrorsInCardboardUsingCamera1.call(camera1_id=123, frame=frame)

        Things to keep in mind:
        - The output is a tuple of boolean and integer, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool', 'error_type:int'] - module: camera1 - class_name: DetectErrorsInCardboardUsingCamera1brief_description: Data service that, given the id of a camera2, provides a frame captured from that camera2. - detailed_description: Data service that, given the id of a camera2, provides a frame captured from that camera2.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera2 (an integer) and returns a frame captured from that camera2 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera2 is 123, then the data service would be called as follows:
        camera2_id = 123
        frame = GetFrameFromCamera2.call(camera2_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int'] - output_values: ['frame:np.matrix'] - module: camera2 - class_name: GetFrameFromCamera2brief_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors. - detailed_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera2 to use and the frame captured from that camera2 that contains a stack of cardboards.
        It returns a boolean value, True if the frame contains a stack of cardboards with errors, False otherwise.

        Example usage:
        - If frame is a variable containing the frame captured from the camera2 with id 123, then the data service would be called as follows:
        camera2_id = 123
        contains_errors, error_type = DetectErrorsInCardboardStack.call(camera2_id=123, frame=frame)

        Things to keep in mind:
        - The output value is a boolean, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool'] - module: camera2 - class_name: DetectErrorsInCardboardStackUsingCamera2brief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera1 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera1.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera1)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera1:int'] - module: database - class_name: GetSerialCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera2 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera2.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera2)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera2:int'] - module: database - class_name: GetSerialCamera2IdFromDiecutterIdbrief_description: Data service that provides the list of id of the diecutters installed in the factory. - detailed_description: Data service that provides the id of the diecutter installed in the factory.
        The data service relies on the management database of the cardboard factory to provide the list of diecutter id.
        The data service takes no parameter and returns a list of integers, which are the id of the diecutters installed in the factory.

        Example usage:
        - The data service would be called as follows:
        diecutters_id = GetDiecuttersIdOfFactory.call()
        # assuming the diecutters id are [1, 2, 3]
        print(diecutters_id)  # [1, 2, 3]

        Things to keep in mind:
        - The diecutters id is a list of integers, so avoid trying to access it as a dictionary. - input_parameters: [] - output_values: ['diecutters_id:list'] - module: database - class_name: GetDiecuttersIdOfFactorybrief_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter.
        The data service relies on the management database of the cardboard factory to provide the chip id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the chip id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=123)
        # assuming the chip id is 456
        print(chip_id)  # 456

        Things to keep in mind:
        - The chip id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['chip_id:int'] - module: database - class_name: GetDiecutterChipIdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera1 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera1 id is 456
        print(camera1_id)  # 456

        Things to keep in mind:
        - The camera1 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera1_id:int'] - module: database - class_name: GetCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera2 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera2 id is 456
        print(camera2_id)  # 456

        Things to keep in mind:
        - The camera2 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera2_id:int'] - module: database - class_name: GetCamera2IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter.
        The data service relies on the management database of the cardboard factory to provide the session id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the current session id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=123)
        # assuming the session id is 456
        print(session_id)  # 456

        Things to keep in mind:
        - The session id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['session_id:int'] - module: database - class_name: GetCurrentSessionIdFromDiecutterIdbrief_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip. - detailed_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip.
        In general each diecutter has exactly one chip embedded into it, and each chip is uniquely identified by an integer id. 
        This means that the chip id has a one-to-one correspondence with the id of the diecutter, but those two ids may not be the same.
        This data service takes a single parameter, namely the id of the chip (an integer) and returns a single dictionary containing the current speed, temperature and number of rotations of the diecutter it is attached to.
        The keys of the dictionary are ""speed"", ""temperature"" and ""rotations"". 
        
        Example usage:
        - If the id of the chip is 123, then the data service would be called as follows:
        chip_id = 123
        current_data = GetCurrentData.call(chip_id=123)
        # get the current speed, temperature and number of rotations
        current_speed = data[""speed""]
        current_temperature = data[""temperature""]
        current_rotations = data[""rotations""]
    
        Things to keep in mind:
        - The refresh rate of the data is 1 second, i.e. the data is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - Note that the values in the dictionary represents the current values of the speed, etc. of the diecutter, they are not aggregated values.
        - Remember that the output value is a dictionary with the above specified keys, so avoid trying to access it using keys not in the above example. - input_parameters: ['chip_id:int'] - output_values: ['diecutter_current_data:dict'] - module: diecutter - class_name: GetCurrentDataFromChip","from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
import threading
import time

def pipeline_function():
    diecutter_id = 25
    interval = 30  # seconds
    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    
    # Function to retrieve speed data from the chip
    def retrieve_speed_data(chip_id, speed_results):
        for _ in range(interval):
            current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
            speed_results.append(current_data['speed'])
            time.sleep(1)  # Wait for the next second to get fresh data

    speed_results = []
    speed_thread = threading.Thread(target=retrieve_speed_data, args=(chip_id, speed_results))
    speed_thread.start()
    speed_thread.join()

    # Find the highest speed during the interval
    highest_speed = max(speed_results) if speed_results else None

    result = [{'highest_speed': highest_speed}]
    return result","+----+-----------------+
|    |   highest_speed |
|----+-----------------|
|  0 |               9 |
+----+-----------------+",[{'highest_speed': 9}],"Consider the diecutter with id 6, generate a table containing the average temperature computed over a time span of 1 minute.","from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.database import GetCamera2IdFromDiecutterId
from data_services.database import GetCurrentSessionIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
from data_services.camera2 import GetFrameFromCamera2
from data_services.camera2 import DetectErrorsInCardboardStackUsingCamera2
import threading
import time

def pipeline_function():
    diecutter_id = 14
    n_stacks = 30

    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=diecutter_id)
    camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)

    def check_error(camera2_id, frame, card_errors_res):
        has_error, error_type = DetectErrorsInCardboardStackUsingCamera2.call(camera2_id=camera2_id, frame=frame)
        card_errors_res['has_error'] = has_error
        card_errors_res['error_type'] = error_type
    
    def retrieve_diecutter_data(chip_id, diecutter_info_res):
        current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
        diecutter_info_res.update(current_data)

    results = []
    for _ in range(n_stacks):
        frame = GetFrameFromCamera2.call(camera2_id=camera2_id)
        timestamp = time.time()
        card_errors_res = {}
        card_errors = threading.Thread(target=check_error, args=(camera2_id, frame, card_errors_res))
        diecutter_info_res = {}
        diecutter_info = threading.Thread(target=retrieve_diecutter_data, args=(chip_id, diecutter_info_res))
        card_errors.start()
        diecutter_info.start()
        card_errors.join()
        diecutter_info.join()
        if card_errors_res['has_error']:
            result_row = {
                'timestamp': time.strftime(""%Y-%m-%d %H:%M:%S"", time.gmtime(timestamp)),
                'session_id': session_id,
                'error_type': card_errors_res['error_type'],
                'speed': diecutter_info_res['speed'],
                'temperature': diecutter_info_res['temperature'],
                'rotations': diecutter_info_res['rotations']
            }
            results.append(result_row)

    return results
"
q1,2,Create a table showing the highest speed reached by the diecutter identified by ID 25 in a duration of 30 seconds.,"brief_description: Data service that, given the id of a camera1, provides a frame captured from that camera1. - detailed_description: Data service that, given the id of a camera1, provides a frame captured from that camera1.
        In general instances of camera1 point downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera1 (an integer) and returns a frame captured from that camera1 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera1 is 123, then the data service would be called as follows:
        camera1_id = 123
        frame = GetFrameFromCamera1.call(camera1_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int'] - output_values: ['frame:np.matrix'] - module: camera1 - class_name: GetFrameFromCamera1brief_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors and provide the type of error. - detailed_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors.
        Recall that a camera1 is a camera device that points downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera1 to use and the frame captured from that camera1.
        It returns a boolean value, True if the frame contains a cardboard with errors, False otherwise.
        Also it returns a integer value, 0 if the frame does not contain errors, 1 if the errors are of type hole and 2 if the errors are of type fold. 

        Example usage:
        - If frame is a variable containing the frame captured from the camera1 with id 123, then the data service would be called as follows:
        camera1_id = 123
        contains_errors, type_errors = DetectErrorsInCardboardUsingCamera1.call(camera1_id=123, frame=frame)

        Things to keep in mind:
        - The output is a tuple of boolean and integer, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool', 'error_type:int'] - module: camera1 - class_name: DetectErrorsInCardboardUsingCamera1brief_description: Data service that, given the id of a camera2, provides a frame captured from that camera2. - detailed_description: Data service that, given the id of a camera2, provides a frame captured from that camera2.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera2 (an integer) and returns a frame captured from that camera2 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera2 is 123, then the data service would be called as follows:
        camera2_id = 123
        frame = GetFrameFromCamera2.call(camera2_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int'] - output_values: ['frame:np.matrix'] - module: camera2 - class_name: GetFrameFromCamera2brief_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors. - detailed_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera2 to use and the frame captured from that camera2 that contains a stack of cardboards.
        It returns a boolean value, True if the frame contains a stack of cardboards with errors, False otherwise.

        Example usage:
        - If frame is a variable containing the frame captured from the camera2 with id 123, then the data service would be called as follows:
        camera2_id = 123
        contains_errors, error_type = DetectErrorsInCardboardStack.call(camera2_id=123, frame=frame)

        Things to keep in mind:
        - The output value is a boolean, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool'] - module: camera2 - class_name: DetectErrorsInCardboardStackUsingCamera2brief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera1 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera1.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera1)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera1:int'] - module: database - class_name: GetSerialCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera2 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera2.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera2)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera2:int'] - module: database - class_name: GetSerialCamera2IdFromDiecutterIdbrief_description: Data service that provides the list of id of the diecutters installed in the factory. - detailed_description: Data service that provides the id of the diecutter installed in the factory.
        The data service relies on the management database of the cardboard factory to provide the list of diecutter id.
        The data service takes no parameter and returns a list of integers, which are the id of the diecutters installed in the factory.

        Example usage:
        - The data service would be called as follows:
        diecutters_id = GetDiecuttersIdOfFactory.call()
        # assuming the diecutters id are [1, 2, 3]
        print(diecutters_id)  # [1, 2, 3]

        Things to keep in mind:
        - The diecutters id is a list of integers, so avoid trying to access it as a dictionary. - input_parameters: [] - output_values: ['diecutters_id:list'] - module: database - class_name: GetDiecuttersIdOfFactorybrief_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter.
        The data service relies on the management database of the cardboard factory to provide the chip id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the chip id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=123)
        # assuming the chip id is 456
        print(chip_id)  # 456

        Things to keep in mind:
        - The chip id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['chip_id:int'] - module: database - class_name: GetDiecutterChipIdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera1 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera1 id is 456
        print(camera1_id)  # 456

        Things to keep in mind:
        - The camera1 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera1_id:int'] - module: database - class_name: GetCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera2 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera2 id is 456
        print(camera2_id)  # 456

        Things to keep in mind:
        - The camera2 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera2_id:int'] - module: database - class_name: GetCamera2IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter.
        The data service relies on the management database of the cardboard factory to provide the session id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the current session id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=123)
        # assuming the session id is 456
        print(session_id)  # 456

        Things to keep in mind:
        - The session id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['session_id:int'] - module: database - class_name: GetCurrentSessionIdFromDiecutterIdbrief_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip. - detailed_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip.
        In general each diecutter has exactly one chip embedded into it, and each chip is uniquely identified by an integer id. 
        This means that the chip id has a one-to-one correspondence with the id of the diecutter, but those two ids may not be the same.
        This data service takes a single parameter, namely the id of the chip (an integer) and returns a single dictionary containing the current speed, temperature and number of rotations of the diecutter it is attached to.
        The keys of the dictionary are ""speed"", ""temperature"" and ""rotations"". 
        
        Example usage:
        - If the id of the chip is 123, then the data service would be called as follows:
        chip_id = 123
        current_data = GetCurrentData.call(chip_id=123)
        # get the current speed, temperature and number of rotations
        current_speed = data[""speed""]
        current_temperature = data[""temperature""]
        current_rotations = data[""rotations""]
    
        Things to keep in mind:
        - The refresh rate of the data is 1 second, i.e. the data is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - Note that the values in the dictionary represents the current values of the speed, etc. of the diecutter, they are not aggregated values.
        - Remember that the output value is a dictionary with the above specified keys, so avoid trying to access it using keys not in the above example. - input_parameters: ['chip_id:int'] - output_values: ['diecutter_current_data:dict'] - module: diecutter - class_name: GetCurrentDataFromChip","from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
import time

def pipeline_function():
    diecutter_id = 25
    duration = 30  # seconds
    highest_speed = 0

    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)

    start_time = time.time()
    while time.time() - start_time < duration:
        current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
        current_speed = current_data[""speed""]
        if current_speed > highest_speed:
            highest_speed = current_speed
        time.sleep(1)  # Wait for the next second to get updated data

    result = [{
        ""diecutter_id"": diecutter_id,
        ""highest_speed"": highest_speed
    }]

    return result","+----+----------------+-----------------+
|    |   diecutter_id |   highest_speed |
|----+----------------+-----------------|
|  0 |             25 |               9 |
+----+----------------+-----------------+","[{'diecutter_id': 25, 'highest_speed': 9}]","Consider the diecutter with id 6, generate a table containing the average temperature computed over a time span of 1 minute.","from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.database import GetCamera2IdFromDiecutterId
from data_services.database import GetCurrentSessionIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
from data_services.camera2 import GetFrameFromCamera2
from data_services.camera2 import DetectErrorsInCardboardStackUsingCamera2
import threading
import time

def pipeline_function():
    diecutter_id = 14
    n_stacks = 30

    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=diecutter_id)
    camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)

    def check_error(camera2_id, frame, card_errors_res):
        has_error, error_type = DetectErrorsInCardboardStackUsingCamera2.call(camera2_id=camera2_id, frame=frame)
        card_errors_res['has_error'] = has_error
        card_errors_res['error_type'] = error_type
    
    def retrieve_diecutter_data(chip_id, diecutter_info_res):
        current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
        diecutter_info_res.update(current_data)

    results = []
    for _ in range(n_stacks):
        frame = GetFrameFromCamera2.call(camera2_id=camera2_id)
        timestamp = time.time()
        card_errors_res = {}
        card_errors = threading.Thread(target=check_error, args=(camera2_id, frame, card_errors_res))
        diecutter_info_res = {}
        diecutter_info = threading.Thread(target=retrieve_diecutter_data, args=(chip_id, diecutter_info_res))
        card_errors.start()
        diecutter_info.start()
        card_errors.join()
        diecutter_info.join()
        if card_errors_res['has_error']:
            result_row = {
                'timestamp': time.strftime(""%Y-%m-%d %H:%M:%S"", time.gmtime(timestamp)),
                'session_id': session_id,
                'error_type': card_errors_res['error_type'],
                'speed': diecutter_info_res['speed'],
                'temperature': diecutter_info_res['temperature'],
                'rotations': diecutter_info_res['rotations']
            }
            results.append(result_row)

    return results
"
q1,3,Produce a table showing the maximum speed of the diecutter identified by id 25 within a 30-second interval.,"brief_description: Data service that, given the id of a camera1, provides a frame captured from that camera1. - detailed_description: Data service that, given the id of a camera1, provides a frame captured from that camera1.
        In general instances of camera1 point downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera1 (an integer) and returns a frame captured from that camera1 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera1 is 123, then the data service would be called as follows:
        camera1_id = 123
        frame = GetFrameFromCamera1.call(camera1_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int'] - output_values: ['frame:np.matrix'] - module: camera1 - class_name: GetFrameFromCamera1brief_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors and provide the type of error. - detailed_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors.
        Recall that a camera1 is a camera device that points downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera1 to use and the frame captured from that camera1.
        It returns a boolean value, True if the frame contains a cardboard with errors, False otherwise.
        Also it returns a integer value, 0 if the frame does not contain errors, 1 if the errors are of type hole and 2 if the errors are of type fold. 

        Example usage:
        - If frame is a variable containing the frame captured from the camera1 with id 123, then the data service would be called as follows:
        camera1_id = 123
        contains_errors, type_errors = DetectErrorsInCardboardUsingCamera1.call(camera1_id=123, frame=frame)

        Things to keep in mind:
        - The output is a tuple of boolean and integer, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool', 'error_type:int'] - module: camera1 - class_name: DetectErrorsInCardboardUsingCamera1brief_description: Data service that, given the id of a camera2, provides a frame captured from that camera2. - detailed_description: Data service that, given the id of a camera2, provides a frame captured from that camera2.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera2 (an integer) and returns a frame captured from that camera2 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera2 is 123, then the data service would be called as follows:
        camera2_id = 123
        frame = GetFrameFromCamera2.call(camera2_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int'] - output_values: ['frame:np.matrix'] - module: camera2 - class_name: GetFrameFromCamera2brief_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors. - detailed_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera2 to use and the frame captured from that camera2 that contains a stack of cardboards.
        It returns a boolean value, True if the frame contains a stack of cardboards with errors, False otherwise.

        Example usage:
        - If frame is a variable containing the frame captured from the camera2 with id 123, then the data service would be called as follows:
        camera2_id = 123
        contains_errors, error_type = DetectErrorsInCardboardStack.call(camera2_id=123, frame=frame)

        Things to keep in mind:
        - The output value is a boolean, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool'] - module: camera2 - class_name: DetectErrorsInCardboardStackUsingCamera2brief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera1 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera1.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera1)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera1:int'] - module: database - class_name: GetSerialCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera2 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera2.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera2)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera2:int'] - module: database - class_name: GetSerialCamera2IdFromDiecutterIdbrief_description: Data service that provides the list of id of the diecutters installed in the factory. - detailed_description: Data service that provides the id of the diecutter installed in the factory.
        The data service relies on the management database of the cardboard factory to provide the list of diecutter id.
        The data service takes no parameter and returns a list of integers, which are the id of the diecutters installed in the factory.

        Example usage:
        - The data service would be called as follows:
        diecutters_id = GetDiecuttersIdOfFactory.call()
        # assuming the diecutters id are [1, 2, 3]
        print(diecutters_id)  # [1, 2, 3]

        Things to keep in mind:
        - The diecutters id is a list of integers, so avoid trying to access it as a dictionary. - input_parameters: [] - output_values: ['diecutters_id:list'] - module: database - class_name: GetDiecuttersIdOfFactorybrief_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter.
        The data service relies on the management database of the cardboard factory to provide the chip id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the chip id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=123)
        # assuming the chip id is 456
        print(chip_id)  # 456

        Things to keep in mind:
        - The chip id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['chip_id:int'] - module: database - class_name: GetDiecutterChipIdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera1 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera1 id is 456
        print(camera1_id)  # 456

        Things to keep in mind:
        - The camera1 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera1_id:int'] - module: database - class_name: GetCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera2 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera2 id is 456
        print(camera2_id)  # 456

        Things to keep in mind:
        - The camera2 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera2_id:int'] - module: database - class_name: GetCamera2IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter.
        The data service relies on the management database of the cardboard factory to provide the session id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the current session id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=123)
        # assuming the session id is 456
        print(session_id)  # 456

        Things to keep in mind:
        - The session id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['session_id:int'] - module: database - class_name: GetCurrentSessionIdFromDiecutterIdbrief_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip. - detailed_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip.
        In general each diecutter has exactly one chip embedded into it, and each chip is uniquely identified by an integer id. 
        This means that the chip id has a one-to-one correspondence with the id of the diecutter, but those two ids may not be the same.
        This data service takes a single parameter, namely the id of the chip (an integer) and returns a single dictionary containing the current speed, temperature and number of rotations of the diecutter it is attached to.
        The keys of the dictionary are ""speed"", ""temperature"" and ""rotations"". 
        
        Example usage:
        - If the id of the chip is 123, then the data service would be called as follows:
        chip_id = 123
        current_data = GetCurrentData.call(chip_id=123)
        # get the current speed, temperature and number of rotations
        current_speed = data[""speed""]
        current_temperature = data[""temperature""]
        current_rotations = data[""rotations""]
    
        Things to keep in mind:
        - The refresh rate of the data is 1 second, i.e. the data is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - Note that the values in the dictionary represents the current values of the speed, etc. of the diecutter, they are not aggregated values.
        - Remember that the output value is a dictionary with the above specified keys, so avoid trying to access it using keys not in the above example. - input_parameters: ['chip_id:int'] - output_values: ['diecutter_current_data:dict'] - module: diecutter - class_name: GetCurrentDataFromChip","from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
import time

def pipeline_function():
    diecutter_id = 25
    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    
    max_speed = 0
    start_time = time.time()
    
    while time.time() - start_time < 30:
        current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
        current_speed = current_data[""speed""]
        if current_speed > max_speed:
            max_speed = current_speed
        time.sleep(1)  # Wait for the next second to get fresh data
    
    result = [{'max_speed': max_speed}]
    return result","+----+-------------+
|    |   max_speed |
|----+-------------|
|  0 |           9 |
+----+-------------+",[{'max_speed': 9}],"Consider the diecutter with id 6, generate a table containing the average temperature computed over a time span of 1 minute.","from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.database import GetCamera2IdFromDiecutterId
from data_services.database import GetCurrentSessionIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
from data_services.camera2 import GetFrameFromCamera2
from data_services.camera2 import DetectErrorsInCardboardStackUsingCamera2
import threading
import time

def pipeline_function():
    diecutter_id = 14
    n_stacks = 30

    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=diecutter_id)
    camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)

    def check_error(camera2_id, frame, card_errors_res):
        has_error, error_type = DetectErrorsInCardboardStackUsingCamera2.call(camera2_id=camera2_id, frame=frame)
        card_errors_res['has_error'] = has_error
        card_errors_res['error_type'] = error_type
    
    def retrieve_diecutter_data(chip_id, diecutter_info_res):
        current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
        diecutter_info_res.update(current_data)

    results = []
    for _ in range(n_stacks):
        frame = GetFrameFromCamera2.call(camera2_id=camera2_id)
        timestamp = time.time()
        card_errors_res = {}
        card_errors = threading.Thread(target=check_error, args=(camera2_id, frame, card_errors_res))
        diecutter_info_res = {}
        diecutter_info = threading.Thread(target=retrieve_diecutter_data, args=(chip_id, diecutter_info_res))
        card_errors.start()
        diecutter_info.start()
        card_errors.join()
        diecutter_info.join()
        if card_errors_res['has_error']:
            result_row = {
                'timestamp': time.strftime(""%Y-%m-%d %H:%M:%S"", time.gmtime(timestamp)),
                'session_id': session_id,
                'error_type': card_errors_res['error_type'],
                'speed': diecutter_info_res['speed'],
                'temperature': diecutter_info_res['temperature'],
                'rotations': diecutter_info_res['rotations']
            }
            results.append(result_row)

    return results
"
q1,4,Create a table showing the highest speed reached by the diecutter identified by id 25 within a 30-second interval.,"brief_description: Data service that, given the id of a camera1, provides a frame captured from that camera1. - detailed_description: Data service that, given the id of a camera1, provides a frame captured from that camera1.
        In general instances of camera1 point downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera1 (an integer) and returns a frame captured from that camera1 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera1 is 123, then the data service would be called as follows:
        camera1_id = 123
        frame = GetFrameFromCamera1.call(camera1_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int'] - output_values: ['frame:np.matrix'] - module: camera1 - class_name: GetFrameFromCamera1brief_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors and provide the type of error. - detailed_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors.
        Recall that a camera1 is a camera device that points downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera1 to use and the frame captured from that camera1.
        It returns a boolean value, True if the frame contains a cardboard with errors, False otherwise.
        Also it returns a integer value, 0 if the frame does not contain errors, 1 if the errors are of type hole and 2 if the errors are of type fold. 

        Example usage:
        - If frame is a variable containing the frame captured from the camera1 with id 123, then the data service would be called as follows:
        camera1_id = 123
        contains_errors, type_errors = DetectErrorsInCardboardUsingCamera1.call(camera1_id=123, frame=frame)

        Things to keep in mind:
        - The output is a tuple of boolean and integer, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool', 'error_type:int'] - module: camera1 - class_name: DetectErrorsInCardboardUsingCamera1brief_description: Data service that, given the id of a camera2, provides a frame captured from that camera2. - detailed_description: Data service that, given the id of a camera2, provides a frame captured from that camera2.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera2 (an integer) and returns a frame captured from that camera2 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera2 is 123, then the data service would be called as follows:
        camera2_id = 123
        frame = GetFrameFromCamera2.call(camera2_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int'] - output_values: ['frame:np.matrix'] - module: camera2 - class_name: GetFrameFromCamera2brief_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors. - detailed_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera2 to use and the frame captured from that camera2 that contains a stack of cardboards.
        It returns a boolean value, True if the frame contains a stack of cardboards with errors, False otherwise.

        Example usage:
        - If frame is a variable containing the frame captured from the camera2 with id 123, then the data service would be called as follows:
        camera2_id = 123
        contains_errors, error_type = DetectErrorsInCardboardStack.call(camera2_id=123, frame=frame)

        Things to keep in mind:
        - The output value is a boolean, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool'] - module: camera2 - class_name: DetectErrorsInCardboardStackUsingCamera2brief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera1 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera1.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera1)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera1:int'] - module: database - class_name: GetSerialCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera2 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera2.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera2)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera2:int'] - module: database - class_name: GetSerialCamera2IdFromDiecutterIdbrief_description: Data service that provides the list of id of the diecutters installed in the factory. - detailed_description: Data service that provides the id of the diecutter installed in the factory.
        The data service relies on the management database of the cardboard factory to provide the list of diecutter id.
        The data service takes no parameter and returns a list of integers, which are the id of the diecutters installed in the factory.

        Example usage:
        - The data service would be called as follows:
        diecutters_id = GetDiecuttersIdOfFactory.call()
        # assuming the diecutters id are [1, 2, 3]
        print(diecutters_id)  # [1, 2, 3]

        Things to keep in mind:
        - The diecutters id is a list of integers, so avoid trying to access it as a dictionary. - input_parameters: [] - output_values: ['diecutters_id:list'] - module: database - class_name: GetDiecuttersIdOfFactorybrief_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter.
        The data service relies on the management database of the cardboard factory to provide the chip id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the chip id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=123)
        # assuming the chip id is 456
        print(chip_id)  # 456

        Things to keep in mind:
        - The chip id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['chip_id:int'] - module: database - class_name: GetDiecutterChipIdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera1 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera1 id is 456
        print(camera1_id)  # 456

        Things to keep in mind:
        - The camera1 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera1_id:int'] - module: database - class_name: GetCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera2 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera2 id is 456
        print(camera2_id)  # 456

        Things to keep in mind:
        - The camera2 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera2_id:int'] - module: database - class_name: GetCamera2IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter.
        The data service relies on the management database of the cardboard factory to provide the session id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the current session id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=123)
        # assuming the session id is 456
        print(session_id)  # 456

        Things to keep in mind:
        - The session id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['session_id:int'] - module: database - class_name: GetCurrentSessionIdFromDiecutterIdbrief_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip. - detailed_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip.
        In general each diecutter has exactly one chip embedded into it, and each chip is uniquely identified by an integer id. 
        This means that the chip id has a one-to-one correspondence with the id of the diecutter, but those two ids may not be the same.
        This data service takes a single parameter, namely the id of the chip (an integer) and returns a single dictionary containing the current speed, temperature and number of rotations of the diecutter it is attached to.
        The keys of the dictionary are ""speed"", ""temperature"" and ""rotations"". 
        
        Example usage:
        - If the id of the chip is 123, then the data service would be called as follows:
        chip_id = 123
        current_data = GetCurrentData.call(chip_id=123)
        # get the current speed, temperature and number of rotations
        current_speed = data[""speed""]
        current_temperature = data[""temperature""]
        current_rotations = data[""rotations""]
    
        Things to keep in mind:
        - The refresh rate of the data is 1 second, i.e. the data is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - Note that the values in the dictionary represents the current values of the speed, etc. of the diecutter, they are not aggregated values.
        - Remember that the output value is a dictionary with the above specified keys, so avoid trying to access it using keys not in the above example. - input_parameters: ['chip_id:int'] - output_values: ['diecutter_current_data:dict'] - module: diecutter - class_name: GetCurrentDataFromChip","from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
import threading
import time

def pipeline_function():
    diecutter_id = 25
    duration = 30  # seconds
    highest_speed = 0

    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)

    def retrieve_speed(chip_id, speed_res):
        current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
        speed_res.append(current_data['speed'])

    speed_results = []
    threads = []
    start_time = time.time()

    while time.time() - start_time < duration:
        t = threading.Thread(target=retrieve_speed, args=(chip_id, speed_results))
        t.start()
        threads.append(t)
        time.sleep(1)  # Ensure data is fetched every second

    for t in threads:
        t.join()

    if speed_results:
        highest_speed = max(speed_results)

    result = [{'highest_speed': highest_speed}]
    return result","+----+-----------------+
|    |   highest_speed |
|----+-----------------|
|  0 |               9 |
+----+-----------------+",[{'highest_speed': 9}],"Consider the diecutter with id 6, generate a table containing the average temperature computed over a time span of 1 minute.","from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.database import GetCamera2IdFromDiecutterId
from data_services.database import GetCurrentSessionIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
from data_services.camera2 import GetFrameFromCamera2
from data_services.camera2 import DetectErrorsInCardboardStackUsingCamera2
import threading
import time

def pipeline_function():
    diecutter_id = 14
    n_stacks = 30

    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=diecutter_id)
    camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)

    def check_error(camera2_id, frame, card_errors_res):
        has_error, error_type = DetectErrorsInCardboardStackUsingCamera2.call(camera2_id=camera2_id, frame=frame)
        card_errors_res['has_error'] = has_error
        card_errors_res['error_type'] = error_type
    
    def retrieve_diecutter_data(chip_id, diecutter_info_res):
        current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
        diecutter_info_res.update(current_data)

    results = []
    for _ in range(n_stacks):
        frame = GetFrameFromCamera2.call(camera2_id=camera2_id)
        timestamp = time.time()
        card_errors_res = {}
        card_errors = threading.Thread(target=check_error, args=(camera2_id, frame, card_errors_res))
        diecutter_info_res = {}
        diecutter_info = threading.Thread(target=retrieve_diecutter_data, args=(chip_id, diecutter_info_res))
        card_errors.start()
        diecutter_info.start()
        card_errors.join()
        diecutter_info.join()
        if card_errors_res['has_error']:
            result_row = {
                'timestamp': time.strftime(""%Y-%m-%d %H:%M:%S"", time.gmtime(timestamp)),
                'session_id': session_id,
                'error_type': card_errors_res['error_type'],
                'speed': diecutter_info_res['speed'],
                'temperature': diecutter_info_res['temperature'],
                'rotations': diecutter_info_res['rotations']
            }
            results.append(result_row)

    return results
"
q1,5,Create a table that shows the maximum speed of the diecutter identified by id 25 during a 30-second interval.,"brief_description: Data service that, given the id of a camera1, provides a frame captured from that camera1. - detailed_description: Data service that, given the id of a camera1, provides a frame captured from that camera1.
        In general instances of camera1 point downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera1 (an integer) and returns a frame captured from that camera1 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera1 is 123, then the data service would be called as follows:
        camera1_id = 123
        frame = GetFrameFromCamera1.call(camera1_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int'] - output_values: ['frame:np.matrix'] - module: camera1 - class_name: GetFrameFromCamera1brief_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors and provide the type of error. - detailed_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors.
        Recall that a camera1 is a camera device that points downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera1 to use and the frame captured from that camera1.
        It returns a boolean value, True if the frame contains a cardboard with errors, False otherwise.
        Also it returns a integer value, 0 if the frame does not contain errors, 1 if the errors are of type hole and 2 if the errors are of type fold. 

        Example usage:
        - If frame is a variable containing the frame captured from the camera1 with id 123, then the data service would be called as follows:
        camera1_id = 123
        contains_errors, type_errors = DetectErrorsInCardboardUsingCamera1.call(camera1_id=123, frame=frame)

        Things to keep in mind:
        - The output is a tuple of boolean and integer, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool', 'error_type:int'] - module: camera1 - class_name: DetectErrorsInCardboardUsingCamera1brief_description: Data service that, given the id of a camera2, provides a frame captured from that camera2. - detailed_description: Data service that, given the id of a camera2, provides a frame captured from that camera2.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera2 (an integer) and returns a frame captured from that camera2 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera2 is 123, then the data service would be called as follows:
        camera2_id = 123
        frame = GetFrameFromCamera2.call(camera2_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int'] - output_values: ['frame:np.matrix'] - module: camera2 - class_name: GetFrameFromCamera2brief_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors. - detailed_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera2 to use and the frame captured from that camera2 that contains a stack of cardboards.
        It returns a boolean value, True if the frame contains a stack of cardboards with errors, False otherwise.

        Example usage:
        - If frame is a variable containing the frame captured from the camera2 with id 123, then the data service would be called as follows:
        camera2_id = 123
        contains_errors, error_type = DetectErrorsInCardboardStack.call(camera2_id=123, frame=frame)

        Things to keep in mind:
        - The output value is a boolean, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool'] - module: camera2 - class_name: DetectErrorsInCardboardStackUsingCamera2brief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera1 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera1.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera1)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera1:int'] - module: database - class_name: GetSerialCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera2 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera2.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera2)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera2:int'] - module: database - class_name: GetSerialCamera2IdFromDiecutterIdbrief_description: Data service that provides the list of id of the diecutters installed in the factory. - detailed_description: Data service that provides the id of the diecutter installed in the factory.
        The data service relies on the management database of the cardboard factory to provide the list of diecutter id.
        The data service takes no parameter and returns a list of integers, which are the id of the diecutters installed in the factory.

        Example usage:
        - The data service would be called as follows:
        diecutters_id = GetDiecuttersIdOfFactory.call()
        # assuming the diecutters id are [1, 2, 3]
        print(diecutters_id)  # [1, 2, 3]

        Things to keep in mind:
        - The diecutters id is a list of integers, so avoid trying to access it as a dictionary. - input_parameters: [] - output_values: ['diecutters_id:list'] - module: database - class_name: GetDiecuttersIdOfFactorybrief_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter.
        The data service relies on the management database of the cardboard factory to provide the chip id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the chip id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=123)
        # assuming the chip id is 456
        print(chip_id)  # 456

        Things to keep in mind:
        - The chip id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['chip_id:int'] - module: database - class_name: GetDiecutterChipIdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera1 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera1 id is 456
        print(camera1_id)  # 456

        Things to keep in mind:
        - The camera1 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera1_id:int'] - module: database - class_name: GetCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera2 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera2 id is 456
        print(camera2_id)  # 456

        Things to keep in mind:
        - The camera2 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera2_id:int'] - module: database - class_name: GetCamera2IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter.
        The data service relies on the management database of the cardboard factory to provide the session id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the current session id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=123)
        # assuming the session id is 456
        print(session_id)  # 456

        Things to keep in mind:
        - The session id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['session_id:int'] - module: database - class_name: GetCurrentSessionIdFromDiecutterIdbrief_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip. - detailed_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip.
        In general each diecutter has exactly one chip embedded into it, and each chip is uniquely identified by an integer id. 
        This means that the chip id has a one-to-one correspondence with the id of the diecutter, but those two ids may not be the same.
        This data service takes a single parameter, namely the id of the chip (an integer) and returns a single dictionary containing the current speed, temperature and number of rotations of the diecutter it is attached to.
        The keys of the dictionary are ""speed"", ""temperature"" and ""rotations"". 
        
        Example usage:
        - If the id of the chip is 123, then the data service would be called as follows:
        chip_id = 123
        current_data = GetCurrentData.call(chip_id=123)
        # get the current speed, temperature and number of rotations
        current_speed = data[""speed""]
        current_temperature = data[""temperature""]
        current_rotations = data[""rotations""]
    
        Things to keep in mind:
        - The refresh rate of the data is 1 second, i.e. the data is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - Note that the values in the dictionary represents the current values of the speed, etc. of the diecutter, they are not aggregated values.
        - Remember that the output value is a dictionary with the above specified keys, so avoid trying to access it using keys not in the above example. - input_parameters: ['chip_id:int'] - output_values: ['diecutter_current_data:dict'] - module: diecutter - class_name: GetCurrentDataFromChip","from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
import threading
import time

def pipeline_function():
    diecutter_id = 25
    interval = 30  # seconds
    max_speed = 0

    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)

    def retrieve_speed(chip_id, speed_results):
        current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
        speed_results.append(current_data['speed'])

    speed_results = []
    threads = []
    for _ in range(interval):
        t = threading.Thread(target=retrieve_speed, args=(chip_id, speed_results))
        t.start()
        threads.append(t)
        time.sleep(1)  # Ensure that data is collected every second

    for t in threads:
        t.join()

    max_speed = max(speed_results)

    result = [{'max_speed': max_speed}]
    return result","+----+-------------+
|    |   max_speed |
|----+-------------|
|  0 |           9 |
+----+-------------+",[{'max_speed': 9}],"Consider the diecutter with id 6, generate a table containing the average temperature computed over a time span of 1 minute.","from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.database import GetCamera2IdFromDiecutterId
from data_services.database import GetCurrentSessionIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
from data_services.camera2 import GetFrameFromCamera2
from data_services.camera2 import DetectErrorsInCardboardStackUsingCamera2
import threading
import time

def pipeline_function():
    diecutter_id = 14
    n_stacks = 30

    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=diecutter_id)
    camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)

    def check_error(camera2_id, frame, card_errors_res):
        has_error, error_type = DetectErrorsInCardboardStackUsingCamera2.call(camera2_id=camera2_id, frame=frame)
        card_errors_res['has_error'] = has_error
        card_errors_res['error_type'] = error_type
    
    def retrieve_diecutter_data(chip_id, diecutter_info_res):
        current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
        diecutter_info_res.update(current_data)

    results = []
    for _ in range(n_stacks):
        frame = GetFrameFromCamera2.call(camera2_id=camera2_id)
        timestamp = time.time()
        card_errors_res = {}
        card_errors = threading.Thread(target=check_error, args=(camera2_id, frame, card_errors_res))
        diecutter_info_res = {}
        diecutter_info = threading.Thread(target=retrieve_diecutter_data, args=(chip_id, diecutter_info_res))
        card_errors.start()
        diecutter_info.start()
        card_errors.join()
        diecutter_info.join()
        if card_errors_res['has_error']:
            result_row = {
                'timestamp': time.strftime(""%Y-%m-%d %H:%M:%S"", time.gmtime(timestamp)),
                'session_id': session_id,
                'error_type': card_errors_res['error_type'],
                'speed': diecutter_info_res['speed'],
                'temperature': diecutter_info_res['temperature'],
                'rotations': diecutter_info_res['rotations']
            }
            results.append(result_row)

    return results
"
q1,6,Create a table showing the maximum speed reached by the diecutter identified by id 25 during a period of 30 seconds.,"brief_description: Data service that, given the id of a camera1, provides a frame captured from that camera1. - detailed_description: Data service that, given the id of a camera1, provides a frame captured from that camera1.
        In general instances of camera1 point downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera1 (an integer) and returns a frame captured from that camera1 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera1 is 123, then the data service would be called as follows:
        camera1_id = 123
        frame = GetFrameFromCamera1.call(camera1_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int'] - output_values: ['frame:np.matrix'] - module: camera1 - class_name: GetFrameFromCamera1brief_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors and provide the type of error. - detailed_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors.
        Recall that a camera1 is a camera device that points downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera1 to use and the frame captured from that camera1.
        It returns a boolean value, True if the frame contains a cardboard with errors, False otherwise.
        Also it returns a integer value, 0 if the frame does not contain errors, 1 if the errors are of type hole and 2 if the errors are of type fold. 

        Example usage:
        - If frame is a variable containing the frame captured from the camera1 with id 123, then the data service would be called as follows:
        camera1_id = 123
        contains_errors, type_errors = DetectErrorsInCardboardUsingCamera1.call(camera1_id=123, frame=frame)

        Things to keep in mind:
        - The output is a tuple of boolean and integer, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool', 'error_type:int'] - module: camera1 - class_name: DetectErrorsInCardboardUsingCamera1brief_description: Data service that, given the id of a camera2, provides a frame captured from that camera2. - detailed_description: Data service that, given the id of a camera2, provides a frame captured from that camera2.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera2 (an integer) and returns a frame captured from that camera2 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera2 is 123, then the data service would be called as follows:
        camera2_id = 123
        frame = GetFrameFromCamera2.call(camera2_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int'] - output_values: ['frame:np.matrix'] - module: camera2 - class_name: GetFrameFromCamera2brief_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors. - detailed_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera2 to use and the frame captured from that camera2 that contains a stack of cardboards.
        It returns a boolean value, True if the frame contains a stack of cardboards with errors, False otherwise.

        Example usage:
        - If frame is a variable containing the frame captured from the camera2 with id 123, then the data service would be called as follows:
        camera2_id = 123
        contains_errors, error_type = DetectErrorsInCardboardStack.call(camera2_id=123, frame=frame)

        Things to keep in mind:
        - The output value is a boolean, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool'] - module: camera2 - class_name: DetectErrorsInCardboardStackUsingCamera2brief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera1 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera1.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera1)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera1:int'] - module: database - class_name: GetSerialCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera2 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera2.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera2)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera2:int'] - module: database - class_name: GetSerialCamera2IdFromDiecutterIdbrief_description: Data service that provides the list of id of the diecutters installed in the factory. - detailed_description: Data service that provides the id of the diecutter installed in the factory.
        The data service relies on the management database of the cardboard factory to provide the list of diecutter id.
        The data service takes no parameter and returns a list of integers, which are the id of the diecutters installed in the factory.

        Example usage:
        - The data service would be called as follows:
        diecutters_id = GetDiecuttersIdOfFactory.call()
        # assuming the diecutters id are [1, 2, 3]
        print(diecutters_id)  # [1, 2, 3]

        Things to keep in mind:
        - The diecutters id is a list of integers, so avoid trying to access it as a dictionary. - input_parameters: [] - output_values: ['diecutters_id:list'] - module: database - class_name: GetDiecuttersIdOfFactorybrief_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter.
        The data service relies on the management database of the cardboard factory to provide the chip id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the chip id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=123)
        # assuming the chip id is 456
        print(chip_id)  # 456

        Things to keep in mind:
        - The chip id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['chip_id:int'] - module: database - class_name: GetDiecutterChipIdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera1 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera1 id is 456
        print(camera1_id)  # 456

        Things to keep in mind:
        - The camera1 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera1_id:int'] - module: database - class_name: GetCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera2 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera2 id is 456
        print(camera2_id)  # 456

        Things to keep in mind:
        - The camera2 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera2_id:int'] - module: database - class_name: GetCamera2IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter.
        The data service relies on the management database of the cardboard factory to provide the session id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the current session id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=123)
        # assuming the session id is 456
        print(session_id)  # 456

        Things to keep in mind:
        - The session id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['session_id:int'] - module: database - class_name: GetCurrentSessionIdFromDiecutterIdbrief_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip. - detailed_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip.
        In general each diecutter has exactly one chip embedded into it, and each chip is uniquely identified by an integer id. 
        This means that the chip id has a one-to-one correspondence with the id of the diecutter, but those two ids may not be the same.
        This data service takes a single parameter, namely the id of the chip (an integer) and returns a single dictionary containing the current speed, temperature and number of rotations of the diecutter it is attached to.
        The keys of the dictionary are ""speed"", ""temperature"" and ""rotations"". 
        
        Example usage:
        - If the id of the chip is 123, then the data service would be called as follows:
        chip_id = 123
        current_data = GetCurrentData.call(chip_id=123)
        # get the current speed, temperature and number of rotations
        current_speed = data[""speed""]
        current_temperature = data[""temperature""]
        current_rotations = data[""rotations""]
    
        Things to keep in mind:
        - The refresh rate of the data is 1 second, i.e. the data is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - Note that the values in the dictionary represents the current values of the speed, etc. of the diecutter, they are not aggregated values.
        - Remember that the output value is a dictionary with the above specified keys, so avoid trying to access it using keys not in the above example. - input_parameters: ['chip_id:int'] - output_values: ['diecutter_current_data:dict'] - module: diecutter - class_name: GetCurrentDataFromChip","from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
import time

def pipeline_function():
    diecutter_id = 25
    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    
    max_speed = 0
    start_time = time.time()
    
    while time.time() - start_time < 30:
        current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
        current_speed = current_data[""speed""]
        if current_speed > max_speed:
            max_speed = current_speed
        time.sleep(1)  # Ensure we only check once per second

    result = [{'max_speed': max_speed}]
    return result","+----+-------------+
|    |   max_speed |
|----+-------------|
|  0 |           9 |
+----+-------------+",[{'max_speed': 9}],"Consider the diecutter with id 6, generate a table containing the average temperature computed over a time span of 1 minute.","from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.database import GetCamera2IdFromDiecutterId
from data_services.database import GetCurrentSessionIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
from data_services.camera2 import GetFrameFromCamera2
from data_services.camera2 import DetectErrorsInCardboardStackUsingCamera2
import threading
import time

def pipeline_function():
    diecutter_id = 14
    n_stacks = 30

    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=diecutter_id)
    camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)

    def check_error(camera2_id, frame, card_errors_res):
        has_error, error_type = DetectErrorsInCardboardStackUsingCamera2.call(camera2_id=camera2_id, frame=frame)
        card_errors_res['has_error'] = has_error
        card_errors_res['error_type'] = error_type
    
    def retrieve_diecutter_data(chip_id, diecutter_info_res):
        current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
        diecutter_info_res.update(current_data)

    results = []
    for _ in range(n_stacks):
        frame = GetFrameFromCamera2.call(camera2_id=camera2_id)
        timestamp = time.time()
        card_errors_res = {}
        card_errors = threading.Thread(target=check_error, args=(camera2_id, frame, card_errors_res))
        diecutter_info_res = {}
        diecutter_info = threading.Thread(target=retrieve_diecutter_data, args=(chip_id, diecutter_info_res))
        card_errors.start()
        diecutter_info.start()
        card_errors.join()
        diecutter_info.join()
        if card_errors_res['has_error']:
            result_row = {
                'timestamp': time.strftime(""%Y-%m-%d %H:%M:%S"", time.gmtime(timestamp)),
                'session_id': session_id,
                'error_type': card_errors_res['error_type'],
                'speed': diecutter_info_res['speed'],
                'temperature': diecutter_info_res['temperature'],
                'rotations': diecutter_info_res['rotations']
            }
            results.append(result_row)

    return results
"
q1,7,Create a table showing the highest speed of the diecutter identified by id 25 over a period of 30 seconds.,"brief_description: Data service that, given the id of a camera1, provides a frame captured from that camera1. - detailed_description: Data service that, given the id of a camera1, provides a frame captured from that camera1.
        In general instances of camera1 point downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera1 (an integer) and returns a frame captured from that camera1 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera1 is 123, then the data service would be called as follows:
        camera1_id = 123
        frame = GetFrameFromCamera1.call(camera1_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int'] - output_values: ['frame:np.matrix'] - module: camera1 - class_name: GetFrameFromCamera1brief_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors and provide the type of error. - detailed_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors.
        Recall that a camera1 is a camera device that points downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera1 to use and the frame captured from that camera1.
        It returns a boolean value, True if the frame contains a cardboard with errors, False otherwise.
        Also it returns a integer value, 0 if the frame does not contain errors, 1 if the errors are of type hole and 2 if the errors are of type fold. 

        Example usage:
        - If frame is a variable containing the frame captured from the camera1 with id 123, then the data service would be called as follows:
        camera1_id = 123
        contains_errors, type_errors = DetectErrorsInCardboardUsingCamera1.call(camera1_id=123, frame=frame)

        Things to keep in mind:
        - The output is a tuple of boolean and integer, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool', 'error_type:int'] - module: camera1 - class_name: DetectErrorsInCardboardUsingCamera1brief_description: Data service that, given the id of a camera2, provides a frame captured from that camera2. - detailed_description: Data service that, given the id of a camera2, provides a frame captured from that camera2.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera2 (an integer) and returns a frame captured from that camera2 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera2 is 123, then the data service would be called as follows:
        camera2_id = 123
        frame = GetFrameFromCamera2.call(camera2_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int'] - output_values: ['frame:np.matrix'] - module: camera2 - class_name: GetFrameFromCamera2brief_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors. - detailed_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera2 to use and the frame captured from that camera2 that contains a stack of cardboards.
        It returns a boolean value, True if the frame contains a stack of cardboards with errors, False otherwise.

        Example usage:
        - If frame is a variable containing the frame captured from the camera2 with id 123, then the data service would be called as follows:
        camera2_id = 123
        contains_errors, error_type = DetectErrorsInCardboardStack.call(camera2_id=123, frame=frame)

        Things to keep in mind:
        - The output value is a boolean, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool'] - module: camera2 - class_name: DetectErrorsInCardboardStackUsingCamera2brief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera1 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera1.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera1)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera1:int'] - module: database - class_name: GetSerialCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera2 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera2.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera2)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera2:int'] - module: database - class_name: GetSerialCamera2IdFromDiecutterIdbrief_description: Data service that provides the list of id of the diecutters installed in the factory. - detailed_description: Data service that provides the id of the diecutter installed in the factory.
        The data service relies on the management database of the cardboard factory to provide the list of diecutter id.
        The data service takes no parameter and returns a list of integers, which are the id of the diecutters installed in the factory.

        Example usage:
        - The data service would be called as follows:
        diecutters_id = GetDiecuttersIdOfFactory.call()
        # assuming the diecutters id are [1, 2, 3]
        print(diecutters_id)  # [1, 2, 3]

        Things to keep in mind:
        - The diecutters id is a list of integers, so avoid trying to access it as a dictionary. - input_parameters: [] - output_values: ['diecutters_id:list'] - module: database - class_name: GetDiecuttersIdOfFactorybrief_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter.
        The data service relies on the management database of the cardboard factory to provide the chip id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the chip id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=123)
        # assuming the chip id is 456
        print(chip_id)  # 456

        Things to keep in mind:
        - The chip id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['chip_id:int'] - module: database - class_name: GetDiecutterChipIdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera1 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera1 id is 456
        print(camera1_id)  # 456

        Things to keep in mind:
        - The camera1 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera1_id:int'] - module: database - class_name: GetCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera2 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera2 id is 456
        print(camera2_id)  # 456

        Things to keep in mind:
        - The camera2 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera2_id:int'] - module: database - class_name: GetCamera2IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter.
        The data service relies on the management database of the cardboard factory to provide the session id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the current session id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=123)
        # assuming the session id is 456
        print(session_id)  # 456

        Things to keep in mind:
        - The session id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['session_id:int'] - module: database - class_name: GetCurrentSessionIdFromDiecutterIdbrief_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip. - detailed_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip.
        In general each diecutter has exactly one chip embedded into it, and each chip is uniquely identified by an integer id. 
        This means that the chip id has a one-to-one correspondence with the id of the diecutter, but those two ids may not be the same.
        This data service takes a single parameter, namely the id of the chip (an integer) and returns a single dictionary containing the current speed, temperature and number of rotations of the diecutter it is attached to.
        The keys of the dictionary are ""speed"", ""temperature"" and ""rotations"". 
        
        Example usage:
        - If the id of the chip is 123, then the data service would be called as follows:
        chip_id = 123
        current_data = GetCurrentData.call(chip_id=123)
        # get the current speed, temperature and number of rotations
        current_speed = data[""speed""]
        current_temperature = data[""temperature""]
        current_rotations = data[""rotations""]
    
        Things to keep in mind:
        - The refresh rate of the data is 1 second, i.e. the data is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - Note that the values in the dictionary represents the current values of the speed, etc. of the diecutter, they are not aggregated values.
        - Remember that the output value is a dictionary with the above specified keys, so avoid trying to access it using keys not in the above example. - input_parameters: ['chip_id:int'] - output_values: ['diecutter_current_data:dict'] - module: diecutter - class_name: GetCurrentDataFromChip","from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
import threading
import time

def pipeline_function():
    diecutter_id = 25
    duration = 30  # seconds
    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    
    # Function to collect speed data over time
    def collect_speed_data(chip_id, speed_data):
        for _ in range(duration):
            current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
            speed_data.append(current_data['speed'])
            time.sleep(1)  # wait for a second to get the next data point

    speed_data = []
    speed_thread = threading.Thread(target=collect_speed_data, args=(chip_id, speed_data))
    speed_thread.start()
    speed_thread.join()

    # Find the highest speed
    highest_speed = max(speed_data) if speed_data else None

    result = [{'highest_speed': highest_speed}]
    return result","+----+-----------------+
|    |   highest_speed |
|----+-----------------|
|  0 |               9 |
+----+-----------------+",[{'highest_speed': 9}],"Consider the diecutter with id 6, generate a table containing the average temperature computed over a time span of 1 minute.","from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.database import GetCamera2IdFromDiecutterId
from data_services.database import GetCurrentSessionIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
from data_services.camera2 import GetFrameFromCamera2
from data_services.camera2 import DetectErrorsInCardboardStackUsingCamera2
import threading
import time

def pipeline_function():
    diecutter_id = 14
    n_stacks = 30

    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=diecutter_id)
    camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)

    def check_error(camera2_id, frame, card_errors_res):
        has_error, error_type = DetectErrorsInCardboardStackUsingCamera2.call(camera2_id=camera2_id, frame=frame)
        card_errors_res['has_error'] = has_error
        card_errors_res['error_type'] = error_type
    
    def retrieve_diecutter_data(chip_id, diecutter_info_res):
        current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
        diecutter_info_res.update(current_data)

    results = []
    for _ in range(n_stacks):
        frame = GetFrameFromCamera2.call(camera2_id=camera2_id)
        timestamp = time.time()
        card_errors_res = {}
        card_errors = threading.Thread(target=check_error, args=(camera2_id, frame, card_errors_res))
        diecutter_info_res = {}
        diecutter_info = threading.Thread(target=retrieve_diecutter_data, args=(chip_id, diecutter_info_res))
        card_errors.start()
        diecutter_info.start()
        card_errors.join()
        diecutter_info.join()
        if card_errors_res['has_error']:
            result_row = {
                'timestamp': time.strftime(""%Y-%m-%d %H:%M:%S"", time.gmtime(timestamp)),
                'session_id': session_id,
                'error_type': card_errors_res['error_type'],
                'speed': diecutter_info_res['speed'],
                'temperature': diecutter_info_res['temperature'],
                'rotations': diecutter_info_res['rotations']
            }
            results.append(result_row)

    return results
"
q1,8,Create a table displaying the highest speed of the diecutter identified by id 25 during a period of 30 seconds.,"brief_description: Data service that, given the id of a camera1, provides a frame captured from that camera1. - detailed_description: Data service that, given the id of a camera1, provides a frame captured from that camera1.
        In general instances of camera1 point downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera1 (an integer) and returns a frame captured from that camera1 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera1 is 123, then the data service would be called as follows:
        camera1_id = 123
        frame = GetFrameFromCamera1.call(camera1_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int'] - output_values: ['frame:np.matrix'] - module: camera1 - class_name: GetFrameFromCamera1brief_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors and provide the type of error. - detailed_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors.
        Recall that a camera1 is a camera device that points downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera1 to use and the frame captured from that camera1.
        It returns a boolean value, True if the frame contains a cardboard with errors, False otherwise.
        Also it returns a integer value, 0 if the frame does not contain errors, 1 if the errors are of type hole and 2 if the errors are of type fold. 

        Example usage:
        - If frame is a variable containing the frame captured from the camera1 with id 123, then the data service would be called as follows:
        camera1_id = 123
        contains_errors, type_errors = DetectErrorsInCardboardUsingCamera1.call(camera1_id=123, frame=frame)

        Things to keep in mind:
        - The output is a tuple of boolean and integer, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool', 'error_type:int'] - module: camera1 - class_name: DetectErrorsInCardboardUsingCamera1brief_description: Data service that, given the id of a camera2, provides a frame captured from that camera2. - detailed_description: Data service that, given the id of a camera2, provides a frame captured from that camera2.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera2 (an integer) and returns a frame captured from that camera2 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera2 is 123, then the data service would be called as follows:
        camera2_id = 123
        frame = GetFrameFromCamera2.call(camera2_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int'] - output_values: ['frame:np.matrix'] - module: camera2 - class_name: GetFrameFromCamera2brief_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors. - detailed_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera2 to use and the frame captured from that camera2 that contains a stack of cardboards.
        It returns a boolean value, True if the frame contains a stack of cardboards with errors, False otherwise.

        Example usage:
        - If frame is a variable containing the frame captured from the camera2 with id 123, then the data service would be called as follows:
        camera2_id = 123
        contains_errors, error_type = DetectErrorsInCardboardStack.call(camera2_id=123, frame=frame)

        Things to keep in mind:
        - The output value is a boolean, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool'] - module: camera2 - class_name: DetectErrorsInCardboardStackUsingCamera2brief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera1 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera1.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera1)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera1:int'] - module: database - class_name: GetSerialCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera2 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera2.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera2)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera2:int'] - module: database - class_name: GetSerialCamera2IdFromDiecutterIdbrief_description: Data service that provides the list of id of the diecutters installed in the factory. - detailed_description: Data service that provides the id of the diecutter installed in the factory.
        The data service relies on the management database of the cardboard factory to provide the list of diecutter id.
        The data service takes no parameter and returns a list of integers, which are the id of the diecutters installed in the factory.

        Example usage:
        - The data service would be called as follows:
        diecutters_id = GetDiecuttersIdOfFactory.call()
        # assuming the diecutters id are [1, 2, 3]
        print(diecutters_id)  # [1, 2, 3]

        Things to keep in mind:
        - The diecutters id is a list of integers, so avoid trying to access it as a dictionary. - input_parameters: [] - output_values: ['diecutters_id:list'] - module: database - class_name: GetDiecuttersIdOfFactorybrief_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter.
        The data service relies on the management database of the cardboard factory to provide the chip id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the chip id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=123)
        # assuming the chip id is 456
        print(chip_id)  # 456

        Things to keep in mind:
        - The chip id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['chip_id:int'] - module: database - class_name: GetDiecutterChipIdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera1 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera1 id is 456
        print(camera1_id)  # 456

        Things to keep in mind:
        - The camera1 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera1_id:int'] - module: database - class_name: GetCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera2 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera2 id is 456
        print(camera2_id)  # 456

        Things to keep in mind:
        - The camera2 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera2_id:int'] - module: database - class_name: GetCamera2IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter.
        The data service relies on the management database of the cardboard factory to provide the session id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the current session id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=123)
        # assuming the session id is 456
        print(session_id)  # 456

        Things to keep in mind:
        - The session id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['session_id:int'] - module: database - class_name: GetCurrentSessionIdFromDiecutterIdbrief_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip. - detailed_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip.
        In general each diecutter has exactly one chip embedded into it, and each chip is uniquely identified by an integer id. 
        This means that the chip id has a one-to-one correspondence with the id of the diecutter, but those two ids may not be the same.
        This data service takes a single parameter, namely the id of the chip (an integer) and returns a single dictionary containing the current speed, temperature and number of rotations of the diecutter it is attached to.
        The keys of the dictionary are ""speed"", ""temperature"" and ""rotations"". 
        
        Example usage:
        - If the id of the chip is 123, then the data service would be called as follows:
        chip_id = 123
        current_data = GetCurrentData.call(chip_id=123)
        # get the current speed, temperature and number of rotations
        current_speed = data[""speed""]
        current_temperature = data[""temperature""]
        current_rotations = data[""rotations""]
    
        Things to keep in mind:
        - The refresh rate of the data is 1 second, i.e. the data is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - Note that the values in the dictionary represents the current values of the speed, etc. of the diecutter, they are not aggregated values.
        - Remember that the output value is a dictionary with the above specified keys, so avoid trying to access it using keys not in the above example. - input_parameters: ['chip_id:int'] - output_values: ['diecutter_current_data:dict'] - module: diecutter - class_name: GetCurrentDataFromChip","from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
import time

def pipeline_function():
    diecutter_id = 25
    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    
    # Collect speed data over a period of 30 seconds
    speeds = []
    start_time = time.time()
    while time.time() - start_time < 30:
        current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
        speeds.append(current_data['speed'])
        time.sleep(1)  # Ensure we only collect data once per second

    # Find the highest speed
    highest_speed = max(speeds)
    
    # Return the result as a list of dictionaries
    result = [{'highest_speed': highest_speed}]
    return result","+----+-----------------+
|    |   highest_speed |
|----+-----------------|
|  0 |               9 |
+----+-----------------+",[{'highest_speed': 9}],"Consider the diecutter with id 6, generate a table containing the average temperature computed over a time span of 1 minute.","from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.database import GetCamera2IdFromDiecutterId
from data_services.database import GetCurrentSessionIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
from data_services.camera2 import GetFrameFromCamera2
from data_services.camera2 import DetectErrorsInCardboardStackUsingCamera2
import threading
import time

def pipeline_function():
    diecutter_id = 14
    n_stacks = 30

    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=diecutter_id)
    camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)

    def check_error(camera2_id, frame, card_errors_res):
        has_error, error_type = DetectErrorsInCardboardStackUsingCamera2.call(camera2_id=camera2_id, frame=frame)
        card_errors_res['has_error'] = has_error
        card_errors_res['error_type'] = error_type
    
    def retrieve_diecutter_data(chip_id, diecutter_info_res):
        current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
        diecutter_info_res.update(current_data)

    results = []
    for _ in range(n_stacks):
        frame = GetFrameFromCamera2.call(camera2_id=camera2_id)
        timestamp = time.time()
        card_errors_res = {}
        card_errors = threading.Thread(target=check_error, args=(camera2_id, frame, card_errors_res))
        diecutter_info_res = {}
        diecutter_info = threading.Thread(target=retrieve_diecutter_data, args=(chip_id, diecutter_info_res))
        card_errors.start()
        diecutter_info.start()
        card_errors.join()
        diecutter_info.join()
        if card_errors_res['has_error']:
            result_row = {
                'timestamp': time.strftime(""%Y-%m-%d %H:%M:%S"", time.gmtime(timestamp)),
                'session_id': session_id,
                'error_type': card_errors_res['error_type'],
                'speed': diecutter_info_res['speed'],
                'temperature': diecutter_info_res['temperature'],
                'rotations': diecutter_info_res['rotations']
            }
            results.append(result_row)

    return results
"
q1,9,Create a table showing the maximum speed for the diecutter identified by ID 25 over a duration of 30 seconds.,"brief_description: Data service that, given the id of a camera1, provides a frame captured from that camera1. - detailed_description: Data service that, given the id of a camera1, provides a frame captured from that camera1.
        In general instances of camera1 point downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera1 (an integer) and returns a frame captured from that camera1 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera1 is 123, then the data service would be called as follows:
        camera1_id = 123
        frame = GetFrameFromCamera1.call(camera1_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int'] - output_values: ['frame:np.matrix'] - module: camera1 - class_name: GetFrameFromCamera1brief_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors and provide the type of error. - detailed_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors.
        Recall that a camera1 is a camera device that points downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera1 to use and the frame captured from that camera1.
        It returns a boolean value, True if the frame contains a cardboard with errors, False otherwise.
        Also it returns a integer value, 0 if the frame does not contain errors, 1 if the errors are of type hole and 2 if the errors are of type fold. 

        Example usage:
        - If frame is a variable containing the frame captured from the camera1 with id 123, then the data service would be called as follows:
        camera1_id = 123
        contains_errors, type_errors = DetectErrorsInCardboardUsingCamera1.call(camera1_id=123, frame=frame)

        Things to keep in mind:
        - The output is a tuple of boolean and integer, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool', 'error_type:int'] - module: camera1 - class_name: DetectErrorsInCardboardUsingCamera1brief_description: Data service that, given the id of a camera2, provides a frame captured from that camera2. - detailed_description: Data service that, given the id of a camera2, provides a frame captured from that camera2.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera2 (an integer) and returns a frame captured from that camera2 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera2 is 123, then the data service would be called as follows:
        camera2_id = 123
        frame = GetFrameFromCamera2.call(camera2_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int'] - output_values: ['frame:np.matrix'] - module: camera2 - class_name: GetFrameFromCamera2brief_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors. - detailed_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera2 to use and the frame captured from that camera2 that contains a stack of cardboards.
        It returns a boolean value, True if the frame contains a stack of cardboards with errors, False otherwise.

        Example usage:
        - If frame is a variable containing the frame captured from the camera2 with id 123, then the data service would be called as follows:
        camera2_id = 123
        contains_errors, error_type = DetectErrorsInCardboardStack.call(camera2_id=123, frame=frame)

        Things to keep in mind:
        - The output value is a boolean, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool'] - module: camera2 - class_name: DetectErrorsInCardboardStackUsingCamera2brief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera1 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera1.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera1)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera1:int'] - module: database - class_name: GetSerialCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera2 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera2.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera2)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera2:int'] - module: database - class_name: GetSerialCamera2IdFromDiecutterIdbrief_description: Data service that provides the list of id of the diecutters installed in the factory. - detailed_description: Data service that provides the id of the diecutter installed in the factory.
        The data service relies on the management database of the cardboard factory to provide the list of diecutter id.
        The data service takes no parameter and returns a list of integers, which are the id of the diecutters installed in the factory.

        Example usage:
        - The data service would be called as follows:
        diecutters_id = GetDiecuttersIdOfFactory.call()
        # assuming the diecutters id are [1, 2, 3]
        print(diecutters_id)  # [1, 2, 3]

        Things to keep in mind:
        - The diecutters id is a list of integers, so avoid trying to access it as a dictionary. - input_parameters: [] - output_values: ['diecutters_id:list'] - module: database - class_name: GetDiecuttersIdOfFactorybrief_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter.
        The data service relies on the management database of the cardboard factory to provide the chip id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the chip id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=123)
        # assuming the chip id is 456
        print(chip_id)  # 456

        Things to keep in mind:
        - The chip id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['chip_id:int'] - module: database - class_name: GetDiecutterChipIdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera1 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera1 id is 456
        print(camera1_id)  # 456

        Things to keep in mind:
        - The camera1 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera1_id:int'] - module: database - class_name: GetCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera2 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera2 id is 456
        print(camera2_id)  # 456

        Things to keep in mind:
        - The camera2 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera2_id:int'] - module: database - class_name: GetCamera2IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter.
        The data service relies on the management database of the cardboard factory to provide the session id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the current session id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=123)
        # assuming the session id is 456
        print(session_id)  # 456

        Things to keep in mind:
        - The session id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['session_id:int'] - module: database - class_name: GetCurrentSessionIdFromDiecutterIdbrief_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip. - detailed_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip.
        In general each diecutter has exactly one chip embedded into it, and each chip is uniquely identified by an integer id. 
        This means that the chip id has a one-to-one correspondence with the id of the diecutter, but those two ids may not be the same.
        This data service takes a single parameter, namely the id of the chip (an integer) and returns a single dictionary containing the current speed, temperature and number of rotations of the diecutter it is attached to.
        The keys of the dictionary are ""speed"", ""temperature"" and ""rotations"". 
        
        Example usage:
        - If the id of the chip is 123, then the data service would be called as follows:
        chip_id = 123
        current_data = GetCurrentData.call(chip_id=123)
        # get the current speed, temperature and number of rotations
        current_speed = data[""speed""]
        current_temperature = data[""temperature""]
        current_rotations = data[""rotations""]
    
        Things to keep in mind:
        - The refresh rate of the data is 1 second, i.e. the data is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - Note that the values in the dictionary represents the current values of the speed, etc. of the diecutter, they are not aggregated values.
        - Remember that the output value is a dictionary with the above specified keys, so avoid trying to access it using keys not in the above example. - input_parameters: ['chip_id:int'] - output_values: ['diecutter_current_data:dict'] - module: diecutter - class_name: GetCurrentDataFromChip","from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
import time

def pipeline_function():
    diecutter_id = 25
    duration = 30  # seconds
    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    
    max_speed = 0
    start_time = time.time()
    
    while time.time() - start_time < duration:
        current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
        current_speed = current_data[""speed""]
        if current_speed > max_speed:
            max_speed = current_speed
        time.sleep(1)  # Wait for the next second to get updated data
    
    result = [{'max_speed': max_speed}]
    return result","+----+-------------+
|    |   max_speed |
|----+-------------|
|  0 |           9 |
+----+-------------+",[{'max_speed': 9}],"Consider the diecutter with id 6, generate a table containing the average temperature computed over a time span of 1 minute.","from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.database import GetCamera2IdFromDiecutterId
from data_services.database import GetCurrentSessionIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
from data_services.camera2 import GetFrameFromCamera2
from data_services.camera2 import DetectErrorsInCardboardStackUsingCamera2
import threading
import time

def pipeline_function():
    diecutter_id = 14
    n_stacks = 30

    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=diecutter_id)
    camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)

    def check_error(camera2_id, frame, card_errors_res):
        has_error, error_type = DetectErrorsInCardboardStackUsingCamera2.call(camera2_id=camera2_id, frame=frame)
        card_errors_res['has_error'] = has_error
        card_errors_res['error_type'] = error_type
    
    def retrieve_diecutter_data(chip_id, diecutter_info_res):
        current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
        diecutter_info_res.update(current_data)

    results = []
    for _ in range(n_stacks):
        frame = GetFrameFromCamera2.call(camera2_id=camera2_id)
        timestamp = time.time()
        card_errors_res = {}
        card_errors = threading.Thread(target=check_error, args=(camera2_id, frame, card_errors_res))
        diecutter_info_res = {}
        diecutter_info = threading.Thread(target=retrieve_diecutter_data, args=(chip_id, diecutter_info_res))
        card_errors.start()
        diecutter_info.start()
        card_errors.join()
        diecutter_info.join()
        if card_errors_res['has_error']:
            result_row = {
                'timestamp': time.strftime(""%Y-%m-%d %H:%M:%S"", time.gmtime(timestamp)),
                'session_id': session_id,
                'error_type': card_errors_res['error_type'],
                'speed': diecutter_info_res['speed'],
                'temperature': diecutter_info_res['temperature'],
                'rotations': diecutter_info_res['rotations']
            }
            results.append(result_row)

    return results
"
q2,0,"Generate a list of average speed values for the current session of the diecutter 7, where each average value is computed over 10 consecutive, non-overlapping time windows of 10 seconds.","brief_description: Data service that, given the id of a camera1, provides a frame captured from that camera1. - detailed_description: Data service that, given the id of a camera1, provides a frame captured from that camera1.
        In general instances of camera1 point downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera1 (an integer) and returns a frame captured from that camera1 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera1 is 123, then the data service would be called as follows:
        camera1_id = 123
        frame = GetFrameFromCamera1.call(camera1_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int'] - output_values: ['frame:np.matrix'] - module: camera1 - class_name: GetFrameFromCamera1brief_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors and provide the type of error. - detailed_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors.
        Recall that a camera1 is a camera device that points downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera1 to use and the frame captured from that camera1.
        It returns a boolean value, True if the frame contains a cardboard with errors, False otherwise.
        Also it returns a integer value, 0 if the frame does not contain errors, 1 if the errors are of type hole and 2 if the errors are of type fold. 

        Example usage:
        - If frame is a variable containing the frame captured from the camera1 with id 123, then the data service would be called as follows:
        camera1_id = 123
        contains_errors, type_errors = DetectErrorsInCardboardUsingCamera1.call(camera1_id=123, frame=frame)

        Things to keep in mind:
        - The output is a tuple of boolean and integer, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool', 'error_type:int'] - module: camera1 - class_name: DetectErrorsInCardboardUsingCamera1brief_description: Data service that, given the id of a camera2, provides a frame captured from that camera2. - detailed_description: Data service that, given the id of a camera2, provides a frame captured from that camera2.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera2 (an integer) and returns a frame captured from that camera2 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera2 is 123, then the data service would be called as follows:
        camera2_id = 123
        frame = GetFrameFromCamera2.call(camera2_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int'] - output_values: ['frame:np.matrix'] - module: camera2 - class_name: GetFrameFromCamera2brief_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors. - detailed_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera2 to use and the frame captured from that camera2 that contains a stack of cardboards.
        It returns a boolean value, True if the frame contains a stack of cardboards with errors, False otherwise.

        Example usage:
        - If frame is a variable containing the frame captured from the camera2 with id 123, then the data service would be called as follows:
        camera2_id = 123
        contains_errors, error_type = DetectErrorsInCardboardStack.call(camera2_id=123, frame=frame)

        Things to keep in mind:
        - The output value is a boolean, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool'] - module: camera2 - class_name: DetectErrorsInCardboardStackUsingCamera2brief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera1 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera1.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera1)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera1:int'] - module: database - class_name: GetSerialCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera2 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera2.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera2)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera2:int'] - module: database - class_name: GetSerialCamera2IdFromDiecutterIdbrief_description: Data service that provides the list of id of the diecutters installed in the factory. - detailed_description: Data service that provides the id of the diecutter installed in the factory.
        The data service relies on the management database of the cardboard factory to provide the list of diecutter id.
        The data service takes no parameter and returns a list of integers, which are the id of the diecutters installed in the factory.

        Example usage:
        - The data service would be called as follows:
        diecutters_id = GetDiecuttersIdOfFactory.call()
        # assuming the diecutters id are [1, 2, 3]
        print(diecutters_id)  # [1, 2, 3]

        Things to keep in mind:
        - The diecutters id is a list of integers, so avoid trying to access it as a dictionary. - input_parameters: [] - output_values: ['diecutters_id:list'] - module: database - class_name: GetDiecuttersIdOfFactorybrief_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter.
        The data service relies on the management database of the cardboard factory to provide the chip id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the chip id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=123)
        # assuming the chip id is 456
        print(chip_id)  # 456

        Things to keep in mind:
        - The chip id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['chip_id:int'] - module: database - class_name: GetDiecutterChipIdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera1 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera1 id is 456
        print(camera1_id)  # 456

        Things to keep in mind:
        - The camera1 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera1_id:int'] - module: database - class_name: GetCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera2 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera2 id is 456
        print(camera2_id)  # 456

        Things to keep in mind:
        - The camera2 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera2_id:int'] - module: database - class_name: GetCamera2IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter.
        The data service relies on the management database of the cardboard factory to provide the session id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the current session id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=123)
        # assuming the session id is 456
        print(session_id)  # 456

        Things to keep in mind:
        - The session id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['session_id:int'] - module: database - class_name: GetCurrentSessionIdFromDiecutterIdbrief_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip. - detailed_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip.
        In general each diecutter has exactly one chip embedded into it, and each chip is uniquely identified by an integer id. 
        This means that the chip id has a one-to-one correspondence with the id of the diecutter, but those two ids may not be the same.
        This data service takes a single parameter, namely the id of the chip (an integer) and returns a single dictionary containing the current speed, temperature and number of rotations of the diecutter it is attached to.
        The keys of the dictionary are ""speed"", ""temperature"" and ""rotations"". 
        
        Example usage:
        - If the id of the chip is 123, then the data service would be called as follows:
        chip_id = 123
        current_data = GetCurrentData.call(chip_id=123)
        # get the current speed, temperature and number of rotations
        current_speed = data[""speed""]
        current_temperature = data[""temperature""]
        current_rotations = data[""rotations""]
    
        Things to keep in mind:
        - The refresh rate of the data is 1 second, i.e. the data is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - Note that the values in the dictionary represents the current values of the speed, etc. of the diecutter, they are not aggregated values.
        - Remember that the output value is a dictionary with the above specified keys, so avoid trying to access it using keys not in the above example. - input_parameters: ['chip_id:int'] - output_values: ['diecutter_current_data:dict'] - module: diecutter - class_name: GetCurrentDataFromChip","from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
import time

def pipeline_function():
    diecutter_id = 7
    results = []
    
    # Get the chip ID from the diecutter ID
    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    
    # Collect data over 10 consecutive, non-overlapping time windows of 10 seconds each
    for _ in range(10):
        window_speeds = []
        for _ in range(10):
            current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
            window_speeds.append(current_data['speed'])
            time.sleep(1)  # Wait for 1 second to get the next data point
        
        # Calculate the average speed over the 10-second window
        average_speed = sum(window_speeds) / len(window_speeds)
        results.append({'average_speed': average_speed})
    
    return results","+----+-----------------+
|    |   average_speed |
|----+-----------------|
|  0 |             5.7 |
|  1 |             4.3 |
|  2 |             6.1 |
|  3 |             4.8 |
|  4 |             5.1 |
|  5 |             4.6 |
|  6 |             4.2 |
|  7 |             3.8 |
|  8 |             4.4 |
|  9 |             5.5 |
+----+-----------------+","[{'average_speed': 5.7}, {'average_speed': 4.3}, {'average_speed': 6.1}, {'average_speed': 4.8}, {'average_speed': 5.1}, {'average_speed': 4.6}, {'average_speed': 4.2}, {'average_speed': 3.8}, {'average_speed': 4.4}, {'average_speed': 5.5}]","Generate a list of average temperature and total rotations values for the current session of the diecutter 25, where each value is computed over 3 consecutive, non-overlapping time windows of 30 seconds.","from data_services.database import GetSerialCamera1IdFromDiecutterId
from data_services.database import GetSerialCamera2IdFromDiecutterId
from data_services.database import GetDiecuttersIdOfFactory

def pipeline_function():
    serial_number = 88888404

    results = []

    diecutters_ids = GetDiecuttersIdOfFactory.call()
    for diecutter_id in diecutters_ids:
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=diecutter_id)
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)
        if serial_camera1 == serial_number:
            camera_type = ""camera1""
            results.append({
                'serial number': serial_number,
                'diecutter_id': diecutter_id,
                'type': camera_type
            })
            break
        elif serial_camera2 == serial_number:
            camera_type = ""camera2""
            results.append({
                'serial number': serial_number,
                'diecutter_id': diecutter_id,
                'type': camera_type
            })
            break
    
    return results"
q2,1,"Produce a table showing the mean speeds for the present session of diecutter 7, with each mean calculated across 10 distinct, consecutive time intervals of 10 seconds each.","brief_description: Data service that, given the id of a camera1, provides a frame captured from that camera1. - detailed_description: Data service that, given the id of a camera1, provides a frame captured from that camera1.
        In general instances of camera1 point downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera1 (an integer) and returns a frame captured from that camera1 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera1 is 123, then the data service would be called as follows:
        camera1_id = 123
        frame = GetFrameFromCamera1.call(camera1_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int'] - output_values: ['frame:np.matrix'] - module: camera1 - class_name: GetFrameFromCamera1brief_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors and provide the type of error. - detailed_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors.
        Recall that a camera1 is a camera device that points downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera1 to use and the frame captured from that camera1.
        It returns a boolean value, True if the frame contains a cardboard with errors, False otherwise.
        Also it returns a integer value, 0 if the frame does not contain errors, 1 if the errors are of type hole and 2 if the errors are of type fold. 

        Example usage:
        - If frame is a variable containing the frame captured from the camera1 with id 123, then the data service would be called as follows:
        camera1_id = 123
        contains_errors, type_errors = DetectErrorsInCardboardUsingCamera1.call(camera1_id=123, frame=frame)

        Things to keep in mind:
        - The output is a tuple of boolean and integer, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool', 'error_type:int'] - module: camera1 - class_name: DetectErrorsInCardboardUsingCamera1brief_description: Data service that, given the id of a camera2, provides a frame captured from that camera2. - detailed_description: Data service that, given the id of a camera2, provides a frame captured from that camera2.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera2 (an integer) and returns a frame captured from that camera2 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera2 is 123, then the data service would be called as follows:
        camera2_id = 123
        frame = GetFrameFromCamera2.call(camera2_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int'] - output_values: ['frame:np.matrix'] - module: camera2 - class_name: GetFrameFromCamera2brief_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors. - detailed_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera2 to use and the frame captured from that camera2 that contains a stack of cardboards.
        It returns a boolean value, True if the frame contains a stack of cardboards with errors, False otherwise.

        Example usage:
        - If frame is a variable containing the frame captured from the camera2 with id 123, then the data service would be called as follows:
        camera2_id = 123
        contains_errors, error_type = DetectErrorsInCardboardStack.call(camera2_id=123, frame=frame)

        Things to keep in mind:
        - The output value is a boolean, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool'] - module: camera2 - class_name: DetectErrorsInCardboardStackUsingCamera2brief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera1 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera1.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera1)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera1:int'] - module: database - class_name: GetSerialCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera2 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera2.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera2)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera2:int'] - module: database - class_name: GetSerialCamera2IdFromDiecutterIdbrief_description: Data service that provides the list of id of the diecutters installed in the factory. - detailed_description: Data service that provides the id of the diecutter installed in the factory.
        The data service relies on the management database of the cardboard factory to provide the list of diecutter id.
        The data service takes no parameter and returns a list of integers, which are the id of the diecutters installed in the factory.

        Example usage:
        - The data service would be called as follows:
        diecutters_id = GetDiecuttersIdOfFactory.call()
        # assuming the diecutters id are [1, 2, 3]
        print(diecutters_id)  # [1, 2, 3]

        Things to keep in mind:
        - The diecutters id is a list of integers, so avoid trying to access it as a dictionary. - input_parameters: [] - output_values: ['diecutters_id:list'] - module: database - class_name: GetDiecuttersIdOfFactorybrief_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter.
        The data service relies on the management database of the cardboard factory to provide the chip id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the chip id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=123)
        # assuming the chip id is 456
        print(chip_id)  # 456

        Things to keep in mind:
        - The chip id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['chip_id:int'] - module: database - class_name: GetDiecutterChipIdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera1 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera1 id is 456
        print(camera1_id)  # 456

        Things to keep in mind:
        - The camera1 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera1_id:int'] - module: database - class_name: GetCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera2 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera2 id is 456
        print(camera2_id)  # 456

        Things to keep in mind:
        - The camera2 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera2_id:int'] - module: database - class_name: GetCamera2IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter.
        The data service relies on the management database of the cardboard factory to provide the session id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the current session id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=123)
        # assuming the session id is 456
        print(session_id)  # 456

        Things to keep in mind:
        - The session id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['session_id:int'] - module: database - class_name: GetCurrentSessionIdFromDiecutterIdbrief_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip. - detailed_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip.
        In general each diecutter has exactly one chip embedded into it, and each chip is uniquely identified by an integer id. 
        This means that the chip id has a one-to-one correspondence with the id of the diecutter, but those two ids may not be the same.
        This data service takes a single parameter, namely the id of the chip (an integer) and returns a single dictionary containing the current speed, temperature and number of rotations of the diecutter it is attached to.
        The keys of the dictionary are ""speed"", ""temperature"" and ""rotations"". 
        
        Example usage:
        - If the id of the chip is 123, then the data service would be called as follows:
        chip_id = 123
        current_data = GetCurrentData.call(chip_id=123)
        # get the current speed, temperature and number of rotations
        current_speed = data[""speed""]
        current_temperature = data[""temperature""]
        current_rotations = data[""rotations""]
    
        Things to keep in mind:
        - The refresh rate of the data is 1 second, i.e. the data is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - Note that the values in the dictionary represents the current values of the speed, etc. of the diecutter, they are not aggregated values.
        - Remember that the output value is a dictionary with the above specified keys, so avoid trying to access it using keys not in the above example. - input_parameters: ['chip_id:int'] - output_values: ['diecutter_current_data:dict'] - module: diecutter - class_name: GetCurrentDataFromChip","from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
import time
import threading

def pipeline_function():
    diecutter_id = 7
    interval_duration = 10  # seconds
    intervals = 10
    results = []

    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)

    def collect_speed_data(interval_index, speed_results):
        start_time = time.time()
        speeds = []
        while time.time() - start_time < interval_duration:
            current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
            speeds.append(current_data['speed'])
            time.sleep(1)  # Ensure we only collect data once per second
        average_speed = sum(speeds) / len(speeds)
        speed_results.append({'interval': interval_index + 1, 'mean_speed': average_speed})

    threads = []
    speed_results = []

    for i in range(intervals):
        thread = threading.Thread(target=collect_speed_data, args=(i, speed_results))
        threads.append(thread)
        thread.start()
        time.sleep(interval_duration)  # Start the next interval after the previous one has started

    for thread in threads:
        thread.join()

    # Sort results by interval as threads might finish at different times
    sorted_results = sorted(speed_results, key=lambda x: x['interval'])
    return sorted_results","+----+------------+--------------+
|    |   interval |   mean_speed |
|----+------------+--------------|
|  0 |          1 |          5.7 |
|  1 |          2 |          4.4 |
|  2 |          3 |          6.1 |
|  3 |          4 |          5.6 |
|  4 |          5 |          4.1 |
|  5 |          6 |          4.7 |
|  6 |          7 |          3.9 |
|  7 |          8 |          3.5 |
|  8 |          9 |          4.2 |
|  9 |         10 |          4.8 |
+----+------------+--------------+","[{'interval': 1, 'mean_speed': 5.7}, {'interval': 2, 'mean_speed': 4.4}, {'interval': 3, 'mean_speed': 6.1}, {'interval': 4, 'mean_speed': 5.6}, {'interval': 5, 'mean_speed': 4.1}, {'interval': 6, 'mean_speed': 4.7}, {'interval': 7, 'mean_speed': 3.9}, {'interval': 8, 'mean_speed': 3.5}, {'interval': 9, 'mean_speed': 4.2}, {'interval': 10, 'mean_speed': 4.8}]","Consider the diecutter with id 6, generate a table containing the average temperature computed over a time span of 1 minute.","from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.database import GetCamera2IdFromDiecutterId
from data_services.database import GetCurrentSessionIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
from data_services.camera2 import GetFrameFromCamera2
from data_services.camera2 import DetectErrorsInCardboardStackUsingCamera2
import threading
import time

def pipeline_function():
    diecutter_id = 14
    n_stacks = 30

    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=diecutter_id)
    camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)

    def check_error(camera2_id, frame, card_errors_res):
        has_error, error_type = DetectErrorsInCardboardStackUsingCamera2.call(camera2_id=camera2_id, frame=frame)
        card_errors_res['has_error'] = has_error
        card_errors_res['error_type'] = error_type
    
    def retrieve_diecutter_data(chip_id, diecutter_info_res):
        current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
        diecutter_info_res.update(current_data)

    results = []
    for _ in range(n_stacks):
        frame = GetFrameFromCamera2.call(camera2_id=camera2_id)
        timestamp = time.time()
        card_errors_res = {}
        card_errors = threading.Thread(target=check_error, args=(camera2_id, frame, card_errors_res))
        diecutter_info_res = {}
        diecutter_info = threading.Thread(target=retrieve_diecutter_data, args=(chip_id, diecutter_info_res))
        card_errors.start()
        diecutter_info.start()
        card_errors.join()
        diecutter_info.join()
        if card_errors_res['has_error']:
            result_row = {
                'timestamp': time.strftime(""%Y-%m-%d %H:%M:%S"", time.gmtime(timestamp)),
                'session_id': session_id,
                'error_type': card_errors_res['error_type'],
                'speed': diecutter_info_res['speed'],
                'temperature': diecutter_info_res['temperature'],
                'rotations': diecutter_info_res['rotations']
            }
            results.append(result_row)

    return results
"
q2,2,"Produce a table showing average speed for diecutter 7 during the current session, calculated across ten sequential, non-overlapping intervals of 10 seconds each.","brief_description: Data service that, given the id of a camera1, provides a frame captured from that camera1. - detailed_description: Data service that, given the id of a camera1, provides a frame captured from that camera1.
        In general instances of camera1 point downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera1 (an integer) and returns a frame captured from that camera1 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera1 is 123, then the data service would be called as follows:
        camera1_id = 123
        frame = GetFrameFromCamera1.call(camera1_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int'] - output_values: ['frame:np.matrix'] - module: camera1 - class_name: GetFrameFromCamera1brief_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors and provide the type of error. - detailed_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors.
        Recall that a camera1 is a camera device that points downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera1 to use and the frame captured from that camera1.
        It returns a boolean value, True if the frame contains a cardboard with errors, False otherwise.
        Also it returns a integer value, 0 if the frame does not contain errors, 1 if the errors are of type hole and 2 if the errors are of type fold. 

        Example usage:
        - If frame is a variable containing the frame captured from the camera1 with id 123, then the data service would be called as follows:
        camera1_id = 123
        contains_errors, type_errors = DetectErrorsInCardboardUsingCamera1.call(camera1_id=123, frame=frame)

        Things to keep in mind:
        - The output is a tuple of boolean and integer, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool', 'error_type:int'] - module: camera1 - class_name: DetectErrorsInCardboardUsingCamera1brief_description: Data service that, given the id of a camera2, provides a frame captured from that camera2. - detailed_description: Data service that, given the id of a camera2, provides a frame captured from that camera2.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera2 (an integer) and returns a frame captured from that camera2 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera2 is 123, then the data service would be called as follows:
        camera2_id = 123
        frame = GetFrameFromCamera2.call(camera2_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int'] - output_values: ['frame:np.matrix'] - module: camera2 - class_name: GetFrameFromCamera2brief_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors. - detailed_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera2 to use and the frame captured from that camera2 that contains a stack of cardboards.
        It returns a boolean value, True if the frame contains a stack of cardboards with errors, False otherwise.

        Example usage:
        - If frame is a variable containing the frame captured from the camera2 with id 123, then the data service would be called as follows:
        camera2_id = 123
        contains_errors, error_type = DetectErrorsInCardboardStack.call(camera2_id=123, frame=frame)

        Things to keep in mind:
        - The output value is a boolean, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool'] - module: camera2 - class_name: DetectErrorsInCardboardStackUsingCamera2brief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera1 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera1.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera1)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera1:int'] - module: database - class_name: GetSerialCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera2 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera2.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera2)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera2:int'] - module: database - class_name: GetSerialCamera2IdFromDiecutterIdbrief_description: Data service that provides the list of id of the diecutters installed in the factory. - detailed_description: Data service that provides the id of the diecutter installed in the factory.
        The data service relies on the management database of the cardboard factory to provide the list of diecutter id.
        The data service takes no parameter and returns a list of integers, which are the id of the diecutters installed in the factory.

        Example usage:
        - The data service would be called as follows:
        diecutters_id = GetDiecuttersIdOfFactory.call()
        # assuming the diecutters id are [1, 2, 3]
        print(diecutters_id)  # [1, 2, 3]

        Things to keep in mind:
        - The diecutters id is a list of integers, so avoid trying to access it as a dictionary. - input_parameters: [] - output_values: ['diecutters_id:list'] - module: database - class_name: GetDiecuttersIdOfFactorybrief_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter.
        The data service relies on the management database of the cardboard factory to provide the chip id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the chip id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=123)
        # assuming the chip id is 456
        print(chip_id)  # 456

        Things to keep in mind:
        - The chip id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['chip_id:int'] - module: database - class_name: GetDiecutterChipIdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera1 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera1 id is 456
        print(camera1_id)  # 456

        Things to keep in mind:
        - The camera1 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera1_id:int'] - module: database - class_name: GetCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera2 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera2 id is 456
        print(camera2_id)  # 456

        Things to keep in mind:
        - The camera2 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera2_id:int'] - module: database - class_name: GetCamera2IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter.
        The data service relies on the management database of the cardboard factory to provide the session id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the current session id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=123)
        # assuming the session id is 456
        print(session_id)  # 456

        Things to keep in mind:
        - The session id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['session_id:int'] - module: database - class_name: GetCurrentSessionIdFromDiecutterIdbrief_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip. - detailed_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip.
        In general each diecutter has exactly one chip embedded into it, and each chip is uniquely identified by an integer id. 
        This means that the chip id has a one-to-one correspondence with the id of the diecutter, but those two ids may not be the same.
        This data service takes a single parameter, namely the id of the chip (an integer) and returns a single dictionary containing the current speed, temperature and number of rotations of the diecutter it is attached to.
        The keys of the dictionary are ""speed"", ""temperature"" and ""rotations"". 
        
        Example usage:
        - If the id of the chip is 123, then the data service would be called as follows:
        chip_id = 123
        current_data = GetCurrentData.call(chip_id=123)
        # get the current speed, temperature and number of rotations
        current_speed = data[""speed""]
        current_temperature = data[""temperature""]
        current_rotations = data[""rotations""]
    
        Things to keep in mind:
        - The refresh rate of the data is 1 second, i.e. the data is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - Note that the values in the dictionary represents the current values of the speed, etc. of the diecutter, they are not aggregated values.
        - Remember that the output value is a dictionary with the above specified keys, so avoid trying to access it using keys not in the above example. - input_parameters: ['chip_id:int'] - output_values: ['diecutter_current_data:dict'] - module: diecutter - class_name: GetCurrentDataFromChip","from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
import threading
import time

def pipeline_function():
    diecutter_id = 7
    interval_duration = 10  # seconds
    intervals = 10
    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    
    def collect_speed_data(interval_index, results):
        time.sleep(interval_index * interval_duration)
        current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
        results.append({'interval': interval_index + 1, 'average_speed': current_data['speed']})
    
    threads = []
    results = []
    
    for i in range(intervals):
        thread = threading.Thread(target=collect_speed_data, args=(i, results))
        threads.append(thread)
        thread.start()
    
    for thread in threads:
        thread.join()
    
    # Sorting results by interval to maintain sequential order
    results.sort(key=lambda x: x['interval'])
    return results","+----+------------+-----------------+
|    |   interval |   average_speed |
|----+------------+-----------------|
|  0 |          1 |               8 |
|  1 |          2 |               1 |
|  2 |          3 |               9 |
|  3 |          4 |               1 |
|  4 |          5 |               6 |
|  5 |          6 |               6 |
|  6 |          7 |               6 |
|  7 |          8 |               6 |
|  8 |          9 |               8 |
|  9 |         10 |               6 |
+----+------------+-----------------+","[{'interval': 1, 'average_speed': 8}, {'interval': 2, 'average_speed': 1}, {'interval': 3, 'average_speed': 9}, {'interval': 4, 'average_speed': 1}, {'interval': 5, 'average_speed': 6}, {'interval': 6, 'average_speed': 6}, {'interval': 7, 'average_speed': 6}, {'interval': 8, 'average_speed': 6}, {'interval': 9, 'average_speed': 8}, {'interval': 10, 'average_speed': 6}]","Consider the diecutter with id 6, generate a table containing the average temperature computed over a time span of 1 minute.","from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.database import GetCamera2IdFromDiecutterId
from data_services.database import GetCurrentSessionIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
from data_services.camera2 import GetFrameFromCamera2
from data_services.camera2 import DetectErrorsInCardboardStackUsingCamera2
import threading
import time

def pipeline_function():
    diecutter_id = 14
    n_stacks = 30

    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=diecutter_id)
    camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)

    def check_error(camera2_id, frame, card_errors_res):
        has_error, error_type = DetectErrorsInCardboardStackUsingCamera2.call(camera2_id=camera2_id, frame=frame)
        card_errors_res['has_error'] = has_error
        card_errors_res['error_type'] = error_type
    
    def retrieve_diecutter_data(chip_id, diecutter_info_res):
        current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
        diecutter_info_res.update(current_data)

    results = []
    for _ in range(n_stacks):
        frame = GetFrameFromCamera2.call(camera2_id=camera2_id)
        timestamp = time.time()
        card_errors_res = {}
        card_errors = threading.Thread(target=check_error, args=(camera2_id, frame, card_errors_res))
        diecutter_info_res = {}
        diecutter_info = threading.Thread(target=retrieve_diecutter_data, args=(chip_id, diecutter_info_res))
        card_errors.start()
        diecutter_info.start()
        card_errors.join()
        diecutter_info.join()
        if card_errors_res['has_error']:
            result_row = {
                'timestamp': time.strftime(""%Y-%m-%d %H:%M:%S"", time.gmtime(timestamp)),
                'session_id': session_id,
                'error_type': card_errors_res['error_type'],
                'speed': diecutter_info_res['speed'],
                'temperature': diecutter_info_res['temperature'],
                'rotations': diecutter_info_res['rotations']
            }
            results.append(result_row)

    return results
"
q2,3,"Create a table of mean speed figures for the ongoing session of diecutter 7, each calculated over ten distinct, consecutive time intervals of 10 seconds.","brief_description: Data service that, given the id of a camera1, provides a frame captured from that camera1. - detailed_description: Data service that, given the id of a camera1, provides a frame captured from that camera1.
        In general instances of camera1 point downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera1 (an integer) and returns a frame captured from that camera1 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera1 is 123, then the data service would be called as follows:
        camera1_id = 123
        frame = GetFrameFromCamera1.call(camera1_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int'] - output_values: ['frame:np.matrix'] - module: camera1 - class_name: GetFrameFromCamera1brief_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors and provide the type of error. - detailed_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors.
        Recall that a camera1 is a camera device that points downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera1 to use and the frame captured from that camera1.
        It returns a boolean value, True if the frame contains a cardboard with errors, False otherwise.
        Also it returns a integer value, 0 if the frame does not contain errors, 1 if the errors are of type hole and 2 if the errors are of type fold. 

        Example usage:
        - If frame is a variable containing the frame captured from the camera1 with id 123, then the data service would be called as follows:
        camera1_id = 123
        contains_errors, type_errors = DetectErrorsInCardboardUsingCamera1.call(camera1_id=123, frame=frame)

        Things to keep in mind:
        - The output is a tuple of boolean and integer, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool', 'error_type:int'] - module: camera1 - class_name: DetectErrorsInCardboardUsingCamera1brief_description: Data service that, given the id of a camera2, provides a frame captured from that camera2. - detailed_description: Data service that, given the id of a camera2, provides a frame captured from that camera2.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera2 (an integer) and returns a frame captured from that camera2 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera2 is 123, then the data service would be called as follows:
        camera2_id = 123
        frame = GetFrameFromCamera2.call(camera2_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int'] - output_values: ['frame:np.matrix'] - module: camera2 - class_name: GetFrameFromCamera2brief_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors. - detailed_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera2 to use and the frame captured from that camera2 that contains a stack of cardboards.
        It returns a boolean value, True if the frame contains a stack of cardboards with errors, False otherwise.

        Example usage:
        - If frame is a variable containing the frame captured from the camera2 with id 123, then the data service would be called as follows:
        camera2_id = 123
        contains_errors, error_type = DetectErrorsInCardboardStack.call(camera2_id=123, frame=frame)

        Things to keep in mind:
        - The output value is a boolean, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool'] - module: camera2 - class_name: DetectErrorsInCardboardStackUsingCamera2brief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera1 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera1.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera1)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera1:int'] - module: database - class_name: GetSerialCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera2 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera2.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera2)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera2:int'] - module: database - class_name: GetSerialCamera2IdFromDiecutterIdbrief_description: Data service that provides the list of id of the diecutters installed in the factory. - detailed_description: Data service that provides the id of the diecutter installed in the factory.
        The data service relies on the management database of the cardboard factory to provide the list of diecutter id.
        The data service takes no parameter and returns a list of integers, which are the id of the diecutters installed in the factory.

        Example usage:
        - The data service would be called as follows:
        diecutters_id = GetDiecuttersIdOfFactory.call()
        # assuming the diecutters id are [1, 2, 3]
        print(diecutters_id)  # [1, 2, 3]

        Things to keep in mind:
        - The diecutters id is a list of integers, so avoid trying to access it as a dictionary. - input_parameters: [] - output_values: ['diecutters_id:list'] - module: database - class_name: GetDiecuttersIdOfFactorybrief_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter.
        The data service relies on the management database of the cardboard factory to provide the chip id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the chip id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=123)
        # assuming the chip id is 456
        print(chip_id)  # 456

        Things to keep in mind:
        - The chip id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['chip_id:int'] - module: database - class_name: GetDiecutterChipIdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera1 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera1 id is 456
        print(camera1_id)  # 456

        Things to keep in mind:
        - The camera1 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera1_id:int'] - module: database - class_name: GetCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera2 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera2 id is 456
        print(camera2_id)  # 456

        Things to keep in mind:
        - The camera2 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera2_id:int'] - module: database - class_name: GetCamera2IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter.
        The data service relies on the management database of the cardboard factory to provide the session id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the current session id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=123)
        # assuming the session id is 456
        print(session_id)  # 456

        Things to keep in mind:
        - The session id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['session_id:int'] - module: database - class_name: GetCurrentSessionIdFromDiecutterIdbrief_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip. - detailed_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip.
        In general each diecutter has exactly one chip embedded into it, and each chip is uniquely identified by an integer id. 
        This means that the chip id has a one-to-one correspondence with the id of the diecutter, but those two ids may not be the same.
        This data service takes a single parameter, namely the id of the chip (an integer) and returns a single dictionary containing the current speed, temperature and number of rotations of the diecutter it is attached to.
        The keys of the dictionary are ""speed"", ""temperature"" and ""rotations"". 
        
        Example usage:
        - If the id of the chip is 123, then the data service would be called as follows:
        chip_id = 123
        current_data = GetCurrentData.call(chip_id=123)
        # get the current speed, temperature and number of rotations
        current_speed = data[""speed""]
        current_temperature = data[""temperature""]
        current_rotations = data[""rotations""]
    
        Things to keep in mind:
        - The refresh rate of the data is 1 second, i.e. the data is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - Note that the values in the dictionary represents the current values of the speed, etc. of the diecutter, they are not aggregated values.
        - Remember that the output value is a dictionary with the above specified keys, so avoid trying to access it using keys not in the above example. - input_parameters: ['chip_id:int'] - output_values: ['diecutter_current_data:dict'] - module: diecutter - class_name: GetCurrentDataFromChip","from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
import time
import threading

def pipeline_function():
    diecutter_id = 7
    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    
    def collect_speed_data(interval, results, index):
        time.sleep(interval * index)  # Delay each thread to start at the correct interval
        data = GetCurrentDataFromChip.call(chip_id=chip_id)
        results.append({'mean_speed': data['speed'], 'interval': index + 1})
    
    results = []
    threads = []
    interval_duration = 10  # seconds
    num_intervals = 10
    
    for i in range(num_intervals):
        thread = threading.Thread(target=collect_speed_data, args=(interval_duration, results, i))
        threads.append(thread)
        thread.start()
    
    for thread in threads:
        thread.join()
    
    # Sort results by interval as threads may complete at different times
    sorted_results = sorted(results, key=lambda x: x['interval'])
    return sorted_results","+----+--------------+------------+
|    |   mean_speed |   interval |
|----+--------------+------------|
|  0 |            8 |          1 |
|  1 |            1 |          2 |
|  2 |            9 |          3 |
|  3 |            1 |          4 |
|  4 |            6 |          5 |
|  5 |            6 |          6 |
|  6 |            6 |          7 |
|  7 |            6 |          8 |
|  8 |            8 |          9 |
|  9 |            6 |         10 |
+----+--------------+------------+","[{'mean_speed': 8, 'interval': 1}, {'mean_speed': 1, 'interval': 2}, {'mean_speed': 9, 'interval': 3}, {'mean_speed': 1, 'interval': 4}, {'mean_speed': 6, 'interval': 5}, {'mean_speed': 6, 'interval': 6}, {'mean_speed': 6, 'interval': 7}, {'mean_speed': 6, 'interval': 8}, {'mean_speed': 8, 'interval': 9}, {'mean_speed': 6, 'interval': 10}]","Consider the diecutter with id 6, generate a table containing the average temperature computed over a time span of 1 minute.","from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.database import GetCamera2IdFromDiecutterId
from data_services.database import GetCurrentSessionIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
from data_services.camera2 import GetFrameFromCamera2
from data_services.camera2 import DetectErrorsInCardboardStackUsingCamera2
import threading
import time

def pipeline_function():
    diecutter_id = 14
    n_stacks = 30

    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=diecutter_id)
    camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)

    def check_error(camera2_id, frame, card_errors_res):
        has_error, error_type = DetectErrorsInCardboardStackUsingCamera2.call(camera2_id=camera2_id, frame=frame)
        card_errors_res['has_error'] = has_error
        card_errors_res['error_type'] = error_type
    
    def retrieve_diecutter_data(chip_id, diecutter_info_res):
        current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
        diecutter_info_res.update(current_data)

    results = []
    for _ in range(n_stacks):
        frame = GetFrameFromCamera2.call(camera2_id=camera2_id)
        timestamp = time.time()
        card_errors_res = {}
        card_errors = threading.Thread(target=check_error, args=(camera2_id, frame, card_errors_res))
        diecutter_info_res = {}
        diecutter_info = threading.Thread(target=retrieve_diecutter_data, args=(chip_id, diecutter_info_res))
        card_errors.start()
        diecutter_info.start()
        card_errors.join()
        diecutter_info.join()
        if card_errors_res['has_error']:
            result_row = {
                'timestamp': time.strftime(""%Y-%m-%d %H:%M:%S"", time.gmtime(timestamp)),
                'session_id': session_id,
                'error_type': card_errors_res['error_type'],
                'speed': diecutter_info_res['speed'],
                'temperature': diecutter_info_res['temperature'],
                'rotations': diecutter_info_res['rotations']
            }
            results.append(result_row)

    return results
"
q2,4,"Produce a table outlining the mean speed values for the ongoing session of diecutter 7, calculated over ten successive, distinct time intervals of 10 seconds each.","brief_description: Data service that, given the id of a camera1, provides a frame captured from that camera1. - detailed_description: Data service that, given the id of a camera1, provides a frame captured from that camera1.
        In general instances of camera1 point downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera1 (an integer) and returns a frame captured from that camera1 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera1 is 123, then the data service would be called as follows:
        camera1_id = 123
        frame = GetFrameFromCamera1.call(camera1_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int'] - output_values: ['frame:np.matrix'] - module: camera1 - class_name: GetFrameFromCamera1brief_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors and provide the type of error. - detailed_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors.
        Recall that a camera1 is a camera device that points downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera1 to use and the frame captured from that camera1.
        It returns a boolean value, True if the frame contains a cardboard with errors, False otherwise.
        Also it returns a integer value, 0 if the frame does not contain errors, 1 if the errors are of type hole and 2 if the errors are of type fold. 

        Example usage:
        - If frame is a variable containing the frame captured from the camera1 with id 123, then the data service would be called as follows:
        camera1_id = 123
        contains_errors, type_errors = DetectErrorsInCardboardUsingCamera1.call(camera1_id=123, frame=frame)

        Things to keep in mind:
        - The output is a tuple of boolean and integer, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool', 'error_type:int'] - module: camera1 - class_name: DetectErrorsInCardboardUsingCamera1brief_description: Data service that, given the id of a camera2, provides a frame captured from that camera2. - detailed_description: Data service that, given the id of a camera2, provides a frame captured from that camera2.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera2 (an integer) and returns a frame captured from that camera2 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera2 is 123, then the data service would be called as follows:
        camera2_id = 123
        frame = GetFrameFromCamera2.call(camera2_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int'] - output_values: ['frame:np.matrix'] - module: camera2 - class_name: GetFrameFromCamera2brief_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors. - detailed_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera2 to use and the frame captured from that camera2 that contains a stack of cardboards.
        It returns a boolean value, True if the frame contains a stack of cardboards with errors, False otherwise.

        Example usage:
        - If frame is a variable containing the frame captured from the camera2 with id 123, then the data service would be called as follows:
        camera2_id = 123
        contains_errors, error_type = DetectErrorsInCardboardStack.call(camera2_id=123, frame=frame)

        Things to keep in mind:
        - The output value is a boolean, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool'] - module: camera2 - class_name: DetectErrorsInCardboardStackUsingCamera2brief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera1 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera1.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera1)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera1:int'] - module: database - class_name: GetSerialCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera2 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera2.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera2)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera2:int'] - module: database - class_name: GetSerialCamera2IdFromDiecutterIdbrief_description: Data service that provides the list of id of the diecutters installed in the factory. - detailed_description: Data service that provides the id of the diecutter installed in the factory.
        The data service relies on the management database of the cardboard factory to provide the list of diecutter id.
        The data service takes no parameter and returns a list of integers, which are the id of the diecutters installed in the factory.

        Example usage:
        - The data service would be called as follows:
        diecutters_id = GetDiecuttersIdOfFactory.call()
        # assuming the diecutters id are [1, 2, 3]
        print(diecutters_id)  # [1, 2, 3]

        Things to keep in mind:
        - The diecutters id is a list of integers, so avoid trying to access it as a dictionary. - input_parameters: [] - output_values: ['diecutters_id:list'] - module: database - class_name: GetDiecuttersIdOfFactorybrief_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter.
        The data service relies on the management database of the cardboard factory to provide the chip id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the chip id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=123)
        # assuming the chip id is 456
        print(chip_id)  # 456

        Things to keep in mind:
        - The chip id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['chip_id:int'] - module: database - class_name: GetDiecutterChipIdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera1 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera1 id is 456
        print(camera1_id)  # 456

        Things to keep in mind:
        - The camera1 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera1_id:int'] - module: database - class_name: GetCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera2 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera2 id is 456
        print(camera2_id)  # 456

        Things to keep in mind:
        - The camera2 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera2_id:int'] - module: database - class_name: GetCamera2IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter.
        The data service relies on the management database of the cardboard factory to provide the session id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the current session id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=123)
        # assuming the session id is 456
        print(session_id)  # 456

        Things to keep in mind:
        - The session id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['session_id:int'] - module: database - class_name: GetCurrentSessionIdFromDiecutterIdbrief_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip. - detailed_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip.
        In general each diecutter has exactly one chip embedded into it, and each chip is uniquely identified by an integer id. 
        This means that the chip id has a one-to-one correspondence with the id of the diecutter, but those two ids may not be the same.
        This data service takes a single parameter, namely the id of the chip (an integer) and returns a single dictionary containing the current speed, temperature and number of rotations of the diecutter it is attached to.
        The keys of the dictionary are ""speed"", ""temperature"" and ""rotations"". 
        
        Example usage:
        - If the id of the chip is 123, then the data service would be called as follows:
        chip_id = 123
        current_data = GetCurrentData.call(chip_id=123)
        # get the current speed, temperature and number of rotations
        current_speed = data[""speed""]
        current_temperature = data[""temperature""]
        current_rotations = data[""rotations""]
    
        Things to keep in mind:
        - The refresh rate of the data is 1 second, i.e. the data is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - Note that the values in the dictionary represents the current values of the speed, etc. of the diecutter, they are not aggregated values.
        - Remember that the output value is a dictionary with the above specified keys, so avoid trying to access it using keys not in the above example. - input_parameters: ['chip_id:int'] - output_values: ['diecutter_current_data:dict'] - module: diecutter - class_name: GetCurrentDataFromChip","from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
import time
import threading

def pipeline_function():
    diecutter_id = 7
    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    
    def collect_speed_data(speed_results, chip_id):
        for _ in range(10):
            current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
            speed_results.append({'speed': current_data['speed']})
            time.sleep(10)  # wait for the next 10-second interval

    speed_results = []
    speed_thread = threading.Thread(target=collect_speed_data, args=(speed_results, chip_id))
    speed_thread.start()
    speed_thread.join()

    return speed_results","+----+---------+
|    |   speed |
|----+---------|
|  0 |       8 |
|  1 |       1 |
|  2 |       9 |
|  3 |       1 |
|  4 |       6 |
|  5 |       6 |
|  6 |       6 |
|  7 |       6 |
|  8 |       8 |
|  9 |       6 |
+----+---------+","[{'speed': 8}, {'speed': 1}, {'speed': 9}, {'speed': 1}, {'speed': 6}, {'speed': 6}, {'speed': 6}, {'speed': 6}, {'speed': 8}, {'speed': 6}]","Consider the diecutter with id 6, generate a table containing the average temperature computed over a time span of 1 minute.","from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.database import GetCamera2IdFromDiecutterId
from data_services.database import GetCurrentSessionIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
from data_services.camera2 import GetFrameFromCamera2
from data_services.camera2 import DetectErrorsInCardboardStackUsingCamera2
import threading
import time

def pipeline_function():
    diecutter_id = 14
    n_stacks = 30

    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=diecutter_id)
    camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)

    def check_error(camera2_id, frame, card_errors_res):
        has_error, error_type = DetectErrorsInCardboardStackUsingCamera2.call(camera2_id=camera2_id, frame=frame)
        card_errors_res['has_error'] = has_error
        card_errors_res['error_type'] = error_type
    
    def retrieve_diecutter_data(chip_id, diecutter_info_res):
        current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
        diecutter_info_res.update(current_data)

    results = []
    for _ in range(n_stacks):
        frame = GetFrameFromCamera2.call(camera2_id=camera2_id)
        timestamp = time.time()
        card_errors_res = {}
        card_errors = threading.Thread(target=check_error, args=(camera2_id, frame, card_errors_res))
        diecutter_info_res = {}
        diecutter_info = threading.Thread(target=retrieve_diecutter_data, args=(chip_id, diecutter_info_res))
        card_errors.start()
        diecutter_info.start()
        card_errors.join()
        diecutter_info.join()
        if card_errors_res['has_error']:
            result_row = {
                'timestamp': time.strftime(""%Y-%m-%d %H:%M:%S"", time.gmtime(timestamp)),
                'session_id': session_id,
                'error_type': card_errors_res['error_type'],
                'speed': diecutter_info_res['speed'],
                'temperature': diecutter_info_res['temperature'],
                'rotations': diecutter_info_res['rotations']
            }
            results.append(result_row)

    return results
"
q2,5,"Create a table of mean speeds for the ongoing session of diecutter 7, calculated across 10 successive, distinct time intervals of 10 seconds each.","brief_description: Data service that, given the id of a camera1, provides a frame captured from that camera1. - detailed_description: Data service that, given the id of a camera1, provides a frame captured from that camera1.
        In general instances of camera1 point downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera1 (an integer) and returns a frame captured from that camera1 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera1 is 123, then the data service would be called as follows:
        camera1_id = 123
        frame = GetFrameFromCamera1.call(camera1_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int'] - output_values: ['frame:np.matrix'] - module: camera1 - class_name: GetFrameFromCamera1brief_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors and provide the type of error. - detailed_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors.
        Recall that a camera1 is a camera device that points downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera1 to use and the frame captured from that camera1.
        It returns a boolean value, True if the frame contains a cardboard with errors, False otherwise.
        Also it returns a integer value, 0 if the frame does not contain errors, 1 if the errors are of type hole and 2 if the errors are of type fold. 

        Example usage:
        - If frame is a variable containing the frame captured from the camera1 with id 123, then the data service would be called as follows:
        camera1_id = 123
        contains_errors, type_errors = DetectErrorsInCardboardUsingCamera1.call(camera1_id=123, frame=frame)

        Things to keep in mind:
        - The output is a tuple of boolean and integer, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool', 'error_type:int'] - module: camera1 - class_name: DetectErrorsInCardboardUsingCamera1brief_description: Data service that, given the id of a camera2, provides a frame captured from that camera2. - detailed_description: Data service that, given the id of a camera2, provides a frame captured from that camera2.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera2 (an integer) and returns a frame captured from that camera2 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera2 is 123, then the data service would be called as follows:
        camera2_id = 123
        frame = GetFrameFromCamera2.call(camera2_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int'] - output_values: ['frame:np.matrix'] - module: camera2 - class_name: GetFrameFromCamera2brief_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors. - detailed_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera2 to use and the frame captured from that camera2 that contains a stack of cardboards.
        It returns a boolean value, True if the frame contains a stack of cardboards with errors, False otherwise.

        Example usage:
        - If frame is a variable containing the frame captured from the camera2 with id 123, then the data service would be called as follows:
        camera2_id = 123
        contains_errors, error_type = DetectErrorsInCardboardStack.call(camera2_id=123, frame=frame)

        Things to keep in mind:
        - The output value is a boolean, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool'] - module: camera2 - class_name: DetectErrorsInCardboardStackUsingCamera2brief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera1 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera1.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera1)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera1:int'] - module: database - class_name: GetSerialCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera2 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera2.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera2)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera2:int'] - module: database - class_name: GetSerialCamera2IdFromDiecutterIdbrief_description: Data service that provides the list of id of the diecutters installed in the factory. - detailed_description: Data service that provides the id of the diecutter installed in the factory.
        The data service relies on the management database of the cardboard factory to provide the list of diecutter id.
        The data service takes no parameter and returns a list of integers, which are the id of the diecutters installed in the factory.

        Example usage:
        - The data service would be called as follows:
        diecutters_id = GetDiecuttersIdOfFactory.call()
        # assuming the diecutters id are [1, 2, 3]
        print(diecutters_id)  # [1, 2, 3]

        Things to keep in mind:
        - The diecutters id is a list of integers, so avoid trying to access it as a dictionary. - input_parameters: [] - output_values: ['diecutters_id:list'] - module: database - class_name: GetDiecuttersIdOfFactorybrief_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter.
        The data service relies on the management database of the cardboard factory to provide the chip id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the chip id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=123)
        # assuming the chip id is 456
        print(chip_id)  # 456

        Things to keep in mind:
        - The chip id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['chip_id:int'] - module: database - class_name: GetDiecutterChipIdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera1 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera1 id is 456
        print(camera1_id)  # 456

        Things to keep in mind:
        - The camera1 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera1_id:int'] - module: database - class_name: GetCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera2 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera2 id is 456
        print(camera2_id)  # 456

        Things to keep in mind:
        - The camera2 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera2_id:int'] - module: database - class_name: GetCamera2IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter.
        The data service relies on the management database of the cardboard factory to provide the session id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the current session id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=123)
        # assuming the session id is 456
        print(session_id)  # 456

        Things to keep in mind:
        - The session id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['session_id:int'] - module: database - class_name: GetCurrentSessionIdFromDiecutterIdbrief_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip. - detailed_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip.
        In general each diecutter has exactly one chip embedded into it, and each chip is uniquely identified by an integer id. 
        This means that the chip id has a one-to-one correspondence with the id of the diecutter, but those two ids may not be the same.
        This data service takes a single parameter, namely the id of the chip (an integer) and returns a single dictionary containing the current speed, temperature and number of rotations of the diecutter it is attached to.
        The keys of the dictionary are ""speed"", ""temperature"" and ""rotations"". 
        
        Example usage:
        - If the id of the chip is 123, then the data service would be called as follows:
        chip_id = 123
        current_data = GetCurrentData.call(chip_id=123)
        # get the current speed, temperature and number of rotations
        current_speed = data[""speed""]
        current_temperature = data[""temperature""]
        current_rotations = data[""rotations""]
    
        Things to keep in mind:
        - The refresh rate of the data is 1 second, i.e. the data is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - Note that the values in the dictionary represents the current values of the speed, etc. of the diecutter, they are not aggregated values.
        - Remember that the output value is a dictionary with the above specified keys, so avoid trying to access it using keys not in the above example. - input_parameters: ['chip_id:int'] - output_values: ['diecutter_current_data:dict'] - module: diecutter - class_name: GetCurrentDataFromChip","from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
import time
import threading

def pipeline_function():
    diecutter_id = 7
    interval_duration = 10  # seconds
    intervals = 10
    results = []

    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)

    def collect_speed_data(interval_index, speed_results):
        time.sleep(interval_index * interval_duration)
        current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
        speed_results.append({'interval': interval_index + 1, 'mean_speed': current_data['speed']})

    threads = []
    speed_results = []

    for i in range(intervals):
        thread = threading.Thread(target=collect_speed_data, args=(i, speed_results))
        threads.append(thread)
        thread.start()

    for thread in threads:
        thread.join()

    # Sorting results by interval as threads might finish at different times
    sorted_speed_results = sorted(speed_results, key=lambda x: x['interval'])
    return sorted_speed_results","+----+------------+--------------+
|    |   interval |   mean_speed |
|----+------------+--------------|
|  0 |          1 |            8 |
|  1 |          2 |            1 |
|  2 |          3 |            9 |
|  3 |          4 |            1 |
|  4 |          5 |            6 |
|  5 |          6 |            6 |
|  6 |          7 |            6 |
|  7 |          8 |            6 |
|  8 |          9 |            8 |
|  9 |         10 |            6 |
+----+------------+--------------+","[{'interval': 1, 'mean_speed': 8}, {'interval': 2, 'mean_speed': 1}, {'interval': 3, 'mean_speed': 9}, {'interval': 4, 'mean_speed': 1}, {'interval': 5, 'mean_speed': 6}, {'interval': 6, 'mean_speed': 6}, {'interval': 7, 'mean_speed': 6}, {'interval': 8, 'mean_speed': 6}, {'interval': 9, 'mean_speed': 8}, {'interval': 10, 'mean_speed': 6}]","Consider the diecutter with id 6, generate a table containing the average temperature computed over a time span of 1 minute.","from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.database import GetCamera2IdFromDiecutterId
from data_services.database import GetCurrentSessionIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
from data_services.camera2 import GetFrameFromCamera2
from data_services.camera2 import DetectErrorsInCardboardStackUsingCamera2
import threading
import time

def pipeline_function():
    diecutter_id = 14
    n_stacks = 30

    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=diecutter_id)
    camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)

    def check_error(camera2_id, frame, card_errors_res):
        has_error, error_type = DetectErrorsInCardboardStackUsingCamera2.call(camera2_id=camera2_id, frame=frame)
        card_errors_res['has_error'] = has_error
        card_errors_res['error_type'] = error_type
    
    def retrieve_diecutter_data(chip_id, diecutter_info_res):
        current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
        diecutter_info_res.update(current_data)

    results = []
    for _ in range(n_stacks):
        frame = GetFrameFromCamera2.call(camera2_id=camera2_id)
        timestamp = time.time()
        card_errors_res = {}
        card_errors = threading.Thread(target=check_error, args=(camera2_id, frame, card_errors_res))
        diecutter_info_res = {}
        diecutter_info = threading.Thread(target=retrieve_diecutter_data, args=(chip_id, diecutter_info_res))
        card_errors.start()
        diecutter_info.start()
        card_errors.join()
        diecutter_info.join()
        if card_errors_res['has_error']:
            result_row = {
                'timestamp': time.strftime(""%Y-%m-%d %H:%M:%S"", time.gmtime(timestamp)),
                'session_id': session_id,
                'error_type': card_errors_res['error_type'],
                'speed': diecutter_info_res['speed'],
                'temperature': diecutter_info_res['temperature'],
                'rotations': diecutter_info_res['rotations']
            }
            results.append(result_row)

    return results
"
q2,6,"Produce a table showing the mean speeds for the active session of diecutter 7, calculated over ten sequential, distinct 10-second intervals.","brief_description: Data service that, given the id of a camera1, provides a frame captured from that camera1. - detailed_description: Data service that, given the id of a camera1, provides a frame captured from that camera1.
        In general instances of camera1 point downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera1 (an integer) and returns a frame captured from that camera1 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera1 is 123, then the data service would be called as follows:
        camera1_id = 123
        frame = GetFrameFromCamera1.call(camera1_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int'] - output_values: ['frame:np.matrix'] - module: camera1 - class_name: GetFrameFromCamera1brief_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors and provide the type of error. - detailed_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors.
        Recall that a camera1 is a camera device that points downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera1 to use and the frame captured from that camera1.
        It returns a boolean value, True if the frame contains a cardboard with errors, False otherwise.
        Also it returns a integer value, 0 if the frame does not contain errors, 1 if the errors are of type hole and 2 if the errors are of type fold. 

        Example usage:
        - If frame is a variable containing the frame captured from the camera1 with id 123, then the data service would be called as follows:
        camera1_id = 123
        contains_errors, type_errors = DetectErrorsInCardboardUsingCamera1.call(camera1_id=123, frame=frame)

        Things to keep in mind:
        - The output is a tuple of boolean and integer, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool', 'error_type:int'] - module: camera1 - class_name: DetectErrorsInCardboardUsingCamera1brief_description: Data service that, given the id of a camera2, provides a frame captured from that camera2. - detailed_description: Data service that, given the id of a camera2, provides a frame captured from that camera2.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera2 (an integer) and returns a frame captured from that camera2 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera2 is 123, then the data service would be called as follows:
        camera2_id = 123
        frame = GetFrameFromCamera2.call(camera2_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int'] - output_values: ['frame:np.matrix'] - module: camera2 - class_name: GetFrameFromCamera2brief_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors. - detailed_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera2 to use and the frame captured from that camera2 that contains a stack of cardboards.
        It returns a boolean value, True if the frame contains a stack of cardboards with errors, False otherwise.

        Example usage:
        - If frame is a variable containing the frame captured from the camera2 with id 123, then the data service would be called as follows:
        camera2_id = 123
        contains_errors, error_type = DetectErrorsInCardboardStack.call(camera2_id=123, frame=frame)

        Things to keep in mind:
        - The output value is a boolean, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool'] - module: camera2 - class_name: DetectErrorsInCardboardStackUsingCamera2brief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera1 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera1.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera1)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera1:int'] - module: database - class_name: GetSerialCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera2 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera2.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera2)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera2:int'] - module: database - class_name: GetSerialCamera2IdFromDiecutterIdbrief_description: Data service that provides the list of id of the diecutters installed in the factory. - detailed_description: Data service that provides the id of the diecutter installed in the factory.
        The data service relies on the management database of the cardboard factory to provide the list of diecutter id.
        The data service takes no parameter and returns a list of integers, which are the id of the diecutters installed in the factory.

        Example usage:
        - The data service would be called as follows:
        diecutters_id = GetDiecuttersIdOfFactory.call()
        # assuming the diecutters id are [1, 2, 3]
        print(diecutters_id)  # [1, 2, 3]

        Things to keep in mind:
        - The diecutters id is a list of integers, so avoid trying to access it as a dictionary. - input_parameters: [] - output_values: ['diecutters_id:list'] - module: database - class_name: GetDiecuttersIdOfFactorybrief_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter.
        The data service relies on the management database of the cardboard factory to provide the chip id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the chip id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=123)
        # assuming the chip id is 456
        print(chip_id)  # 456

        Things to keep in mind:
        - The chip id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['chip_id:int'] - module: database - class_name: GetDiecutterChipIdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera1 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera1 id is 456
        print(camera1_id)  # 456

        Things to keep in mind:
        - The camera1 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera1_id:int'] - module: database - class_name: GetCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera2 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera2 id is 456
        print(camera2_id)  # 456

        Things to keep in mind:
        - The camera2 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera2_id:int'] - module: database - class_name: GetCamera2IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter.
        The data service relies on the management database of the cardboard factory to provide the session id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the current session id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=123)
        # assuming the session id is 456
        print(session_id)  # 456

        Things to keep in mind:
        - The session id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['session_id:int'] - module: database - class_name: GetCurrentSessionIdFromDiecutterIdbrief_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip. - detailed_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip.
        In general each diecutter has exactly one chip embedded into it, and each chip is uniquely identified by an integer id. 
        This means that the chip id has a one-to-one correspondence with the id of the diecutter, but those two ids may not be the same.
        This data service takes a single parameter, namely the id of the chip (an integer) and returns a single dictionary containing the current speed, temperature and number of rotations of the diecutter it is attached to.
        The keys of the dictionary are ""speed"", ""temperature"" and ""rotations"". 
        
        Example usage:
        - If the id of the chip is 123, then the data service would be called as follows:
        chip_id = 123
        current_data = GetCurrentData.call(chip_id=123)
        # get the current speed, temperature and number of rotations
        current_speed = data[""speed""]
        current_temperature = data[""temperature""]
        current_rotations = data[""rotations""]
    
        Things to keep in mind:
        - The refresh rate of the data is 1 second, i.e. the data is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - Note that the values in the dictionary represents the current values of the speed, etc. of the diecutter, they are not aggregated values.
        - Remember that the output value is a dictionary with the above specified keys, so avoid trying to access it using keys not in the above example. - input_parameters: ['chip_id:int'] - output_values: ['diecutter_current_data:dict'] - module: diecutter - class_name: GetCurrentDataFromChip","from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
import time

def pipeline_function():
    diecutter_id = 7
    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    
    results = []
    for _ in range(10):  # 10 sequential 10-second intervals
        speeds = []
        for _ in range(10):  # Each second in the 10-second interval
            current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
            speeds.append(current_data['speed'])
            time.sleep(1)  # Wait for the next second to get fresh data
        mean_speed = sum(speeds) / len(speeds)
        results.append({'mean_speed': mean_speed})
        time.sleep(9)  # Wait for the remaining time of the 10-second interval after collecting 10 data points

    return results","+----+--------------+
|    |   mean_speed |
|----+--------------|
|  0 |          5.7 |
|  1 |          4.3 |
|  2 |          6.1 |
|  3 |          4.8 |
|  4 |          5.1 |
|  5 |          4.6 |
|  6 |          4.2 |
|  7 |          3.8 |
|  8 |          4.4 |
|  9 |          5.5 |
+----+--------------+","[{'mean_speed': 5.7}, {'mean_speed': 4.3}, {'mean_speed': 6.1}, {'mean_speed': 4.8}, {'mean_speed': 5.1}, {'mean_speed': 4.6}, {'mean_speed': 4.2}, {'mean_speed': 3.8}, {'mean_speed': 4.4}, {'mean_speed': 5.5}]","Consider the diecutter with id 6, generate a table containing the average temperature computed over a time span of 1 minute.","from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.database import GetCamera2IdFromDiecutterId
from data_services.database import GetCurrentSessionIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
from data_services.camera2 import GetFrameFromCamera2
from data_services.camera2 import DetectErrorsInCardboardStackUsingCamera2
import threading
import time

def pipeline_function():
    diecutter_id = 14
    n_stacks = 30

    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=diecutter_id)
    camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)

    def check_error(camera2_id, frame, card_errors_res):
        has_error, error_type = DetectErrorsInCardboardStackUsingCamera2.call(camera2_id=camera2_id, frame=frame)
        card_errors_res['has_error'] = has_error
        card_errors_res['error_type'] = error_type
    
    def retrieve_diecutter_data(chip_id, diecutter_info_res):
        current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
        diecutter_info_res.update(current_data)

    results = []
    for _ in range(n_stacks):
        frame = GetFrameFromCamera2.call(camera2_id=camera2_id)
        timestamp = time.time()
        card_errors_res = {}
        card_errors = threading.Thread(target=check_error, args=(camera2_id, frame, card_errors_res))
        diecutter_info_res = {}
        diecutter_info = threading.Thread(target=retrieve_diecutter_data, args=(chip_id, diecutter_info_res))
        card_errors.start()
        diecutter_info.start()
        card_errors.join()
        diecutter_info.join()
        if card_errors_res['has_error']:
            result_row = {
                'timestamp': time.strftime(""%Y-%m-%d %H:%M:%S"", time.gmtime(timestamp)),
                'session_id': session_id,
                'error_type': card_errors_res['error_type'],
                'speed': diecutter_info_res['speed'],
                'temperature': diecutter_info_res['temperature'],
                'rotations': diecutter_info_res['rotations']
            }
            results.append(result_row)

    return results
"
q2,7,"Produce a table of mean velocity for the ongoing session of diecutter 7, each mean computed across ten successive, distinct time intervals of ten seconds each.","brief_description: Data service that, given the id of a camera1, provides a frame captured from that camera1. - detailed_description: Data service that, given the id of a camera1, provides a frame captured from that camera1.
        In general instances of camera1 point downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera1 (an integer) and returns a frame captured from that camera1 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera1 is 123, then the data service would be called as follows:
        camera1_id = 123
        frame = GetFrameFromCamera1.call(camera1_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int'] - output_values: ['frame:np.matrix'] - module: camera1 - class_name: GetFrameFromCamera1brief_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors and provide the type of error. - detailed_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors.
        Recall that a camera1 is a camera device that points downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera1 to use and the frame captured from that camera1.
        It returns a boolean value, True if the frame contains a cardboard with errors, False otherwise.
        Also it returns a integer value, 0 if the frame does not contain errors, 1 if the errors are of type hole and 2 if the errors are of type fold. 

        Example usage:
        - If frame is a variable containing the frame captured from the camera1 with id 123, then the data service would be called as follows:
        camera1_id = 123
        contains_errors, type_errors = DetectErrorsInCardboardUsingCamera1.call(camera1_id=123, frame=frame)

        Things to keep in mind:
        - The output is a tuple of boolean and integer, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool', 'error_type:int'] - module: camera1 - class_name: DetectErrorsInCardboardUsingCamera1brief_description: Data service that, given the id of a camera2, provides a frame captured from that camera2. - detailed_description: Data service that, given the id of a camera2, provides a frame captured from that camera2.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera2 (an integer) and returns a frame captured from that camera2 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera2 is 123, then the data service would be called as follows:
        camera2_id = 123
        frame = GetFrameFromCamera2.call(camera2_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int'] - output_values: ['frame:np.matrix'] - module: camera2 - class_name: GetFrameFromCamera2brief_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors. - detailed_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera2 to use and the frame captured from that camera2 that contains a stack of cardboards.
        It returns a boolean value, True if the frame contains a stack of cardboards with errors, False otherwise.

        Example usage:
        - If frame is a variable containing the frame captured from the camera2 with id 123, then the data service would be called as follows:
        camera2_id = 123
        contains_errors, error_type = DetectErrorsInCardboardStack.call(camera2_id=123, frame=frame)

        Things to keep in mind:
        - The output value is a boolean, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool'] - module: camera2 - class_name: DetectErrorsInCardboardStackUsingCamera2brief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera1 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera1.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera1)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera1:int'] - module: database - class_name: GetSerialCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera2 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera2.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera2)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera2:int'] - module: database - class_name: GetSerialCamera2IdFromDiecutterIdbrief_description: Data service that provides the list of id of the diecutters installed in the factory. - detailed_description: Data service that provides the id of the diecutter installed in the factory.
        The data service relies on the management database of the cardboard factory to provide the list of diecutter id.
        The data service takes no parameter and returns a list of integers, which are the id of the diecutters installed in the factory.

        Example usage:
        - The data service would be called as follows:
        diecutters_id = GetDiecuttersIdOfFactory.call()
        # assuming the diecutters id are [1, 2, 3]
        print(diecutters_id)  # [1, 2, 3]

        Things to keep in mind:
        - The diecutters id is a list of integers, so avoid trying to access it as a dictionary. - input_parameters: [] - output_values: ['diecutters_id:list'] - module: database - class_name: GetDiecuttersIdOfFactorybrief_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter.
        The data service relies on the management database of the cardboard factory to provide the chip id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the chip id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=123)
        # assuming the chip id is 456
        print(chip_id)  # 456

        Things to keep in mind:
        - The chip id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['chip_id:int'] - module: database - class_name: GetDiecutterChipIdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera1 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera1 id is 456
        print(camera1_id)  # 456

        Things to keep in mind:
        - The camera1 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera1_id:int'] - module: database - class_name: GetCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera2 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera2 id is 456
        print(camera2_id)  # 456

        Things to keep in mind:
        - The camera2 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera2_id:int'] - module: database - class_name: GetCamera2IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter.
        The data service relies on the management database of the cardboard factory to provide the session id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the current session id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=123)
        # assuming the session id is 456
        print(session_id)  # 456

        Things to keep in mind:
        - The session id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['session_id:int'] - module: database - class_name: GetCurrentSessionIdFromDiecutterIdbrief_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip. - detailed_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip.
        In general each diecutter has exactly one chip embedded into it, and each chip is uniquely identified by an integer id. 
        This means that the chip id has a one-to-one correspondence with the id of the diecutter, but those two ids may not be the same.
        This data service takes a single parameter, namely the id of the chip (an integer) and returns a single dictionary containing the current speed, temperature and number of rotations of the diecutter it is attached to.
        The keys of the dictionary are ""speed"", ""temperature"" and ""rotations"". 
        
        Example usage:
        - If the id of the chip is 123, then the data service would be called as follows:
        chip_id = 123
        current_data = GetCurrentData.call(chip_id=123)
        # get the current speed, temperature and number of rotations
        current_speed = data[""speed""]
        current_temperature = data[""temperature""]
        current_rotations = data[""rotations""]
    
        Things to keep in mind:
        - The refresh rate of the data is 1 second, i.e. the data is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - Note that the values in the dictionary represents the current values of the speed, etc. of the diecutter, they are not aggregated values.
        - Remember that the output value is a dictionary with the above specified keys, so avoid trying to access it using keys not in the above example. - input_parameters: ['chip_id:int'] - output_values: ['diecutter_current_data:dict'] - module: diecutter - class_name: GetCurrentDataFromChip","from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
import time
import threading

def pipeline_function():
    diecutter_id = 7
    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    
    def collect_speed_data(interval, results, index):
        start_time = time.time()
        while time.time() - start_time < interval:
            current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
            results[index].append(current_data['speed'])
            time.sleep(1)  # Sleep to ensure data is collected once per second

    results = [[] for _ in range(10)]
    threads = []
    for i in range(10):
        t = threading.Thread(target=collect_speed_data, args=(10, results, i))
        t.start()
        threads.append(t)
        time.sleep(10)  # Start the next interval after 10 seconds

    for t in threads:
        t.join()

    mean_speeds = [{'interval': i+1, 'mean_speed': sum(data)/len(data) if data else 0} for i, data in enumerate(results)]
    return mean_speeds","+----+------------+--------------+
|    |   interval |   mean_speed |
|----+------------+--------------|
|  0 |          1 |          5.7 |
|  1 |          2 |          4.4 |
|  2 |          3 |          6.1 |
|  3 |          4 |          5.6 |
|  4 |          5 |          4.1 |
|  5 |          6 |          4.7 |
|  6 |          7 |          3.9 |
|  7 |          8 |          3.5 |
|  8 |          9 |          4.2 |
|  9 |         10 |          4.8 |
+----+------------+--------------+","[{'interval': 1, 'mean_speed': 5.7}, {'interval': 2, 'mean_speed': 4.4}, {'interval': 3, 'mean_speed': 6.1}, {'interval': 4, 'mean_speed': 5.6}, {'interval': 5, 'mean_speed': 4.1}, {'interval': 6, 'mean_speed': 4.7}, {'interval': 7, 'mean_speed': 3.9}, {'interval': 8, 'mean_speed': 3.5}, {'interval': 9, 'mean_speed': 4.2}, {'interval': 10, 'mean_speed': 4.8}]","Consider the diecutter with id 6, generate a table containing the average temperature computed over a time span of 1 minute.","from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.database import GetCamera2IdFromDiecutterId
from data_services.database import GetCurrentSessionIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
from data_services.camera2 import GetFrameFromCamera2
from data_services.camera2 import DetectErrorsInCardboardStackUsingCamera2
import threading
import time

def pipeline_function():
    diecutter_id = 14
    n_stacks = 30

    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=diecutter_id)
    camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)

    def check_error(camera2_id, frame, card_errors_res):
        has_error, error_type = DetectErrorsInCardboardStackUsingCamera2.call(camera2_id=camera2_id, frame=frame)
        card_errors_res['has_error'] = has_error
        card_errors_res['error_type'] = error_type
    
    def retrieve_diecutter_data(chip_id, diecutter_info_res):
        current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
        diecutter_info_res.update(current_data)

    results = []
    for _ in range(n_stacks):
        frame = GetFrameFromCamera2.call(camera2_id=camera2_id)
        timestamp = time.time()
        card_errors_res = {}
        card_errors = threading.Thread(target=check_error, args=(camera2_id, frame, card_errors_res))
        diecutter_info_res = {}
        diecutter_info = threading.Thread(target=retrieve_diecutter_data, args=(chip_id, diecutter_info_res))
        card_errors.start()
        diecutter_info.start()
        card_errors.join()
        diecutter_info.join()
        if card_errors_res['has_error']:
            result_row = {
                'timestamp': time.strftime(""%Y-%m-%d %H:%M:%S"", time.gmtime(timestamp)),
                'session_id': session_id,
                'error_type': card_errors_res['error_type'],
                'speed': diecutter_info_res['speed'],
                'temperature': diecutter_info_res['temperature'],
                'rotations': diecutter_info_res['rotations']
            }
            results.append(result_row)

    return results
"
q2,8,"Produce a table of mean speed metrics for the ongoing session of diecutter 7, with each mean speed calculated across 10 successive, distinct 10-second intervals.","brief_description: Data service that, given the id of a camera1, provides a frame captured from that camera1. - detailed_description: Data service that, given the id of a camera1, provides a frame captured from that camera1.
        In general instances of camera1 point downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera1 (an integer) and returns a frame captured from that camera1 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera1 is 123, then the data service would be called as follows:
        camera1_id = 123
        frame = GetFrameFromCamera1.call(camera1_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int'] - output_values: ['frame:np.matrix'] - module: camera1 - class_name: GetFrameFromCamera1brief_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors and provide the type of error. - detailed_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors.
        Recall that a camera1 is a camera device that points downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera1 to use and the frame captured from that camera1.
        It returns a boolean value, True if the frame contains a cardboard with errors, False otherwise.
        Also it returns a integer value, 0 if the frame does not contain errors, 1 if the errors are of type hole and 2 if the errors are of type fold. 

        Example usage:
        - If frame is a variable containing the frame captured from the camera1 with id 123, then the data service would be called as follows:
        camera1_id = 123
        contains_errors, type_errors = DetectErrorsInCardboardUsingCamera1.call(camera1_id=123, frame=frame)

        Things to keep in mind:
        - The output is a tuple of boolean and integer, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool', 'error_type:int'] - module: camera1 - class_name: DetectErrorsInCardboardUsingCamera1brief_description: Data service that, given the id of a camera2, provides a frame captured from that camera2. - detailed_description: Data service that, given the id of a camera2, provides a frame captured from that camera2.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera2 (an integer) and returns a frame captured from that camera2 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera2 is 123, then the data service would be called as follows:
        camera2_id = 123
        frame = GetFrameFromCamera2.call(camera2_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int'] - output_values: ['frame:np.matrix'] - module: camera2 - class_name: GetFrameFromCamera2brief_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors. - detailed_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera2 to use and the frame captured from that camera2 that contains a stack of cardboards.
        It returns a boolean value, True if the frame contains a stack of cardboards with errors, False otherwise.

        Example usage:
        - If frame is a variable containing the frame captured from the camera2 with id 123, then the data service would be called as follows:
        camera2_id = 123
        contains_errors, error_type = DetectErrorsInCardboardStack.call(camera2_id=123, frame=frame)

        Things to keep in mind:
        - The output value is a boolean, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool'] - module: camera2 - class_name: DetectErrorsInCardboardStackUsingCamera2brief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera1 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera1.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera1)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera1:int'] - module: database - class_name: GetSerialCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera2 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera2.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera2)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera2:int'] - module: database - class_name: GetSerialCamera2IdFromDiecutterIdbrief_description: Data service that provides the list of id of the diecutters installed in the factory. - detailed_description: Data service that provides the id of the diecutter installed in the factory.
        The data service relies on the management database of the cardboard factory to provide the list of diecutter id.
        The data service takes no parameter and returns a list of integers, which are the id of the diecutters installed in the factory.

        Example usage:
        - The data service would be called as follows:
        diecutters_id = GetDiecuttersIdOfFactory.call()
        # assuming the diecutters id are [1, 2, 3]
        print(diecutters_id)  # [1, 2, 3]

        Things to keep in mind:
        - The diecutters id is a list of integers, so avoid trying to access it as a dictionary. - input_parameters: [] - output_values: ['diecutters_id:list'] - module: database - class_name: GetDiecuttersIdOfFactorybrief_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter.
        The data service relies on the management database of the cardboard factory to provide the chip id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the chip id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=123)
        # assuming the chip id is 456
        print(chip_id)  # 456

        Things to keep in mind:
        - The chip id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['chip_id:int'] - module: database - class_name: GetDiecutterChipIdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera1 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera1 id is 456
        print(camera1_id)  # 456

        Things to keep in mind:
        - The camera1 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera1_id:int'] - module: database - class_name: GetCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera2 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera2 id is 456
        print(camera2_id)  # 456

        Things to keep in mind:
        - The camera2 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera2_id:int'] - module: database - class_name: GetCamera2IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter.
        The data service relies on the management database of the cardboard factory to provide the session id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the current session id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=123)
        # assuming the session id is 456
        print(session_id)  # 456

        Things to keep in mind:
        - The session id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['session_id:int'] - module: database - class_name: GetCurrentSessionIdFromDiecutterIdbrief_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip. - detailed_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip.
        In general each diecutter has exactly one chip embedded into it, and each chip is uniquely identified by an integer id. 
        This means that the chip id has a one-to-one correspondence with the id of the diecutter, but those two ids may not be the same.
        This data service takes a single parameter, namely the id of the chip (an integer) and returns a single dictionary containing the current speed, temperature and number of rotations of the diecutter it is attached to.
        The keys of the dictionary are ""speed"", ""temperature"" and ""rotations"". 
        
        Example usage:
        - If the id of the chip is 123, then the data service would be called as follows:
        chip_id = 123
        current_data = GetCurrentData.call(chip_id=123)
        # get the current speed, temperature and number of rotations
        current_speed = data[""speed""]
        current_temperature = data[""temperature""]
        current_rotations = data[""rotations""]
    
        Things to keep in mind:
        - The refresh rate of the data is 1 second, i.e. the data is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - Note that the values in the dictionary represents the current values of the speed, etc. of the diecutter, they are not aggregated values.
        - Remember that the output value is a dictionary with the above specified keys, so avoid trying to access it using keys not in the above example. - input_parameters: ['chip_id:int'] - output_values: ['diecutter_current_data:dict'] - module: diecutter - class_name: GetCurrentDataFromChip","from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
import threading
import time

def pipeline_function():
    diecutter_id = 7
    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    
    # Define a function to collect speed data over 10 seconds
    def collect_speed_data(interval, results, index):
        speeds = []
        start_time = time.time()
        while time.time() - start_time < interval:
            current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
            speeds.append(current_data['speed'])
            time.sleep(1)  # Ensure we collect data every second
        results[index] = sum(speeds) / len(speeds) if speeds else 0

    # We need to calculate mean speed over 10 successive 10-second intervals
    intervals = 10
    interval_duration = 10  # seconds
    results = [0] * intervals
    threads = []
    
    for i in range(intervals):
        thread = threading.Thread(target=collect_speed_data, args=(interval_duration, results, i))
        threads.append(thread)
        thread.start()
        time.sleep(interval_duration)  # Start the next interval after the previous one finishes

    for thread in threads:
        thread.join()

    # Prepare the output as a list of dictionaries
    output = [{'interval': i + 1, 'mean_speed': results[i]} for i in range(intervals)]
    return output","+----+------------+--------------+
|    |   interval |   mean_speed |
|----+------------+--------------|
|  0 |          1 |          5.7 |
|  1 |          2 |          4.4 |
|  2 |          3 |          6.1 |
|  3 |          4 |          5.6 |
|  4 |          5 |          4.1 |
|  5 |          6 |          4.7 |
|  6 |          7 |          3.9 |
|  7 |          8 |          3.5 |
|  8 |          9 |          4.2 |
|  9 |         10 |          4.8 |
+----+------------+--------------+","[{'interval': 1, 'mean_speed': 5.7}, {'interval': 2, 'mean_speed': 4.4}, {'interval': 3, 'mean_speed': 6.1}, {'interval': 4, 'mean_speed': 5.6}, {'interval': 5, 'mean_speed': 4.1}, {'interval': 6, 'mean_speed': 4.7}, {'interval': 7, 'mean_speed': 3.9}, {'interval': 8, 'mean_speed': 3.5}, {'interval': 9, 'mean_speed': 4.2}, {'interval': 10, 'mean_speed': 4.8}]","Consider the diecutter with id 6, generate a table containing the average temperature computed over a time span of 1 minute.","from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.database import GetCamera2IdFromDiecutterId
from data_services.database import GetCurrentSessionIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
from data_services.camera2 import GetFrameFromCamera2
from data_services.camera2 import DetectErrorsInCardboardStackUsingCamera2
import threading
import time

def pipeline_function():
    diecutter_id = 14
    n_stacks = 30

    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=diecutter_id)
    camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)

    def check_error(camera2_id, frame, card_errors_res):
        has_error, error_type = DetectErrorsInCardboardStackUsingCamera2.call(camera2_id=camera2_id, frame=frame)
        card_errors_res['has_error'] = has_error
        card_errors_res['error_type'] = error_type
    
    def retrieve_diecutter_data(chip_id, diecutter_info_res):
        current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
        diecutter_info_res.update(current_data)

    results = []
    for _ in range(n_stacks):
        frame = GetFrameFromCamera2.call(camera2_id=camera2_id)
        timestamp = time.time()
        card_errors_res = {}
        card_errors = threading.Thread(target=check_error, args=(camera2_id, frame, card_errors_res))
        diecutter_info_res = {}
        diecutter_info = threading.Thread(target=retrieve_diecutter_data, args=(chip_id, diecutter_info_res))
        card_errors.start()
        diecutter_info.start()
        card_errors.join()
        diecutter_info.join()
        if card_errors_res['has_error']:
            result_row = {
                'timestamp': time.strftime(""%Y-%m-%d %H:%M:%S"", time.gmtime(timestamp)),
                'session_id': session_id,
                'error_type': card_errors_res['error_type'],
                'speed': diecutter_info_res['speed'],
                'temperature': diecutter_info_res['temperature'],
                'rotations': diecutter_info_res['rotations']
            }
            results.append(result_row)

    return results
"
q2,9,"Create a table of mean speed values for the ongoing session of diecutter 7, with each mean calculated across 10 distinct, successive 10-second intervals.","brief_description: Data service that, given the id of a camera1, provides a frame captured from that camera1. - detailed_description: Data service that, given the id of a camera1, provides a frame captured from that camera1.
        In general instances of camera1 point downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera1 (an integer) and returns a frame captured from that camera1 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera1 is 123, then the data service would be called as follows:
        camera1_id = 123
        frame = GetFrameFromCamera1.call(camera1_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int'] - output_values: ['frame:np.matrix'] - module: camera1 - class_name: GetFrameFromCamera1brief_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors and provide the type of error. - detailed_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors.
        Recall that a camera1 is a camera device that points downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera1 to use and the frame captured from that camera1.
        It returns a boolean value, True if the frame contains a cardboard with errors, False otherwise.
        Also it returns a integer value, 0 if the frame does not contain errors, 1 if the errors are of type hole and 2 if the errors are of type fold. 

        Example usage:
        - If frame is a variable containing the frame captured from the camera1 with id 123, then the data service would be called as follows:
        camera1_id = 123
        contains_errors, type_errors = DetectErrorsInCardboardUsingCamera1.call(camera1_id=123, frame=frame)

        Things to keep in mind:
        - The output is a tuple of boolean and integer, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool', 'error_type:int'] - module: camera1 - class_name: DetectErrorsInCardboardUsingCamera1brief_description: Data service that, given the id of a camera2, provides a frame captured from that camera2. - detailed_description: Data service that, given the id of a camera2, provides a frame captured from that camera2.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera2 (an integer) and returns a frame captured from that camera2 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera2 is 123, then the data service would be called as follows:
        camera2_id = 123
        frame = GetFrameFromCamera2.call(camera2_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int'] - output_values: ['frame:np.matrix'] - module: camera2 - class_name: GetFrameFromCamera2brief_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors. - detailed_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera2 to use and the frame captured from that camera2 that contains a stack of cardboards.
        It returns a boolean value, True if the frame contains a stack of cardboards with errors, False otherwise.

        Example usage:
        - If frame is a variable containing the frame captured from the camera2 with id 123, then the data service would be called as follows:
        camera2_id = 123
        contains_errors, error_type = DetectErrorsInCardboardStack.call(camera2_id=123, frame=frame)

        Things to keep in mind:
        - The output value is a boolean, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool'] - module: camera2 - class_name: DetectErrorsInCardboardStackUsingCamera2brief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera1 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera1.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera1)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera1:int'] - module: database - class_name: GetSerialCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera2 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera2.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera2)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera2:int'] - module: database - class_name: GetSerialCamera2IdFromDiecutterIdbrief_description: Data service that provides the list of id of the diecutters installed in the factory. - detailed_description: Data service that provides the id of the diecutter installed in the factory.
        The data service relies on the management database of the cardboard factory to provide the list of diecutter id.
        The data service takes no parameter and returns a list of integers, which are the id of the diecutters installed in the factory.

        Example usage:
        - The data service would be called as follows:
        diecutters_id = GetDiecuttersIdOfFactory.call()
        # assuming the diecutters id are [1, 2, 3]
        print(diecutters_id)  # [1, 2, 3]

        Things to keep in mind:
        - The diecutters id is a list of integers, so avoid trying to access it as a dictionary. - input_parameters: [] - output_values: ['diecutters_id:list'] - module: database - class_name: GetDiecuttersIdOfFactorybrief_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter.
        The data service relies on the management database of the cardboard factory to provide the chip id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the chip id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=123)
        # assuming the chip id is 456
        print(chip_id)  # 456

        Things to keep in mind:
        - The chip id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['chip_id:int'] - module: database - class_name: GetDiecutterChipIdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera1 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera1 id is 456
        print(camera1_id)  # 456

        Things to keep in mind:
        - The camera1 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera1_id:int'] - module: database - class_name: GetCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera2 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera2 id is 456
        print(camera2_id)  # 456

        Things to keep in mind:
        - The camera2 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera2_id:int'] - module: database - class_name: GetCamera2IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter.
        The data service relies on the management database of the cardboard factory to provide the session id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the current session id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=123)
        # assuming the session id is 456
        print(session_id)  # 456

        Things to keep in mind:
        - The session id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['session_id:int'] - module: database - class_name: GetCurrentSessionIdFromDiecutterIdbrief_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip. - detailed_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip.
        In general each diecutter has exactly one chip embedded into it, and each chip is uniquely identified by an integer id. 
        This means that the chip id has a one-to-one correspondence with the id of the diecutter, but those two ids may not be the same.
        This data service takes a single parameter, namely the id of the chip (an integer) and returns a single dictionary containing the current speed, temperature and number of rotations of the diecutter it is attached to.
        The keys of the dictionary are ""speed"", ""temperature"" and ""rotations"". 
        
        Example usage:
        - If the id of the chip is 123, then the data service would be called as follows:
        chip_id = 123
        current_data = GetCurrentData.call(chip_id=123)
        # get the current speed, temperature and number of rotations
        current_speed = data[""speed""]
        current_temperature = data[""temperature""]
        current_rotations = data[""rotations""]
    
        Things to keep in mind:
        - The refresh rate of the data is 1 second, i.e. the data is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - Note that the values in the dictionary represents the current values of the speed, etc. of the diecutter, they are not aggregated values.
        - Remember that the output value is a dictionary with the above specified keys, so avoid trying to access it using keys not in the above example. - input_parameters: ['chip_id:int'] - output_values: ['diecutter_current_data:dict'] - module: diecutter - class_name: GetCurrentDataFromChip","from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
import time
import threading

def pipeline_function():
    diecutter_id = 7
    interval_duration = 10  # seconds
    intervals = 10
    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)

    def collect_speed_data(interval, results):
        start_time = time.time()
        speeds = []
        while time.time() - start_time < interval:
            current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
            speeds.append(current_data['speed'])
            time.sleep(1)  # Ensure data is collected once every second
        mean_speed = sum(speeds) / len(speeds)
        results.append({'interval': interval, 'mean_speed': mean_speed})

    results = []
    threads = []
    for i in range(intervals):
        thread = threading.Thread(target=collect_speed_data, args=(interval_duration, results))
        threads.append(thread)
        thread.start()
        time.sleep(interval_duration)  # Start the next interval collection after the previous one

    for thread in threads:
        thread.join()

    return results","+----+------------+--------------+
|    |   interval |   mean_speed |
|----+------------+--------------|
|  0 |         10 |          5.7 |
|  1 |         10 |          4.4 |
|  2 |         10 |          6.1 |
|  3 |         10 |          5.6 |
|  4 |         10 |          4.1 |
|  5 |         10 |          4.7 |
|  6 |         10 |          3.9 |
|  7 |         10 |          3.5 |
|  8 |         10 |          4.2 |
|  9 |         10 |          4.8 |
+----+------------+--------------+","[{'interval': 10, 'mean_speed': 5.7}, {'interval': 10, 'mean_speed': 4.4}, {'interval': 10, 'mean_speed': 6.1}, {'interval': 10, 'mean_speed': 5.6}, {'interval': 10, 'mean_speed': 4.1}, {'interval': 10, 'mean_speed': 4.7}, {'interval': 10, 'mean_speed': 3.9}, {'interval': 10, 'mean_speed': 3.5}, {'interval': 10, 'mean_speed': 4.2}, {'interval': 10, 'mean_speed': 4.8}]","Consider the diecutter with id 6, generate a table containing the average temperature computed over a time span of 1 minute.","from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.database import GetCamera2IdFromDiecutterId
from data_services.database import GetCurrentSessionIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
from data_services.camera2 import GetFrameFromCamera2
from data_services.camera2 import DetectErrorsInCardboardStackUsingCamera2
import threading
import time

def pipeline_function():
    diecutter_id = 14
    n_stacks = 30

    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=diecutter_id)
    camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)

    def check_error(camera2_id, frame, card_errors_res):
        has_error, error_type = DetectErrorsInCardboardStackUsingCamera2.call(camera2_id=camera2_id, frame=frame)
        card_errors_res['has_error'] = has_error
        card_errors_res['error_type'] = error_type
    
    def retrieve_diecutter_data(chip_id, diecutter_info_res):
        current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
        diecutter_info_res.update(current_data)

    results = []
    for _ in range(n_stacks):
        frame = GetFrameFromCamera2.call(camera2_id=camera2_id)
        timestamp = time.time()
        card_errors_res = {}
        card_errors = threading.Thread(target=check_error, args=(camera2_id, frame, card_errors_res))
        diecutter_info_res = {}
        diecutter_info = threading.Thread(target=retrieve_diecutter_data, args=(chip_id, diecutter_info_res))
        card_errors.start()
        diecutter_info.start()
        card_errors.join()
        diecutter_info.join()
        if card_errors_res['has_error']:
            result_row = {
                'timestamp': time.strftime(""%Y-%m-%d %H:%M:%S"", time.gmtime(timestamp)),
                'session_id': session_id,
                'error_type': card_errors_res['error_type'],
                'speed': diecutter_info_res['speed'],
                'temperature': diecutter_info_res['temperature'],
                'rotations': diecutter_info_res['rotations']
            }
            results.append(result_row)

    return results
"
q3,0,Consider the next 30 cardboard of the diecutter with id 7. Generate a table containing (i) the number of cardboards with no defects and (ii) those with errors.,"brief_description: Data service that, given the id of a camera1, provides a frame captured from that camera1. - detailed_description: Data service that, given the id of a camera1, provides a frame captured from that camera1.
        In general instances of camera1 point downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera1 (an integer) and returns a frame captured from that camera1 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera1 is 123, then the data service would be called as follows:
        camera1_id = 123
        frame = GetFrameFromCamera1.call(camera1_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int'] - output_values: ['frame:np.matrix'] - module: camera1 - class_name: GetFrameFromCamera1brief_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors and provide the type of error. - detailed_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors.
        Recall that a camera1 is a camera device that points downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera1 to use and the frame captured from that camera1.
        It returns a boolean value, True if the frame contains a cardboard with errors, False otherwise.
        Also it returns a integer value, 0 if the frame does not contain errors, 1 if the errors are of type hole and 2 if the errors are of type fold. 

        Example usage:
        - If frame is a variable containing the frame captured from the camera1 with id 123, then the data service would be called as follows:
        camera1_id = 123
        contains_errors, type_errors = DetectErrorsInCardboardUsingCamera1.call(camera1_id=123, frame=frame)

        Things to keep in mind:
        - The output is a tuple of boolean and integer, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool', 'error_type:int'] - module: camera1 - class_name: DetectErrorsInCardboardUsingCamera1brief_description: Data service that, given the id of a camera2, provides a frame captured from that camera2. - detailed_description: Data service that, given the id of a camera2, provides a frame captured from that camera2.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera2 (an integer) and returns a frame captured from that camera2 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera2 is 123, then the data service would be called as follows:
        camera2_id = 123
        frame = GetFrameFromCamera2.call(camera2_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int'] - output_values: ['frame:np.matrix'] - module: camera2 - class_name: GetFrameFromCamera2brief_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors. - detailed_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera2 to use and the frame captured from that camera2 that contains a stack of cardboards.
        It returns a boolean value, True if the frame contains a stack of cardboards with errors, False otherwise.

        Example usage:
        - If frame is a variable containing the frame captured from the camera2 with id 123, then the data service would be called as follows:
        camera2_id = 123
        contains_errors, error_type = DetectErrorsInCardboardStack.call(camera2_id=123, frame=frame)

        Things to keep in mind:
        - The output value is a boolean, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool'] - module: camera2 - class_name: DetectErrorsInCardboardStackUsingCamera2brief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera1 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera1.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera1)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera1:int'] - module: database - class_name: GetSerialCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera2 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera2.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera2)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera2:int'] - module: database - class_name: GetSerialCamera2IdFromDiecutterIdbrief_description: Data service that provides the list of id of the diecutters installed in the factory. - detailed_description: Data service that provides the id of the diecutter installed in the factory.
        The data service relies on the management database of the cardboard factory to provide the list of diecutter id.
        The data service takes no parameter and returns a list of integers, which are the id of the diecutters installed in the factory.

        Example usage:
        - The data service would be called as follows:
        diecutters_id = GetDiecuttersIdOfFactory.call()
        # assuming the diecutters id are [1, 2, 3]
        print(diecutters_id)  # [1, 2, 3]

        Things to keep in mind:
        - The diecutters id is a list of integers, so avoid trying to access it as a dictionary. - input_parameters: [] - output_values: ['diecutters_id:list'] - module: database - class_name: GetDiecuttersIdOfFactorybrief_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter.
        The data service relies on the management database of the cardboard factory to provide the chip id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the chip id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=123)
        # assuming the chip id is 456
        print(chip_id)  # 456

        Things to keep in mind:
        - The chip id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['chip_id:int'] - module: database - class_name: GetDiecutterChipIdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera1 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera1 id is 456
        print(camera1_id)  # 456

        Things to keep in mind:
        - The camera1 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera1_id:int'] - module: database - class_name: GetCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera2 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera2 id is 456
        print(camera2_id)  # 456

        Things to keep in mind:
        - The camera2 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera2_id:int'] - module: database - class_name: GetCamera2IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter.
        The data service relies on the management database of the cardboard factory to provide the session id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the current session id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=123)
        # assuming the session id is 456
        print(session_id)  # 456

        Things to keep in mind:
        - The session id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['session_id:int'] - module: database - class_name: GetCurrentSessionIdFromDiecutterIdbrief_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip. - detailed_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip.
        In general each diecutter has exactly one chip embedded into it, and each chip is uniquely identified by an integer id. 
        This means that the chip id has a one-to-one correspondence with the id of the diecutter, but those two ids may not be the same.
        This data service takes a single parameter, namely the id of the chip (an integer) and returns a single dictionary containing the current speed, temperature and number of rotations of the diecutter it is attached to.
        The keys of the dictionary are ""speed"", ""temperature"" and ""rotations"". 
        
        Example usage:
        - If the id of the chip is 123, then the data service would be called as follows:
        chip_id = 123
        current_data = GetCurrentData.call(chip_id=123)
        # get the current speed, temperature and number of rotations
        current_speed = data[""speed""]
        current_temperature = data[""temperature""]
        current_rotations = data[""rotations""]
    
        Things to keep in mind:
        - The refresh rate of the data is 1 second, i.e. the data is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - Note that the values in the dictionary represents the current values of the speed, etc. of the diecutter, they are not aggregated values.
        - Remember that the output value is a dictionary with the above specified keys, so avoid trying to access it using keys not in the above example. - input_parameters: ['chip_id:int'] - output_values: ['diecutter_current_data:dict'] - module: diecutter - class_name: GetCurrentDataFromChip","from data_services.database import GetCamera1IdFromDiecutterId
from data_services.camera1 import GetFrameFromCamera1, DetectErrorsInCardboardUsingCamera1
import time

def pipeline_function():
    diecutter_id = 7
    num_cardboards = 30
    results = []

    # Get the camera1 ID associated with the diecutter
    camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=diecutter_id)

    # Initialize counters
    count_no_defects = 0
    count_with_errors = 0

    # Process each cardboard
    for _ in range(num_cardboards):
        # Get a frame from the camera
        frame = GetFrameFromCamera1.call(camera1_id=camera1_id)
        
        # Detect errors in the cardboard
        contains_errors, error_type = DetectErrorsInCardboardUsingCamera1.call(camera1_id=camera1_id, frame=frame)
        
        # Update counters based on the presence of errors
        if contains_errors:
            count_with_errors += 1
        else:
            count_no_defects += 1
        
        # Wait for the next frame (since the camera refresh rate is 1 second)
        time.sleep(1)

    # Append the results
    results.append({
        'number_of_cardboards_with_no_defects': count_no_defects,
        'number_of_cardboards_with_errors': count_with_errors
    })

    return results","+----+----------------------------------------+------------------------------------+
|    |   number_of_cardboards_with_no_defects |   number_of_cardboards_with_errors |
|----+----------------------------------------+------------------------------------|
|  0 |                                     17 |                                 13 |
+----+----------------------------------------+------------------------------------+","[{'number_of_cardboards_with_no_defects': 17, 'number_of_cardboards_with_errors': 13}]","Consider the next 5 carboard of the first diecutter. Generate a table containing: (i) the number of cardboards with no defects, (ii) those with errors, (iii) how many fold errors, and (iv) how many hole errors.","from data_services.database import GetSerialCamera1IdFromDiecutterId
from data_services.database import GetSerialCamera2IdFromDiecutterId
from data_services.database import GetDiecuttersIdOfFactory

def pipeline_function():
    serial_number = 88888404

    results = []

    diecutters_ids = GetDiecuttersIdOfFactory.call()
    for diecutter_id in diecutters_ids:
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=diecutter_id)
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)
        if serial_camera1 == serial_number:
            camera_type = ""camera1""
            results.append({
                'serial number': serial_number,
                'diecutter_id': diecutter_id,
                'type': camera_type
            })
            break
        elif serial_camera2 == serial_number:
            camera_type = ""camera2""
            results.append({
                'serial number': serial_number,
                'diecutter_id': diecutter_id,
                'type': camera_type
            })
            break
    
    return results"
q3,1,"For the upcoming 30 cardboards processed by diecutter with id 7, compile a table listing (i) the count of defect-free cardboards and (ii) the count of cardboards containing defects.","brief_description: Data service that, given the id of a camera1, provides a frame captured from that camera1. - detailed_description: Data service that, given the id of a camera1, provides a frame captured from that camera1.
        In general instances of camera1 point downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera1 (an integer) and returns a frame captured from that camera1 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera1 is 123, then the data service would be called as follows:
        camera1_id = 123
        frame = GetFrameFromCamera1.call(camera1_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int'] - output_values: ['frame:np.matrix'] - module: camera1 - class_name: GetFrameFromCamera1brief_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors and provide the type of error. - detailed_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors.
        Recall that a camera1 is a camera device that points downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera1 to use and the frame captured from that camera1.
        It returns a boolean value, True if the frame contains a cardboard with errors, False otherwise.
        Also it returns a integer value, 0 if the frame does not contain errors, 1 if the errors are of type hole and 2 if the errors are of type fold. 

        Example usage:
        - If frame is a variable containing the frame captured from the camera1 with id 123, then the data service would be called as follows:
        camera1_id = 123
        contains_errors, type_errors = DetectErrorsInCardboardUsingCamera1.call(camera1_id=123, frame=frame)

        Things to keep in mind:
        - The output is a tuple of boolean and integer, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool', 'error_type:int'] - module: camera1 - class_name: DetectErrorsInCardboardUsingCamera1brief_description: Data service that, given the id of a camera2, provides a frame captured from that camera2. - detailed_description: Data service that, given the id of a camera2, provides a frame captured from that camera2.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera2 (an integer) and returns a frame captured from that camera2 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera2 is 123, then the data service would be called as follows:
        camera2_id = 123
        frame = GetFrameFromCamera2.call(camera2_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int'] - output_values: ['frame:np.matrix'] - module: camera2 - class_name: GetFrameFromCamera2brief_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors. - detailed_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera2 to use and the frame captured from that camera2 that contains a stack of cardboards.
        It returns a boolean value, True if the frame contains a stack of cardboards with errors, False otherwise.

        Example usage:
        - If frame is a variable containing the frame captured from the camera2 with id 123, then the data service would be called as follows:
        camera2_id = 123
        contains_errors, error_type = DetectErrorsInCardboardStack.call(camera2_id=123, frame=frame)

        Things to keep in mind:
        - The output value is a boolean, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool'] - module: camera2 - class_name: DetectErrorsInCardboardStackUsingCamera2brief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera1 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera1.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera1)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera1:int'] - module: database - class_name: GetSerialCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera2 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera2.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera2)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera2:int'] - module: database - class_name: GetSerialCamera2IdFromDiecutterIdbrief_description: Data service that provides the list of id of the diecutters installed in the factory. - detailed_description: Data service that provides the id of the diecutter installed in the factory.
        The data service relies on the management database of the cardboard factory to provide the list of diecutter id.
        The data service takes no parameter and returns a list of integers, which are the id of the diecutters installed in the factory.

        Example usage:
        - The data service would be called as follows:
        diecutters_id = GetDiecuttersIdOfFactory.call()
        # assuming the diecutters id are [1, 2, 3]
        print(diecutters_id)  # [1, 2, 3]

        Things to keep in mind:
        - The diecutters id is a list of integers, so avoid trying to access it as a dictionary. - input_parameters: [] - output_values: ['diecutters_id:list'] - module: database - class_name: GetDiecuttersIdOfFactorybrief_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter.
        The data service relies on the management database of the cardboard factory to provide the chip id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the chip id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=123)
        # assuming the chip id is 456
        print(chip_id)  # 456

        Things to keep in mind:
        - The chip id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['chip_id:int'] - module: database - class_name: GetDiecutterChipIdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera1 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera1 id is 456
        print(camera1_id)  # 456

        Things to keep in mind:
        - The camera1 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera1_id:int'] - module: database - class_name: GetCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera2 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera2 id is 456
        print(camera2_id)  # 456

        Things to keep in mind:
        - The camera2 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera2_id:int'] - module: database - class_name: GetCamera2IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter.
        The data service relies on the management database of the cardboard factory to provide the session id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the current session id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=123)
        # assuming the session id is 456
        print(session_id)  # 456

        Things to keep in mind:
        - The session id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['session_id:int'] - module: database - class_name: GetCurrentSessionIdFromDiecutterIdbrief_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip. - detailed_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip.
        In general each diecutter has exactly one chip embedded into it, and each chip is uniquely identified by an integer id. 
        This means that the chip id has a one-to-one correspondence with the id of the diecutter, but those two ids may not be the same.
        This data service takes a single parameter, namely the id of the chip (an integer) and returns a single dictionary containing the current speed, temperature and number of rotations of the diecutter it is attached to.
        The keys of the dictionary are ""speed"", ""temperature"" and ""rotations"". 
        
        Example usage:
        - If the id of the chip is 123, then the data service would be called as follows:
        chip_id = 123
        current_data = GetCurrentData.call(chip_id=123)
        # get the current speed, temperature and number of rotations
        current_speed = data[""speed""]
        current_temperature = data[""temperature""]
        current_rotations = data[""rotations""]
    
        Things to keep in mind:
        - The refresh rate of the data is 1 second, i.e. the data is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - Note that the values in the dictionary represents the current values of the speed, etc. of the diecutter, they are not aggregated values.
        - Remember that the output value is a dictionary with the above specified keys, so avoid trying to access it using keys not in the above example. - input_parameters: ['chip_id:int'] - output_values: ['diecutter_current_data:dict'] - module: diecutter - class_name: GetCurrentDataFromChip","from data_services.database import GetCamera1IdFromDiecutterId
from data_services.camera1 import GetFrameFromCamera1, DetectErrorsInCardboardUsingCamera1
import time

def pipeline_function():
    diecutter_id = 7
    num_cardboards = 30
    defect_free_count = 0
    defect_count = 0

    # Get the camera1 ID associated with the diecutter
    camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=diecutter_id)

    for _ in range(num_cardboards):
        # Capture a frame from the camera
        frame = GetFrameFromCamera1.call(camera1_id=camera1_id)
        
        # Detect errors in the captured frame
        contains_errors, error_type = DetectErrorsInCardboardUsingCamera1.call(camera1_id=camera1_id, frame=frame)
        
        if contains_errors:
            defect_count += 1
        else:
            defect_free_count += 1
        
        # Wait for 1 second to get the next frame
        time.sleep(1)

    results = [{
        'defect_free_count': defect_free_count,
        'defect_count': defect_count
    }]

    return results","+----+---------------------+----------------+
|    |   defect_free_count |   defect_count |
|----+---------------------+----------------|
|  0 |                  17 |             13 |
+----+---------------------+----------------+","[{'defect_free_count': 17, 'defect_count': 13}]","Consider the next 5 carboard of the first diecutter. Generate a table containing: (i) the number of cardboards with no defects, (ii) those with errors, (iii) how many fold errors, and (iv) how many hole errors.","from data_services.database import GetSerialCamera1IdFromDiecutterId
from data_services.database import GetSerialCamera2IdFromDiecutterId
from data_services.database import GetDiecuttersIdOfFactory

def pipeline_function():
    serial_number = 88888404

    results = []

    diecutters_ids = GetDiecuttersIdOfFactory.call()
    for diecutter_id in diecutters_ids:
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=diecutter_id)
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)
        if serial_camera1 == serial_number:
            camera_type = ""camera1""
            results.append({
                'serial number': serial_number,
                'diecutter_id': diecutter_id,
                'type': camera_type
            })
            break
        elif serial_camera2 == serial_number:
            camera_type = ""camera2""
            results.append({
                'serial number': serial_number,
                'diecutter_id': diecutter_id,
                'type': camera_type
            })
            break
    
    return results"
q3,2,Consider the upcoming 30 cardboard processed by diecutter with id 7. Construct a table displaying (i) the count of defect-free cardboards and (ii) the count of cardboards with defects.,"brief_description: Data service that, given the id of a camera1, provides a frame captured from that camera1. - detailed_description: Data service that, given the id of a camera1, provides a frame captured from that camera1.
        In general instances of camera1 point downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera1 (an integer) and returns a frame captured from that camera1 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera1 is 123, then the data service would be called as follows:
        camera1_id = 123
        frame = GetFrameFromCamera1.call(camera1_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int'] - output_values: ['frame:np.matrix'] - module: camera1 - class_name: GetFrameFromCamera1brief_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors and provide the type of error. - detailed_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors.
        Recall that a camera1 is a camera device that points downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera1 to use and the frame captured from that camera1.
        It returns a boolean value, True if the frame contains a cardboard with errors, False otherwise.
        Also it returns a integer value, 0 if the frame does not contain errors, 1 if the errors are of type hole and 2 if the errors are of type fold. 

        Example usage:
        - If frame is a variable containing the frame captured from the camera1 with id 123, then the data service would be called as follows:
        camera1_id = 123
        contains_errors, type_errors = DetectErrorsInCardboardUsingCamera1.call(camera1_id=123, frame=frame)

        Things to keep in mind:
        - The output is a tuple of boolean and integer, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool', 'error_type:int'] - module: camera1 - class_name: DetectErrorsInCardboardUsingCamera1brief_description: Data service that, given the id of a camera2, provides a frame captured from that camera2. - detailed_description: Data service that, given the id of a camera2, provides a frame captured from that camera2.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera2 (an integer) and returns a frame captured from that camera2 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera2 is 123, then the data service would be called as follows:
        camera2_id = 123
        frame = GetFrameFromCamera2.call(camera2_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int'] - output_values: ['frame:np.matrix'] - module: camera2 - class_name: GetFrameFromCamera2brief_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors. - detailed_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera2 to use and the frame captured from that camera2 that contains a stack of cardboards.
        It returns a boolean value, True if the frame contains a stack of cardboards with errors, False otherwise.

        Example usage:
        - If frame is a variable containing the frame captured from the camera2 with id 123, then the data service would be called as follows:
        camera2_id = 123
        contains_errors, error_type = DetectErrorsInCardboardStack.call(camera2_id=123, frame=frame)

        Things to keep in mind:
        - The output value is a boolean, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool'] - module: camera2 - class_name: DetectErrorsInCardboardStackUsingCamera2brief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera1 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera1.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera1)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera1:int'] - module: database - class_name: GetSerialCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera2 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera2.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera2)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera2:int'] - module: database - class_name: GetSerialCamera2IdFromDiecutterIdbrief_description: Data service that provides the list of id of the diecutters installed in the factory. - detailed_description: Data service that provides the id of the diecutter installed in the factory.
        The data service relies on the management database of the cardboard factory to provide the list of diecutter id.
        The data service takes no parameter and returns a list of integers, which are the id of the diecutters installed in the factory.

        Example usage:
        - The data service would be called as follows:
        diecutters_id = GetDiecuttersIdOfFactory.call()
        # assuming the diecutters id are [1, 2, 3]
        print(diecutters_id)  # [1, 2, 3]

        Things to keep in mind:
        - The diecutters id is a list of integers, so avoid trying to access it as a dictionary. - input_parameters: [] - output_values: ['diecutters_id:list'] - module: database - class_name: GetDiecuttersIdOfFactorybrief_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter.
        The data service relies on the management database of the cardboard factory to provide the chip id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the chip id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=123)
        # assuming the chip id is 456
        print(chip_id)  # 456

        Things to keep in mind:
        - The chip id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['chip_id:int'] - module: database - class_name: GetDiecutterChipIdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera1 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera1 id is 456
        print(camera1_id)  # 456

        Things to keep in mind:
        - The camera1 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera1_id:int'] - module: database - class_name: GetCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera2 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera2 id is 456
        print(camera2_id)  # 456

        Things to keep in mind:
        - The camera2 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera2_id:int'] - module: database - class_name: GetCamera2IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter.
        The data service relies on the management database of the cardboard factory to provide the session id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the current session id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=123)
        # assuming the session id is 456
        print(session_id)  # 456

        Things to keep in mind:
        - The session id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['session_id:int'] - module: database - class_name: GetCurrentSessionIdFromDiecutterIdbrief_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip. - detailed_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip.
        In general each diecutter has exactly one chip embedded into it, and each chip is uniquely identified by an integer id. 
        This means that the chip id has a one-to-one correspondence with the id of the diecutter, but those two ids may not be the same.
        This data service takes a single parameter, namely the id of the chip (an integer) and returns a single dictionary containing the current speed, temperature and number of rotations of the diecutter it is attached to.
        The keys of the dictionary are ""speed"", ""temperature"" and ""rotations"". 
        
        Example usage:
        - If the id of the chip is 123, then the data service would be called as follows:
        chip_id = 123
        current_data = GetCurrentData.call(chip_id=123)
        # get the current speed, temperature and number of rotations
        current_speed = data[""speed""]
        current_temperature = data[""temperature""]
        current_rotations = data[""rotations""]
    
        Things to keep in mind:
        - The refresh rate of the data is 1 second, i.e. the data is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - Note that the values in the dictionary represents the current values of the speed, etc. of the diecutter, they are not aggregated values.
        - Remember that the output value is a dictionary with the above specified keys, so avoid trying to access it using keys not in the above example. - input_parameters: ['chip_id:int'] - output_values: ['diecutter_current_data:dict'] - module: diecutter - class_name: GetCurrentDataFromChip","from data_services.database import GetCamera1IdFromDiecutterId
from data_services.camera1 import GetFrameFromCamera1, DetectErrorsInCardboardUsingCamera1
import time

def pipeline_function():
    diecutter_id = 7
    camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=diecutter_id)
    
    defect_free_count = 0
    defects_count = 0
    
    for _ in range(30):
        frame = GetFrameFromCamera1.call(camera1_id=camera1_id)
        contains_errors, error_type = DetectErrorsInCardboardUsingCamera1.call(camera1_id=camera1_id, frame=frame)
        
        if not contains_errors:
            defect_free_count += 1
        else:
            defects_count += 1
        
        time.sleep(1)  # Wait for the next frame to be different

    results = [{
        'defect_free_count': defect_free_count,
        'defects_count': defects_count
    }]
    
    return results","+----+---------------------+-----------------+
|    |   defect_free_count |   defects_count |
|----+---------------------+-----------------|
|  0 |                  17 |              13 |
+----+---------------------+-----------------+","[{'defect_free_count': 17, 'defects_count': 13}]","Consider the next 5 carboard of the first diecutter. Generate a table containing: (i) the number of cardboards with no defects, (ii) those with errors, (iii) how many fold errors, and (iv) how many hole errors.","from data_services.database import GetSerialCamera1IdFromDiecutterId
from data_services.database import GetSerialCamera2IdFromDiecutterId
from data_services.database import GetDiecuttersIdOfFactory

def pipeline_function():
    serial_number = 88888404

    results = []

    diecutters_ids = GetDiecuttersIdOfFactory.call()
    for diecutter_id in diecutters_ids:
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=diecutter_id)
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)
        if serial_camera1 == serial_number:
            camera_type = ""camera1""
            results.append({
                'serial number': serial_number,
                'diecutter_id': diecutter_id,
                'type': camera_type
            })
            break
        elif serial_camera2 == serial_number:
            camera_type = ""camera2""
            results.append({
                'serial number': serial_number,
                'diecutter_id': diecutter_id,
                'type': camera_type
            })
            break
    
    return results"
q3,3,"For the upcoming 30 cardboards processed by the diecutter with id 7, produce a table listing (i) the count of defect-free cardboards and (ii) the count of defective cardboards.","brief_description: Data service that, given the id of a camera1, provides a frame captured from that camera1. - detailed_description: Data service that, given the id of a camera1, provides a frame captured from that camera1.
        In general instances of camera1 point downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera1 (an integer) and returns a frame captured from that camera1 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera1 is 123, then the data service would be called as follows:
        camera1_id = 123
        frame = GetFrameFromCamera1.call(camera1_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int'] - output_values: ['frame:np.matrix'] - module: camera1 - class_name: GetFrameFromCamera1brief_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors and provide the type of error. - detailed_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors.
        Recall that a camera1 is a camera device that points downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera1 to use and the frame captured from that camera1.
        It returns a boolean value, True if the frame contains a cardboard with errors, False otherwise.
        Also it returns a integer value, 0 if the frame does not contain errors, 1 if the errors are of type hole and 2 if the errors are of type fold. 

        Example usage:
        - If frame is a variable containing the frame captured from the camera1 with id 123, then the data service would be called as follows:
        camera1_id = 123
        contains_errors, type_errors = DetectErrorsInCardboardUsingCamera1.call(camera1_id=123, frame=frame)

        Things to keep in mind:
        - The output is a tuple of boolean and integer, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool', 'error_type:int'] - module: camera1 - class_name: DetectErrorsInCardboardUsingCamera1brief_description: Data service that, given the id of a camera2, provides a frame captured from that camera2. - detailed_description: Data service that, given the id of a camera2, provides a frame captured from that camera2.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera2 (an integer) and returns a frame captured from that camera2 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera2 is 123, then the data service would be called as follows:
        camera2_id = 123
        frame = GetFrameFromCamera2.call(camera2_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int'] - output_values: ['frame:np.matrix'] - module: camera2 - class_name: GetFrameFromCamera2brief_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors. - detailed_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera2 to use and the frame captured from that camera2 that contains a stack of cardboards.
        It returns a boolean value, True if the frame contains a stack of cardboards with errors, False otherwise.

        Example usage:
        - If frame is a variable containing the frame captured from the camera2 with id 123, then the data service would be called as follows:
        camera2_id = 123
        contains_errors, error_type = DetectErrorsInCardboardStack.call(camera2_id=123, frame=frame)

        Things to keep in mind:
        - The output value is a boolean, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool'] - module: camera2 - class_name: DetectErrorsInCardboardStackUsingCamera2brief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera1 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera1.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera1)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera1:int'] - module: database - class_name: GetSerialCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera2 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera2.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera2)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera2:int'] - module: database - class_name: GetSerialCamera2IdFromDiecutterIdbrief_description: Data service that provides the list of id of the diecutters installed in the factory. - detailed_description: Data service that provides the id of the diecutter installed in the factory.
        The data service relies on the management database of the cardboard factory to provide the list of diecutter id.
        The data service takes no parameter and returns a list of integers, which are the id of the diecutters installed in the factory.

        Example usage:
        - The data service would be called as follows:
        diecutters_id = GetDiecuttersIdOfFactory.call()
        # assuming the diecutters id are [1, 2, 3]
        print(diecutters_id)  # [1, 2, 3]

        Things to keep in mind:
        - The diecutters id is a list of integers, so avoid trying to access it as a dictionary. - input_parameters: [] - output_values: ['diecutters_id:list'] - module: database - class_name: GetDiecuttersIdOfFactorybrief_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter.
        The data service relies on the management database of the cardboard factory to provide the chip id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the chip id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=123)
        # assuming the chip id is 456
        print(chip_id)  # 456

        Things to keep in mind:
        - The chip id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['chip_id:int'] - module: database - class_name: GetDiecutterChipIdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera1 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera1 id is 456
        print(camera1_id)  # 456

        Things to keep in mind:
        - The camera1 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera1_id:int'] - module: database - class_name: GetCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera2 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera2 id is 456
        print(camera2_id)  # 456

        Things to keep in mind:
        - The camera2 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera2_id:int'] - module: database - class_name: GetCamera2IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter.
        The data service relies on the management database of the cardboard factory to provide the session id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the current session id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=123)
        # assuming the session id is 456
        print(session_id)  # 456

        Things to keep in mind:
        - The session id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['session_id:int'] - module: database - class_name: GetCurrentSessionIdFromDiecutterIdbrief_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip. - detailed_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip.
        In general each diecutter has exactly one chip embedded into it, and each chip is uniquely identified by an integer id. 
        This means that the chip id has a one-to-one correspondence with the id of the diecutter, but those two ids may not be the same.
        This data service takes a single parameter, namely the id of the chip (an integer) and returns a single dictionary containing the current speed, temperature and number of rotations of the diecutter it is attached to.
        The keys of the dictionary are ""speed"", ""temperature"" and ""rotations"". 
        
        Example usage:
        - If the id of the chip is 123, then the data service would be called as follows:
        chip_id = 123
        current_data = GetCurrentData.call(chip_id=123)
        # get the current speed, temperature and number of rotations
        current_speed = data[""speed""]
        current_temperature = data[""temperature""]
        current_rotations = data[""rotations""]
    
        Things to keep in mind:
        - The refresh rate of the data is 1 second, i.e. the data is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - Note that the values in the dictionary represents the current values of the speed, etc. of the diecutter, they are not aggregated values.
        - Remember that the output value is a dictionary with the above specified keys, so avoid trying to access it using keys not in the above example. - input_parameters: ['chip_id:int'] - output_values: ['diecutter_current_data:dict'] - module: diecutter - class_name: GetCurrentDataFromChip","from data_services.database import GetCamera1IdFromDiecutterId
from data_services.camera1 import GetFrameFromCamera1, DetectErrorsInCardboardUsingCamera1
import time

def pipeline_function():
    diecutter_id = 7
    num_cardboards = 30
    defect_free_count = 0
    defective_count = 0

    # Get the camera1 ID associated with the diecutter
    camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=diecutter_id)

    # Process the specified number of cardboards
    for _ in range(num_cardboards):
        # Capture a frame from the camera
        frame = GetFrameFromCamera1.call(camera1_id=camera1_id)
        
        # Detect errors in the captured cardboard
        contains_errors, error_type = DetectErrorsInCardboardUsingCamera1.call(camera1_id=camera1_id, frame=frame)
        
        # Count defect-free and defective cardboards
        if contains_errors:
            defective_count += 1
        else:
            defect_free_count += 1
        
        # Wait for the next frame (since the camera refresh rate is 1 second)
        time.sleep(1)

    # Prepare the result
    results = [{
        'defect_free_count': defect_free_count,
        'defective_count': defective_count
    }]

    return results","+----+---------------------+-------------------+
|    |   defect_free_count |   defective_count |
|----+---------------------+-------------------|
|  0 |                  17 |                13 |
+----+---------------------+-------------------+","[{'defect_free_count': 17, 'defective_count': 13}]","Consider the next 5 carboard of the first diecutter. Generate a table containing: (i) the number of cardboards with no defects, (ii) those with errors, (iii) how many fold errors, and (iv) how many hole errors.","from data_services.database import GetSerialCamera1IdFromDiecutterId
from data_services.database import GetSerialCamera2IdFromDiecutterId
from data_services.database import GetDiecuttersIdOfFactory

def pipeline_function():
    serial_number = 88888404

    results = []

    diecutters_ids = GetDiecuttersIdOfFactory.call()
    for diecutter_id in diecutters_ids:
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=diecutter_id)
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)
        if serial_camera1 == serial_number:
            camera_type = ""camera1""
            results.append({
                'serial number': serial_number,
                'diecutter_id': diecutter_id,
                'type': camera_type
            })
            break
        elif serial_camera2 == serial_number:
            camera_type = ""camera2""
            results.append({
                'serial number': serial_number,
                'diecutter_id': diecutter_id,
                'type': camera_type
            })
            break
    
    return results"
q3,4,Assess the upcoming 30 cardboards processed by diecutter id 7. Create a table displaying (i) the count of defect-free cardboards and (ii) the count of cardboards with defects.,"brief_description: Data service that, given the id of a camera1, provides a frame captured from that camera1. - detailed_description: Data service that, given the id of a camera1, provides a frame captured from that camera1.
        In general instances of camera1 point downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera1 (an integer) and returns a frame captured from that camera1 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera1 is 123, then the data service would be called as follows:
        camera1_id = 123
        frame = GetFrameFromCamera1.call(camera1_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int'] - output_values: ['frame:np.matrix'] - module: camera1 - class_name: GetFrameFromCamera1brief_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors and provide the type of error. - detailed_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors.
        Recall that a camera1 is a camera device that points downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera1 to use and the frame captured from that camera1.
        It returns a boolean value, True if the frame contains a cardboard with errors, False otherwise.
        Also it returns a integer value, 0 if the frame does not contain errors, 1 if the errors are of type hole and 2 if the errors are of type fold. 

        Example usage:
        - If frame is a variable containing the frame captured from the camera1 with id 123, then the data service would be called as follows:
        camera1_id = 123
        contains_errors, type_errors = DetectErrorsInCardboardUsingCamera1.call(camera1_id=123, frame=frame)

        Things to keep in mind:
        - The output is a tuple of boolean and integer, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool', 'error_type:int'] - module: camera1 - class_name: DetectErrorsInCardboardUsingCamera1brief_description: Data service that, given the id of a camera2, provides a frame captured from that camera2. - detailed_description: Data service that, given the id of a camera2, provides a frame captured from that camera2.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera2 (an integer) and returns a frame captured from that camera2 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera2 is 123, then the data service would be called as follows:
        camera2_id = 123
        frame = GetFrameFromCamera2.call(camera2_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int'] - output_values: ['frame:np.matrix'] - module: camera2 - class_name: GetFrameFromCamera2brief_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors. - detailed_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera2 to use and the frame captured from that camera2 that contains a stack of cardboards.
        It returns a boolean value, True if the frame contains a stack of cardboards with errors, False otherwise.

        Example usage:
        - If frame is a variable containing the frame captured from the camera2 with id 123, then the data service would be called as follows:
        camera2_id = 123
        contains_errors, error_type = DetectErrorsInCardboardStack.call(camera2_id=123, frame=frame)

        Things to keep in mind:
        - The output value is a boolean, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool'] - module: camera2 - class_name: DetectErrorsInCardboardStackUsingCamera2brief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera1 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera1.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera1)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera1:int'] - module: database - class_name: GetSerialCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera2 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera2.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera2)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera2:int'] - module: database - class_name: GetSerialCamera2IdFromDiecutterIdbrief_description: Data service that provides the list of id of the diecutters installed in the factory. - detailed_description: Data service that provides the id of the diecutter installed in the factory.
        The data service relies on the management database of the cardboard factory to provide the list of diecutter id.
        The data service takes no parameter and returns a list of integers, which are the id of the diecutters installed in the factory.

        Example usage:
        - The data service would be called as follows:
        diecutters_id = GetDiecuttersIdOfFactory.call()
        # assuming the diecutters id are [1, 2, 3]
        print(diecutters_id)  # [1, 2, 3]

        Things to keep in mind:
        - The diecutters id is a list of integers, so avoid trying to access it as a dictionary. - input_parameters: [] - output_values: ['diecutters_id:list'] - module: database - class_name: GetDiecuttersIdOfFactorybrief_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter.
        The data service relies on the management database of the cardboard factory to provide the chip id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the chip id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=123)
        # assuming the chip id is 456
        print(chip_id)  # 456

        Things to keep in mind:
        - The chip id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['chip_id:int'] - module: database - class_name: GetDiecutterChipIdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera1 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera1 id is 456
        print(camera1_id)  # 456

        Things to keep in mind:
        - The camera1 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera1_id:int'] - module: database - class_name: GetCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera2 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera2 id is 456
        print(camera2_id)  # 456

        Things to keep in mind:
        - The camera2 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera2_id:int'] - module: database - class_name: GetCamera2IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter.
        The data service relies on the management database of the cardboard factory to provide the session id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the current session id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=123)
        # assuming the session id is 456
        print(session_id)  # 456

        Things to keep in mind:
        - The session id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['session_id:int'] - module: database - class_name: GetCurrentSessionIdFromDiecutterIdbrief_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip. - detailed_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip.
        In general each diecutter has exactly one chip embedded into it, and each chip is uniquely identified by an integer id. 
        This means that the chip id has a one-to-one correspondence with the id of the diecutter, but those two ids may not be the same.
        This data service takes a single parameter, namely the id of the chip (an integer) and returns a single dictionary containing the current speed, temperature and number of rotations of the diecutter it is attached to.
        The keys of the dictionary are ""speed"", ""temperature"" and ""rotations"". 
        
        Example usage:
        - If the id of the chip is 123, then the data service would be called as follows:
        chip_id = 123
        current_data = GetCurrentData.call(chip_id=123)
        # get the current speed, temperature and number of rotations
        current_speed = data[""speed""]
        current_temperature = data[""temperature""]
        current_rotations = data[""rotations""]
    
        Things to keep in mind:
        - The refresh rate of the data is 1 second, i.e. the data is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - Note that the values in the dictionary represents the current values of the speed, etc. of the diecutter, they are not aggregated values.
        - Remember that the output value is a dictionary with the above specified keys, so avoid trying to access it using keys not in the above example. - input_parameters: ['chip_id:int'] - output_values: ['diecutter_current_data:dict'] - module: diecutter - class_name: GetCurrentDataFromChip","from data_services.database import GetCamera1IdFromDiecutterId
from data_services.camera1 import GetFrameFromCamera1, DetectErrorsInCardboardUsingCamera1
import time

def pipeline_function():
    diecutter_id = 7
    camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=diecutter_id)
    
    defect_free_count = 0
    defect_count = 0
    
    for _ in range(30):
        frame = GetFrameFromCamera1.call(camera1_id=camera1_id)
        contains_errors, _ = DetectErrorsInCardboardUsingCamera1.call(camera1_id=camera1_id, frame=frame)
        
        if contains_errors:
            defect_count += 1
        else:
            defect_free_count += 1
        
        time.sleep(1)  # Ensure we get a new frame in the next iteration
    
    results = [{
        'count_defect_free_cardboards': defect_free_count,
        'count_cardboards_with_defects': defect_count
    }]
    
    return results","+----+--------------------------------+---------------------------------+
|    |   count_defect_free_cardboards |   count_cardboards_with_defects |
|----+--------------------------------+---------------------------------|
|  0 |                             17 |                              13 |
+----+--------------------------------+---------------------------------+","[{'count_defect_free_cardboards': 17, 'count_cardboards_with_defects': 13}]","Consider the next 5 carboard of the first diecutter. Generate a table containing: (i) the number of cardboards with no defects, (ii) those with errors, (iii) how many fold errors, and (iv) how many hole errors.","from data_services.database import GetSerialCamera1IdFromDiecutterId
from data_services.database import GetSerialCamera2IdFromDiecutterId
from data_services.database import GetDiecuttersIdOfFactory

def pipeline_function():
    serial_number = 88888404

    results = []

    diecutters_ids = GetDiecuttersIdOfFactory.call()
    for diecutter_id in diecutters_ids:
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=diecutter_id)
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)
        if serial_camera1 == serial_number:
            camera_type = ""camera1""
            results.append({
                'serial number': serial_number,
                'diecutter_id': diecutter_id,
                'type': camera_type
            })
            break
        elif serial_camera2 == serial_number:
            camera_type = ""camera2""
            results.append({
                'serial number': serial_number,
                'diecutter_id': diecutter_id,
                'type': camera_type
            })
            break
    
    return results"
q3,5,Examine the upcoming 30 units of cardboard processed by the diecutter assigned id 7. Construct a table detailing (i) the count of defect-free cardboards and (ii) the number exhibiting defects.,"brief_description: Data service that, given the id of a camera1, provides a frame captured from that camera1. - detailed_description: Data service that, given the id of a camera1, provides a frame captured from that camera1.
        In general instances of camera1 point downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera1 (an integer) and returns a frame captured from that camera1 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera1 is 123, then the data service would be called as follows:
        camera1_id = 123
        frame = GetFrameFromCamera1.call(camera1_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int'] - output_values: ['frame:np.matrix'] - module: camera1 - class_name: GetFrameFromCamera1brief_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors and provide the type of error. - detailed_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors.
        Recall that a camera1 is a camera device that points downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera1 to use and the frame captured from that camera1.
        It returns a boolean value, True if the frame contains a cardboard with errors, False otherwise.
        Also it returns a integer value, 0 if the frame does not contain errors, 1 if the errors are of type hole and 2 if the errors are of type fold. 

        Example usage:
        - If frame is a variable containing the frame captured from the camera1 with id 123, then the data service would be called as follows:
        camera1_id = 123
        contains_errors, type_errors = DetectErrorsInCardboardUsingCamera1.call(camera1_id=123, frame=frame)

        Things to keep in mind:
        - The output is a tuple of boolean and integer, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool', 'error_type:int'] - module: camera1 - class_name: DetectErrorsInCardboardUsingCamera1brief_description: Data service that, given the id of a camera2, provides a frame captured from that camera2. - detailed_description: Data service that, given the id of a camera2, provides a frame captured from that camera2.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera2 (an integer) and returns a frame captured from that camera2 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera2 is 123, then the data service would be called as follows:
        camera2_id = 123
        frame = GetFrameFromCamera2.call(camera2_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int'] - output_values: ['frame:np.matrix'] - module: camera2 - class_name: GetFrameFromCamera2brief_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors. - detailed_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera2 to use and the frame captured from that camera2 that contains a stack of cardboards.
        It returns a boolean value, True if the frame contains a stack of cardboards with errors, False otherwise.

        Example usage:
        - If frame is a variable containing the frame captured from the camera2 with id 123, then the data service would be called as follows:
        camera2_id = 123
        contains_errors, error_type = DetectErrorsInCardboardStack.call(camera2_id=123, frame=frame)

        Things to keep in mind:
        - The output value is a boolean, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool'] - module: camera2 - class_name: DetectErrorsInCardboardStackUsingCamera2brief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera1 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera1.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera1)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera1:int'] - module: database - class_name: GetSerialCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera2 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera2.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera2)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera2:int'] - module: database - class_name: GetSerialCamera2IdFromDiecutterIdbrief_description: Data service that provides the list of id of the diecutters installed in the factory. - detailed_description: Data service that provides the id of the diecutter installed in the factory.
        The data service relies on the management database of the cardboard factory to provide the list of diecutter id.
        The data service takes no parameter and returns a list of integers, which are the id of the diecutters installed in the factory.

        Example usage:
        - The data service would be called as follows:
        diecutters_id = GetDiecuttersIdOfFactory.call()
        # assuming the diecutters id are [1, 2, 3]
        print(diecutters_id)  # [1, 2, 3]

        Things to keep in mind:
        - The diecutters id is a list of integers, so avoid trying to access it as a dictionary. - input_parameters: [] - output_values: ['diecutters_id:list'] - module: database - class_name: GetDiecuttersIdOfFactorybrief_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter.
        The data service relies on the management database of the cardboard factory to provide the chip id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the chip id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=123)
        # assuming the chip id is 456
        print(chip_id)  # 456

        Things to keep in mind:
        - The chip id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['chip_id:int'] - module: database - class_name: GetDiecutterChipIdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera1 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera1 id is 456
        print(camera1_id)  # 456

        Things to keep in mind:
        - The camera1 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera1_id:int'] - module: database - class_name: GetCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera2 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera2 id is 456
        print(camera2_id)  # 456

        Things to keep in mind:
        - The camera2 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera2_id:int'] - module: database - class_name: GetCamera2IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter.
        The data service relies on the management database of the cardboard factory to provide the session id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the current session id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=123)
        # assuming the session id is 456
        print(session_id)  # 456

        Things to keep in mind:
        - The session id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['session_id:int'] - module: database - class_name: GetCurrentSessionIdFromDiecutterIdbrief_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip. - detailed_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip.
        In general each diecutter has exactly one chip embedded into it, and each chip is uniquely identified by an integer id. 
        This means that the chip id has a one-to-one correspondence with the id of the diecutter, but those two ids may not be the same.
        This data service takes a single parameter, namely the id of the chip (an integer) and returns a single dictionary containing the current speed, temperature and number of rotations of the diecutter it is attached to.
        The keys of the dictionary are ""speed"", ""temperature"" and ""rotations"". 
        
        Example usage:
        - If the id of the chip is 123, then the data service would be called as follows:
        chip_id = 123
        current_data = GetCurrentData.call(chip_id=123)
        # get the current speed, temperature and number of rotations
        current_speed = data[""speed""]
        current_temperature = data[""temperature""]
        current_rotations = data[""rotations""]
    
        Things to keep in mind:
        - The refresh rate of the data is 1 second, i.e. the data is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - Note that the values in the dictionary represents the current values of the speed, etc. of the diecutter, they are not aggregated values.
        - Remember that the output value is a dictionary with the above specified keys, so avoid trying to access it using keys not in the above example. - input_parameters: ['chip_id:int'] - output_values: ['diecutter_current_data:dict'] - module: diecutter - class_name: GetCurrentDataFromChip","from data_services.database import GetCamera1IdFromDiecutterId
from data_services.camera1 import GetFrameFromCamera1, DetectErrorsInCardboardUsingCamera1
import time

def pipeline_function():
    diecutter_id = 7
    num_cardboards = 30
    defect_free_count = 0
    defects_count = 0

    # Get the camera1 ID associated with the diecutter
    camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=diecutter_id)

    # Analyze the specified number of cardboards
    for _ in range(num_cardboards):
        # Capture a frame from the camera
        frame = GetFrameFromCamera1.call(camera1_id=camera1_id)
        
        # Detect errors in the captured frame
        contains_errors, error_type = DetectErrorsInCardboardUsingCamera1.call(camera1_id=camera1_id, frame=frame)
        
        # Count defect-free and defective cardboards
        if not contains_errors:
            defect_free_count += 1
        else:
            defects_count += 1
        
        # Wait for the next frame (since the camera refresh rate is 1 second)
        time.sleep(1)

    # Prepare the result
    results = [
        {
            ""count_defect_free_cardboards"": defect_free_count,
            ""count_defective_cardboards"": defects_count
        }
    ]

    return results","+----+--------------------------------+------------------------------+
|    |   count_defect_free_cardboards |   count_defective_cardboards |
|----+--------------------------------+------------------------------|
|  0 |                             17 |                           13 |
+----+--------------------------------+------------------------------+","[{'count_defect_free_cardboards': 17, 'count_defective_cardboards': 13}]","Consider the next 5 carboard of the first diecutter. Generate a table containing: (i) the number of cardboards with no defects, (ii) those with errors, (iii) how many fold errors, and (iv) how many hole errors.","from data_services.database import GetSerialCamera1IdFromDiecutterId
from data_services.database import GetSerialCamera2IdFromDiecutterId
from data_services.database import GetDiecuttersIdOfFactory

def pipeline_function():
    serial_number = 88888404

    results = []

    diecutters_ids = GetDiecuttersIdOfFactory.call()
    for diecutter_id in diecutters_ids:
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=diecutter_id)
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)
        if serial_camera1 == serial_number:
            camera_type = ""camera1""
            results.append({
                'serial number': serial_number,
                'diecutter_id': diecutter_id,
                'type': camera_type
            })
            break
        elif serial_camera2 == serial_number:
            camera_type = ""camera2""
            results.append({
                'serial number': serial_number,
                'diecutter_id': diecutter_id,
                'type': camera_type
            })
            break
    
    return results"
q3,6,"Generate a table for the forthcoming 30 cardboard units processed by diecutter number 7, detailing (i) the count of defect-free cardboards and (ii) the count of cardboards with defects.","brief_description: Data service that, given the id of a camera1, provides a frame captured from that camera1. - detailed_description: Data service that, given the id of a camera1, provides a frame captured from that camera1.
        In general instances of camera1 point downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera1 (an integer) and returns a frame captured from that camera1 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera1 is 123, then the data service would be called as follows:
        camera1_id = 123
        frame = GetFrameFromCamera1.call(camera1_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int'] - output_values: ['frame:np.matrix'] - module: camera1 - class_name: GetFrameFromCamera1brief_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors and provide the type of error. - detailed_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors.
        Recall that a camera1 is a camera device that points downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera1 to use and the frame captured from that camera1.
        It returns a boolean value, True if the frame contains a cardboard with errors, False otherwise.
        Also it returns a integer value, 0 if the frame does not contain errors, 1 if the errors are of type hole and 2 if the errors are of type fold. 

        Example usage:
        - If frame is a variable containing the frame captured from the camera1 with id 123, then the data service would be called as follows:
        camera1_id = 123
        contains_errors, type_errors = DetectErrorsInCardboardUsingCamera1.call(camera1_id=123, frame=frame)

        Things to keep in mind:
        - The output is a tuple of boolean and integer, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool', 'error_type:int'] - module: camera1 - class_name: DetectErrorsInCardboardUsingCamera1brief_description: Data service that, given the id of a camera2, provides a frame captured from that camera2. - detailed_description: Data service that, given the id of a camera2, provides a frame captured from that camera2.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera2 (an integer) and returns a frame captured from that camera2 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera2 is 123, then the data service would be called as follows:
        camera2_id = 123
        frame = GetFrameFromCamera2.call(camera2_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int'] - output_values: ['frame:np.matrix'] - module: camera2 - class_name: GetFrameFromCamera2brief_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors. - detailed_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera2 to use and the frame captured from that camera2 that contains a stack of cardboards.
        It returns a boolean value, True if the frame contains a stack of cardboards with errors, False otherwise.

        Example usage:
        - If frame is a variable containing the frame captured from the camera2 with id 123, then the data service would be called as follows:
        camera2_id = 123
        contains_errors, error_type = DetectErrorsInCardboardStack.call(camera2_id=123, frame=frame)

        Things to keep in mind:
        - The output value is a boolean, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool'] - module: camera2 - class_name: DetectErrorsInCardboardStackUsingCamera2brief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera1 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera1.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera1)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera1:int'] - module: database - class_name: GetSerialCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera2 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera2.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera2)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera2:int'] - module: database - class_name: GetSerialCamera2IdFromDiecutterIdbrief_description: Data service that provides the list of id of the diecutters installed in the factory. - detailed_description: Data service that provides the id of the diecutter installed in the factory.
        The data service relies on the management database of the cardboard factory to provide the list of diecutter id.
        The data service takes no parameter and returns a list of integers, which are the id of the diecutters installed in the factory.

        Example usage:
        - The data service would be called as follows:
        diecutters_id = GetDiecuttersIdOfFactory.call()
        # assuming the diecutters id are [1, 2, 3]
        print(diecutters_id)  # [1, 2, 3]

        Things to keep in mind:
        - The diecutters id is a list of integers, so avoid trying to access it as a dictionary. - input_parameters: [] - output_values: ['diecutters_id:list'] - module: database - class_name: GetDiecuttersIdOfFactorybrief_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter.
        The data service relies on the management database of the cardboard factory to provide the chip id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the chip id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=123)
        # assuming the chip id is 456
        print(chip_id)  # 456

        Things to keep in mind:
        - The chip id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['chip_id:int'] - module: database - class_name: GetDiecutterChipIdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera1 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera1 id is 456
        print(camera1_id)  # 456

        Things to keep in mind:
        - The camera1 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera1_id:int'] - module: database - class_name: GetCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera2 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera2 id is 456
        print(camera2_id)  # 456

        Things to keep in mind:
        - The camera2 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera2_id:int'] - module: database - class_name: GetCamera2IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter.
        The data service relies on the management database of the cardboard factory to provide the session id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the current session id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=123)
        # assuming the session id is 456
        print(session_id)  # 456

        Things to keep in mind:
        - The session id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['session_id:int'] - module: database - class_name: GetCurrentSessionIdFromDiecutterIdbrief_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip. - detailed_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip.
        In general each diecutter has exactly one chip embedded into it, and each chip is uniquely identified by an integer id. 
        This means that the chip id has a one-to-one correspondence with the id of the diecutter, but those two ids may not be the same.
        This data service takes a single parameter, namely the id of the chip (an integer) and returns a single dictionary containing the current speed, temperature and number of rotations of the diecutter it is attached to.
        The keys of the dictionary are ""speed"", ""temperature"" and ""rotations"". 
        
        Example usage:
        - If the id of the chip is 123, then the data service would be called as follows:
        chip_id = 123
        current_data = GetCurrentData.call(chip_id=123)
        # get the current speed, temperature and number of rotations
        current_speed = data[""speed""]
        current_temperature = data[""temperature""]
        current_rotations = data[""rotations""]
    
        Things to keep in mind:
        - The refresh rate of the data is 1 second, i.e. the data is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - Note that the values in the dictionary represents the current values of the speed, etc. of the diecutter, they are not aggregated values.
        - Remember that the output value is a dictionary with the above specified keys, so avoid trying to access it using keys not in the above example. - input_parameters: ['chip_id:int'] - output_values: ['diecutter_current_data:dict'] - module: diecutter - class_name: GetCurrentDataFromChip","from data_services.database import GetCamera1IdFromDiecutterId
from data_services.camera1 import GetFrameFromCamera1, DetectErrorsInCardboardUsingCamera1
import time

def pipeline_function():
    diecutter_id = 7
    num_cardboards = 30
    results = []

    # Get the camera1 ID associated with diecutter number 7
    camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=diecutter_id)

    defect_free_count = 0
    defect_count = 0

    for _ in range(num_cardboards):
        # Capture a frame from camera1
        frame = GetFrameFromCamera1.call(camera1_id=camera1_id)
        
        # Detect errors in the captured frame
        contains_errors, error_type = DetectErrorsInCardboardUsingCamera1.call(camera1_id=camera1_id, frame=frame)
        
        if contains_errors:
            defect_count += 1
        else:
            defect_free_count += 1
        
        # Wait for 1 second to get the next frame (as per camera refresh rate)
        time.sleep(1)

    results.append({
        'count_defect_free_cardboards': defect_free_count,
        'count_cardboards_with_defects': defect_count
    })

    return results","+----+--------------------------------+---------------------------------+
|    |   count_defect_free_cardboards |   count_cardboards_with_defects |
|----+--------------------------------+---------------------------------|
|  0 |                             17 |                              13 |
+----+--------------------------------+---------------------------------+","[{'count_defect_free_cardboards': 17, 'count_cardboards_with_defects': 13}]","Consider the next 5 carboard of the first diecutter. Generate a table containing: (i) the number of cardboards with no defects, (ii) those with errors, (iii) how many fold errors, and (iv) how many hole errors.","from data_services.database import GetSerialCamera1IdFromDiecutterId
from data_services.database import GetSerialCamera2IdFromDiecutterId
from data_services.database import GetDiecuttersIdOfFactory

def pipeline_function():
    serial_number = 88888404

    results = []

    diecutters_ids = GetDiecuttersIdOfFactory.call()
    for diecutter_id in diecutters_ids:
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=diecutter_id)
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)
        if serial_camera1 == serial_number:
            camera_type = ""camera1""
            results.append({
                'serial number': serial_number,
                'diecutter_id': diecutter_id,
                'type': camera_type
            })
            break
        elif serial_camera2 == serial_number:
            camera_type = ""camera2""
            results.append({
                'serial number': serial_number,
                'diecutter_id': diecutter_id,
                'type': camera_type
            })
            break
    
    return results"
q3,7,"For the upcoming 30 cardboard units processed by diecutter with ID 7, produce a table showing (i) the count of defect-free cardboards and (ii) the count of cardboards that contain defects.","brief_description: Data service that, given the id of a camera1, provides a frame captured from that camera1. - detailed_description: Data service that, given the id of a camera1, provides a frame captured from that camera1.
        In general instances of camera1 point downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera1 (an integer) and returns a frame captured from that camera1 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera1 is 123, then the data service would be called as follows:
        camera1_id = 123
        frame = GetFrameFromCamera1.call(camera1_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int'] - output_values: ['frame:np.matrix'] - module: camera1 - class_name: GetFrameFromCamera1brief_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors and provide the type of error. - detailed_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors.
        Recall that a camera1 is a camera device that points downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera1 to use and the frame captured from that camera1.
        It returns a boolean value, True if the frame contains a cardboard with errors, False otherwise.
        Also it returns a integer value, 0 if the frame does not contain errors, 1 if the errors are of type hole and 2 if the errors are of type fold. 

        Example usage:
        - If frame is a variable containing the frame captured from the camera1 with id 123, then the data service would be called as follows:
        camera1_id = 123
        contains_errors, type_errors = DetectErrorsInCardboardUsingCamera1.call(camera1_id=123, frame=frame)

        Things to keep in mind:
        - The output is a tuple of boolean and integer, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool', 'error_type:int'] - module: camera1 - class_name: DetectErrorsInCardboardUsingCamera1brief_description: Data service that, given the id of a camera2, provides a frame captured from that camera2. - detailed_description: Data service that, given the id of a camera2, provides a frame captured from that camera2.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera2 (an integer) and returns a frame captured from that camera2 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera2 is 123, then the data service would be called as follows:
        camera2_id = 123
        frame = GetFrameFromCamera2.call(camera2_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int'] - output_values: ['frame:np.matrix'] - module: camera2 - class_name: GetFrameFromCamera2brief_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors. - detailed_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera2 to use and the frame captured from that camera2 that contains a stack of cardboards.
        It returns a boolean value, True if the frame contains a stack of cardboards with errors, False otherwise.

        Example usage:
        - If frame is a variable containing the frame captured from the camera2 with id 123, then the data service would be called as follows:
        camera2_id = 123
        contains_errors, error_type = DetectErrorsInCardboardStack.call(camera2_id=123, frame=frame)

        Things to keep in mind:
        - The output value is a boolean, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool'] - module: camera2 - class_name: DetectErrorsInCardboardStackUsingCamera2brief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera1 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera1.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera1)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera1:int'] - module: database - class_name: GetSerialCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera2 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera2.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera2)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera2:int'] - module: database - class_name: GetSerialCamera2IdFromDiecutterIdbrief_description: Data service that provides the list of id of the diecutters installed in the factory. - detailed_description: Data service that provides the id of the diecutter installed in the factory.
        The data service relies on the management database of the cardboard factory to provide the list of diecutter id.
        The data service takes no parameter and returns a list of integers, which are the id of the diecutters installed in the factory.

        Example usage:
        - The data service would be called as follows:
        diecutters_id = GetDiecuttersIdOfFactory.call()
        # assuming the diecutters id are [1, 2, 3]
        print(diecutters_id)  # [1, 2, 3]

        Things to keep in mind:
        - The diecutters id is a list of integers, so avoid trying to access it as a dictionary. - input_parameters: [] - output_values: ['diecutters_id:list'] - module: database - class_name: GetDiecuttersIdOfFactorybrief_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter.
        The data service relies on the management database of the cardboard factory to provide the chip id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the chip id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=123)
        # assuming the chip id is 456
        print(chip_id)  # 456

        Things to keep in mind:
        - The chip id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['chip_id:int'] - module: database - class_name: GetDiecutterChipIdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera1 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera1 id is 456
        print(camera1_id)  # 456

        Things to keep in mind:
        - The camera1 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera1_id:int'] - module: database - class_name: GetCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera2 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera2 id is 456
        print(camera2_id)  # 456

        Things to keep in mind:
        - The camera2 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera2_id:int'] - module: database - class_name: GetCamera2IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter.
        The data service relies on the management database of the cardboard factory to provide the session id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the current session id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=123)
        # assuming the session id is 456
        print(session_id)  # 456

        Things to keep in mind:
        - The session id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['session_id:int'] - module: database - class_name: GetCurrentSessionIdFromDiecutterIdbrief_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip. - detailed_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip.
        In general each diecutter has exactly one chip embedded into it, and each chip is uniquely identified by an integer id. 
        This means that the chip id has a one-to-one correspondence with the id of the diecutter, but those two ids may not be the same.
        This data service takes a single parameter, namely the id of the chip (an integer) and returns a single dictionary containing the current speed, temperature and number of rotations of the diecutter it is attached to.
        The keys of the dictionary are ""speed"", ""temperature"" and ""rotations"". 
        
        Example usage:
        - If the id of the chip is 123, then the data service would be called as follows:
        chip_id = 123
        current_data = GetCurrentData.call(chip_id=123)
        # get the current speed, temperature and number of rotations
        current_speed = data[""speed""]
        current_temperature = data[""temperature""]
        current_rotations = data[""rotations""]
    
        Things to keep in mind:
        - The refresh rate of the data is 1 second, i.e. the data is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - Note that the values in the dictionary represents the current values of the speed, etc. of the diecutter, they are not aggregated values.
        - Remember that the output value is a dictionary with the above specified keys, so avoid trying to access it using keys not in the above example. - input_parameters: ['chip_id:int'] - output_values: ['diecutter_current_data:dict'] - module: diecutter - class_name: GetCurrentDataFromChip","from data_services.camera1 import GetFrameFromCamera1, DetectErrorsInCardboardUsingCamera1
from data_services.database import GetCamera1IdFromDiecutterId
import time

def pipeline_function():
    diecutter_id = 7
    num_cardboards = 30
    defect_free_count = 0
    defect_count = 0

    # Get the camera1 ID associated with the diecutter
    camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=diecutter_id)

    for _ in range(num_cardboards):
        # Capture a frame from the camera
        frame = GetFrameFromCamera1.call(camera1_id=camera1_id)
        
        # Detect errors in the captured cardboard
        contains_errors, error_type = DetectErrorsInCardboardUsingCamera1.call(camera1_id=camera1_id, frame=frame)
        
        if contains_errors:
            defect_count += 1
        else:
            defect_free_count += 1
        
        # Wait for 1 second to get the next frame (since the camera refresh rate is 1 second)
        time.sleep(1)

    results = [{
        'defect_free_count': defect_free_count,
        'defect_count': defect_count
    }]

    return results","+----+---------------------+----------------+
|    |   defect_free_count |   defect_count |
|----+---------------------+----------------|
|  0 |                  17 |             13 |
+----+---------------------+----------------+","[{'defect_free_count': 17, 'defect_count': 13}]","Consider the next 5 carboard of the first diecutter. Generate a table containing: (i) the number of cardboards with no defects, (ii) those with errors, (iii) how many fold errors, and (iv) how many hole errors.","from data_services.database import GetSerialCamera1IdFromDiecutterId
from data_services.database import GetSerialCamera2IdFromDiecutterId
from data_services.database import GetDiecuttersIdOfFactory

def pipeline_function():
    serial_number = 88888404

    results = []

    diecutters_ids = GetDiecuttersIdOfFactory.call()
    for diecutter_id in diecutters_ids:
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=diecutter_id)
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)
        if serial_camera1 == serial_number:
            camera_type = ""camera1""
            results.append({
                'serial number': serial_number,
                'diecutter_id': diecutter_id,
                'type': camera_type
            })
            break
        elif serial_camera2 == serial_number:
            camera_type = ""camera2""
            results.append({
                'serial number': serial_number,
                'diecutter_id': diecutter_id,
                'type': camera_type
            })
            break
    
    return results"
q3,8,"For the forthcoming 30 cardboard units processed by the diecutter, identified by id 7, construct a table displaying the count of defect-free cardboards and the number with defects.","brief_description: Data service that, given the id of a camera1, provides a frame captured from that camera1. - detailed_description: Data service that, given the id of a camera1, provides a frame captured from that camera1.
        In general instances of camera1 point downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera1 (an integer) and returns a frame captured from that camera1 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera1 is 123, then the data service would be called as follows:
        camera1_id = 123
        frame = GetFrameFromCamera1.call(camera1_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int'] - output_values: ['frame:np.matrix'] - module: camera1 - class_name: GetFrameFromCamera1brief_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors and provide the type of error. - detailed_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors.
        Recall that a camera1 is a camera device that points downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera1 to use and the frame captured from that camera1.
        It returns a boolean value, True if the frame contains a cardboard with errors, False otherwise.
        Also it returns a integer value, 0 if the frame does not contain errors, 1 if the errors are of type hole and 2 if the errors are of type fold. 

        Example usage:
        - If frame is a variable containing the frame captured from the camera1 with id 123, then the data service would be called as follows:
        camera1_id = 123
        contains_errors, type_errors = DetectErrorsInCardboardUsingCamera1.call(camera1_id=123, frame=frame)

        Things to keep in mind:
        - The output is a tuple of boolean and integer, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool', 'error_type:int'] - module: camera1 - class_name: DetectErrorsInCardboardUsingCamera1brief_description: Data service that, given the id of a camera2, provides a frame captured from that camera2. - detailed_description: Data service that, given the id of a camera2, provides a frame captured from that camera2.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera2 (an integer) and returns a frame captured from that camera2 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera2 is 123, then the data service would be called as follows:
        camera2_id = 123
        frame = GetFrameFromCamera2.call(camera2_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int'] - output_values: ['frame:np.matrix'] - module: camera2 - class_name: GetFrameFromCamera2brief_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors. - detailed_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera2 to use and the frame captured from that camera2 that contains a stack of cardboards.
        It returns a boolean value, True if the frame contains a stack of cardboards with errors, False otherwise.

        Example usage:
        - If frame is a variable containing the frame captured from the camera2 with id 123, then the data service would be called as follows:
        camera2_id = 123
        contains_errors, error_type = DetectErrorsInCardboardStack.call(camera2_id=123, frame=frame)

        Things to keep in mind:
        - The output value is a boolean, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool'] - module: camera2 - class_name: DetectErrorsInCardboardStackUsingCamera2brief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera1 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera1.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera1)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera1:int'] - module: database - class_name: GetSerialCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera2 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera2.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera2)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera2:int'] - module: database - class_name: GetSerialCamera2IdFromDiecutterIdbrief_description: Data service that provides the list of id of the diecutters installed in the factory. - detailed_description: Data service that provides the id of the diecutter installed in the factory.
        The data service relies on the management database of the cardboard factory to provide the list of diecutter id.
        The data service takes no parameter and returns a list of integers, which are the id of the diecutters installed in the factory.

        Example usage:
        - The data service would be called as follows:
        diecutters_id = GetDiecuttersIdOfFactory.call()
        # assuming the diecutters id are [1, 2, 3]
        print(diecutters_id)  # [1, 2, 3]

        Things to keep in mind:
        - The diecutters id is a list of integers, so avoid trying to access it as a dictionary. - input_parameters: [] - output_values: ['diecutters_id:list'] - module: database - class_name: GetDiecuttersIdOfFactorybrief_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter.
        The data service relies on the management database of the cardboard factory to provide the chip id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the chip id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=123)
        # assuming the chip id is 456
        print(chip_id)  # 456

        Things to keep in mind:
        - The chip id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['chip_id:int'] - module: database - class_name: GetDiecutterChipIdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera1 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera1 id is 456
        print(camera1_id)  # 456

        Things to keep in mind:
        - The camera1 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera1_id:int'] - module: database - class_name: GetCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera2 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera2 id is 456
        print(camera2_id)  # 456

        Things to keep in mind:
        - The camera2 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera2_id:int'] - module: database - class_name: GetCamera2IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter.
        The data service relies on the management database of the cardboard factory to provide the session id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the current session id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=123)
        # assuming the session id is 456
        print(session_id)  # 456

        Things to keep in mind:
        - The session id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['session_id:int'] - module: database - class_name: GetCurrentSessionIdFromDiecutterIdbrief_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip. - detailed_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip.
        In general each diecutter has exactly one chip embedded into it, and each chip is uniquely identified by an integer id. 
        This means that the chip id has a one-to-one correspondence with the id of the diecutter, but those two ids may not be the same.
        This data service takes a single parameter, namely the id of the chip (an integer) and returns a single dictionary containing the current speed, temperature and number of rotations of the diecutter it is attached to.
        The keys of the dictionary are ""speed"", ""temperature"" and ""rotations"". 
        
        Example usage:
        - If the id of the chip is 123, then the data service would be called as follows:
        chip_id = 123
        current_data = GetCurrentData.call(chip_id=123)
        # get the current speed, temperature and number of rotations
        current_speed = data[""speed""]
        current_temperature = data[""temperature""]
        current_rotations = data[""rotations""]
    
        Things to keep in mind:
        - The refresh rate of the data is 1 second, i.e. the data is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - Note that the values in the dictionary represents the current values of the speed, etc. of the diecutter, they are not aggregated values.
        - Remember that the output value is a dictionary with the above specified keys, so avoid trying to access it using keys not in the above example. - input_parameters: ['chip_id:int'] - output_values: ['diecutter_current_data:dict'] - module: diecutter - class_name: GetCurrentDataFromChip","from data_services.database import GetCamera1IdFromDiecutterId
from data_services.camera1 import GetFrameFromCamera1, DetectErrorsInCardboardUsingCamera1
import time

def pipeline_function():
    diecutter_id = 7
    num_cardboards = 30
    defect_free_count = 0
    defects_count = 0

    # Get the camera1 ID associated with the diecutter
    camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=diecutter_id)

    # Process each cardboard
    for _ in range(num_cardboards):
        # Get a frame from the camera
        frame = GetFrameFromCamera1.call(camera1_id=camera1_id)
        
        # Detect errors in the cardboard
        contains_errors, error_type = DetectErrorsInCardboardUsingCamera1.call(camera1_id=camera1_id, frame=frame)
        
        # Count defect-free and defective cardboards
        if not contains_errors:
            defect_free_count += 1
        else:
            defects_count += 1
        
        # Wait for the next frame (since the camera refresh rate is 1 second)
        time.sleep(1)

    # Prepare the result
    results = [{
        'defect_free_count': defect_free, 
        'defects_count': defects_count
    }]

    return results",The pipeline did not run successfully,"[{'defect_free_count': 17, 'defect_count': 13}]","Consider the next 5 carboard of the first diecutter. Generate a table containing: (i) the number of cardboards with no defects, (ii) those with errors, (iii) how many fold errors, and (iv) how many hole errors.","from data_services.database import GetSerialCamera1IdFromDiecutterId
from data_services.database import GetSerialCamera2IdFromDiecutterId
from data_services.database import GetDiecuttersIdOfFactory

def pipeline_function():
    serial_number = 88888404

    results = []

    diecutters_ids = GetDiecuttersIdOfFactory.call()
    for diecutter_id in diecutters_ids:
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=diecutter_id)
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)
        if serial_camera1 == serial_number:
            camera_type = ""camera1""
            results.append({
                'serial number': serial_number,
                'diecutter_id': diecutter_id,
                'type': camera_type
            })
            break
        elif serial_camera2 == serial_number:
            camera_type = ""camera2""
            results.append({
                'serial number': serial_number,
                'diecutter_id': diecutter_id,
                'type': camera_type
            })
            break
    
    return results"
q3,9,"Please provide a table for the upcoming 30 cardboard pieces processed by the diecutter with ID 7, detailing (i) how many cardboard pieces are defect-free and (ii) how many contain defects.","brief_description: Data service that, given the id of a camera1, provides a frame captured from that camera1. - detailed_description: Data service that, given the id of a camera1, provides a frame captured from that camera1.
        In general instances of camera1 point downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera1 (an integer) and returns a frame captured from that camera1 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera1 is 123, then the data service would be called as follows:
        camera1_id = 123
        frame = GetFrameFromCamera1.call(camera1_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int'] - output_values: ['frame:np.matrix'] - module: camera1 - class_name: GetFrameFromCamera1brief_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors and provide the type of error. - detailed_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors.
        Recall that a camera1 is a camera device that points downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera1 to use and the frame captured from that camera1.
        It returns a boolean value, True if the frame contains a cardboard with errors, False otherwise.
        Also it returns a integer value, 0 if the frame does not contain errors, 1 if the errors are of type hole and 2 if the errors are of type fold. 

        Example usage:
        - If frame is a variable containing the frame captured from the camera1 with id 123, then the data service would be called as follows:
        camera1_id = 123
        contains_errors, type_errors = DetectErrorsInCardboardUsingCamera1.call(camera1_id=123, frame=frame)

        Things to keep in mind:
        - The output is a tuple of boolean and integer, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool', 'error_type:int'] - module: camera1 - class_name: DetectErrorsInCardboardUsingCamera1brief_description: Data service that, given the id of a camera2, provides a frame captured from that camera2. - detailed_description: Data service that, given the id of a camera2, provides a frame captured from that camera2.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera2 (an integer) and returns a frame captured from that camera2 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera2 is 123, then the data service would be called as follows:
        camera2_id = 123
        frame = GetFrameFromCamera2.call(camera2_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int'] - output_values: ['frame:np.matrix'] - module: camera2 - class_name: GetFrameFromCamera2brief_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors. - detailed_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera2 to use and the frame captured from that camera2 that contains a stack of cardboards.
        It returns a boolean value, True if the frame contains a stack of cardboards with errors, False otherwise.

        Example usage:
        - If frame is a variable containing the frame captured from the camera2 with id 123, then the data service would be called as follows:
        camera2_id = 123
        contains_errors, error_type = DetectErrorsInCardboardStack.call(camera2_id=123, frame=frame)

        Things to keep in mind:
        - The output value is a boolean, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool'] - module: camera2 - class_name: DetectErrorsInCardboardStackUsingCamera2brief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera1 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera1.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera1)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera1:int'] - module: database - class_name: GetSerialCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera2 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera2.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera2)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera2:int'] - module: database - class_name: GetSerialCamera2IdFromDiecutterIdbrief_description: Data service that provides the list of id of the diecutters installed in the factory. - detailed_description: Data service that provides the id of the diecutter installed in the factory.
        The data service relies on the management database of the cardboard factory to provide the list of diecutter id.
        The data service takes no parameter and returns a list of integers, which are the id of the diecutters installed in the factory.

        Example usage:
        - The data service would be called as follows:
        diecutters_id = GetDiecuttersIdOfFactory.call()
        # assuming the diecutters id are [1, 2, 3]
        print(diecutters_id)  # [1, 2, 3]

        Things to keep in mind:
        - The diecutters id is a list of integers, so avoid trying to access it as a dictionary. - input_parameters: [] - output_values: ['diecutters_id:list'] - module: database - class_name: GetDiecuttersIdOfFactorybrief_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter.
        The data service relies on the management database of the cardboard factory to provide the chip id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the chip id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=123)
        # assuming the chip id is 456
        print(chip_id)  # 456

        Things to keep in mind:
        - The chip id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['chip_id:int'] - module: database - class_name: GetDiecutterChipIdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera1 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera1 id is 456
        print(camera1_id)  # 456

        Things to keep in mind:
        - The camera1 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera1_id:int'] - module: database - class_name: GetCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera2 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera2 id is 456
        print(camera2_id)  # 456

        Things to keep in mind:
        - The camera2 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera2_id:int'] - module: database - class_name: GetCamera2IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter.
        The data service relies on the management database of the cardboard factory to provide the session id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the current session id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=123)
        # assuming the session id is 456
        print(session_id)  # 456

        Things to keep in mind:
        - The session id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['session_id:int'] - module: database - class_name: GetCurrentSessionIdFromDiecutterIdbrief_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip. - detailed_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip.
        In general each diecutter has exactly one chip embedded into it, and each chip is uniquely identified by an integer id. 
        This means that the chip id has a one-to-one correspondence with the id of the diecutter, but those two ids may not be the same.
        This data service takes a single parameter, namely the id of the chip (an integer) and returns a single dictionary containing the current speed, temperature and number of rotations of the diecutter it is attached to.
        The keys of the dictionary are ""speed"", ""temperature"" and ""rotations"". 
        
        Example usage:
        - If the id of the chip is 123, then the data service would be called as follows:
        chip_id = 123
        current_data = GetCurrentData.call(chip_id=123)
        # get the current speed, temperature and number of rotations
        current_speed = data[""speed""]
        current_temperature = data[""temperature""]
        current_rotations = data[""rotations""]
    
        Things to keep in mind:
        - The refresh rate of the data is 1 second, i.e. the data is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - Note that the values in the dictionary represents the current values of the speed, etc. of the diecutter, they are not aggregated values.
        - Remember that the output value is a dictionary with the above specified keys, so avoid trying to access it using keys not in the above example. - input_parameters: ['chip_id:int'] - output_values: ['diecutter_current_data:dict'] - module: diecutter - class_name: GetCurrentDataFromChip","from data_services.database import GetCamera1IdFromDiecutterId
from data_services.camera1 import GetFrameFromCamera1, DetectErrorsInCardboardUsingCamera1
import time

def pipeline_function():
    diecutter_id = 7
    num_cardboards = 30
    results = []

    # Get the camera1 ID associated with the diecutter
    camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=diecutter_id)

    defect_free_count = 0
    defect_count = 0

    # Process the upcoming 30 cardboard pieces
    for _ in range(num_cardboards):
        # Capture a frame from the camera
        frame = GetFrameFromCamera1.call(camera1_id=camera1_id)
        
        # Detect errors in the captured cardboard frame
        contains_errors, error_type = DetectErrorsInCardboardUsingCamera1.call(camera1_id=camera1_id, frame=frame)
        
        if contains_errors:
            defect_count += 1
        else:
            defect_free_count += 1
        
        # Wait for the next frame (since the camera refresh rate is 1 second)
        time.sleep(1)

    # Append the result for the 30 cardboards
    results.append({
        'defect_free_count': defect_free, 
        'defect_count': defect_count
    })

    return results",The pipeline did not run successfully,"[{'defect_free_count': 17, 'defect_count': 13}]","Consider the next 5 carboard of the first diecutter. Generate a table containing: (i) the number of cardboards with no defects, (ii) those with errors, (iii) how many fold errors, and (iv) how many hole errors.","from data_services.database import GetSerialCamera1IdFromDiecutterId
from data_services.database import GetSerialCamera2IdFromDiecutterId
from data_services.database import GetDiecuttersIdOfFactory

def pipeline_function():
    serial_number = 88888404

    results = []

    diecutters_ids = GetDiecuttersIdOfFactory.call()
    for diecutter_id in diecutters_ids:
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=diecutter_id)
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)
        if serial_camera1 == serial_number:
            camera_type = ""camera1""
            results.append({
                'serial number': serial_number,
                'diecutter_id': diecutter_id,
                'type': camera_type
            })
            break
        elif serial_camera2 == serial_number:
            camera_type = ""camera2""
            results.append({
                'serial number': serial_number,
                'diecutter_id': diecutter_id,
                'type': camera_type
            })
            break
    
    return results"
q4,0,"Compute a table that gives some information about the current session of diecutter 14. For each stack produced, the table should tell me (i) if the stack contains errors, (ii) if it contains errors, the type of error, (iii) the current speed of the diecutter, and (iii) the current temperature of the diecutter. The table should contain data for the next 10 stacks.","brief_description: Data service that, given the id of a camera1, provides a frame captured from that camera1. - detailed_description: Data service that, given the id of a camera1, provides a frame captured from that camera1.
        In general instances of camera1 point downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera1 (an integer) and returns a frame captured from that camera1 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera1 is 123, then the data service would be called as follows:
        camera1_id = 123
        frame = GetFrameFromCamera1.call(camera1_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int'] - output_values: ['frame:np.matrix'] - module: camera1 - class_name: GetFrameFromCamera1brief_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors and provide the type of error. - detailed_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors.
        Recall that a camera1 is a camera device that points downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera1 to use and the frame captured from that camera1.
        It returns a boolean value, True if the frame contains a cardboard with errors, False otherwise.
        Also it returns a integer value, 0 if the frame does not contain errors, 1 if the errors are of type hole and 2 if the errors are of type fold. 

        Example usage:
        - If frame is a variable containing the frame captured from the camera1 with id 123, then the data service would be called as follows:
        camera1_id = 123
        contains_errors, type_errors = DetectErrorsInCardboardUsingCamera1.call(camera1_id=123, frame=frame)

        Things to keep in mind:
        - The output is a tuple of boolean and integer, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool', 'error_type:int'] - module: camera1 - class_name: DetectErrorsInCardboardUsingCamera1brief_description: Data service that, given the id of a camera2, provides a frame captured from that camera2. - detailed_description: Data service that, given the id of a camera2, provides a frame captured from that camera2.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera2 (an integer) and returns a frame captured from that camera2 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera2 is 123, then the data service would be called as follows:
        camera2_id = 123
        frame = GetFrameFromCamera2.call(camera2_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int'] - output_values: ['frame:np.matrix'] - module: camera2 - class_name: GetFrameFromCamera2brief_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors. - detailed_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera2 to use and the frame captured from that camera2 that contains a stack of cardboards.
        It returns a boolean value, True if the frame contains a stack of cardboards with errors, False otherwise.

        Example usage:
        - If frame is a variable containing the frame captured from the camera2 with id 123, then the data service would be called as follows:
        camera2_id = 123
        contains_errors, error_type = DetectErrorsInCardboardStack.call(camera2_id=123, frame=frame)

        Things to keep in mind:
        - The output value is a boolean, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool'] - module: camera2 - class_name: DetectErrorsInCardboardStackUsingCamera2brief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera1 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera1.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera1)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera1:int'] - module: database - class_name: GetSerialCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera2 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera2.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera2)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera2:int'] - module: database - class_name: GetSerialCamera2IdFromDiecutterIdbrief_description: Data service that provides the list of id of the diecutters installed in the factory. - detailed_description: Data service that provides the id of the diecutter installed in the factory.
        The data service relies on the management database of the cardboard factory to provide the list of diecutter id.
        The data service takes no parameter and returns a list of integers, which are the id of the diecutters installed in the factory.

        Example usage:
        - The data service would be called as follows:
        diecutters_id = GetDiecuttersIdOfFactory.call()
        # assuming the diecutters id are [1, 2, 3]
        print(diecutters_id)  # [1, 2, 3]

        Things to keep in mind:
        - The diecutters id is a list of integers, so avoid trying to access it as a dictionary. - input_parameters: [] - output_values: ['diecutters_id:list'] - module: database - class_name: GetDiecuttersIdOfFactorybrief_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter.
        The data service relies on the management database of the cardboard factory to provide the chip id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the chip id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=123)
        # assuming the chip id is 456
        print(chip_id)  # 456

        Things to keep in mind:
        - The chip id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['chip_id:int'] - module: database - class_name: GetDiecutterChipIdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera1 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera1 id is 456
        print(camera1_id)  # 456

        Things to keep in mind:
        - The camera1 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera1_id:int'] - module: database - class_name: GetCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera2 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera2 id is 456
        print(camera2_id)  # 456

        Things to keep in mind:
        - The camera2 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera2_id:int'] - module: database - class_name: GetCamera2IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter.
        The data service relies on the management database of the cardboard factory to provide the session id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the current session id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=123)
        # assuming the session id is 456
        print(session_id)  # 456

        Things to keep in mind:
        - The session id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['session_id:int'] - module: database - class_name: GetCurrentSessionIdFromDiecutterIdbrief_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip. - detailed_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip.
        In general each diecutter has exactly one chip embedded into it, and each chip is uniquely identified by an integer id. 
        This means that the chip id has a one-to-one correspondence with the id of the diecutter, but those two ids may not be the same.
        This data service takes a single parameter, namely the id of the chip (an integer) and returns a single dictionary containing the current speed, temperature and number of rotations of the diecutter it is attached to.
        The keys of the dictionary are ""speed"", ""temperature"" and ""rotations"". 
        
        Example usage:
        - If the id of the chip is 123, then the data service would be called as follows:
        chip_id = 123
        current_data = GetCurrentData.call(chip_id=123)
        # get the current speed, temperature and number of rotations
        current_speed = data[""speed""]
        current_temperature = data[""temperature""]
        current_rotations = data[""rotations""]
    
        Things to keep in mind:
        - The refresh rate of the data is 1 second, i.e. the data is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - Note that the values in the dictionary represents the current values of the speed, etc. of the diecutter, they are not aggregated values.
        - Remember that the output value is a dictionary with the above specified keys, so avoid trying to access it using keys not in the above example. - input_parameters: ['chip_id:int'] - output_values: ['diecutter_current_data:dict'] - module: diecutter - class_name: GetCurrentDataFromChip","from data_services.database import GetCamera2IdFromDiecutterId
from data_services.camera2 import GetFrameFromCamera2, DetectErrorsInCardboardStackUsingCamera2
from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
import time

def pipeline_function():
    diecutter_id = 14
    camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)
    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    
    results = []
    for _ in range(10):
        frame = GetFrameFromCamera2.call(camera2_id=camera2_id)
        contains_errors = DetectErrorsInCardboardStackUsingCamera2.call(camera2_id=camera2_id, frame=frame)
        current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
        
        result = {
            'contains_errors': contains_errors,
            'current_speed': current_data['speed'],
            'current_temperature': current_data['temperature']
        }
        results.append(result)
        
        # Wait for 1 second to get the next frame
        time.sleep(1)
    
    return results","+----+-------------------+-----------------+-----------------------+
|    | contains_errors   |   current_speed |   current_temperature |
|----+-------------------+-----------------+-----------------------|
|  0 | [True, 1]         |               9 |                     0 |
|  1 | [False, 0]        |               4 |                     4 |
|  2 | [False, 0]        |               3 |                     3 |
|  3 | [True, 1]         |               3 |                    14 |
|  4 | [True, 1]         |               4 |                    18 |
|  5 | [False, 0]        |               6 |                    27 |
|  6 | [False, 0]        |               3 |                     0 |
|  7 | [True, 2]         |               7 |                     9 |
|  8 | [True, 1]         |               5 |                    26 |
|  9 | [True, 2]         |               4 |                     9 |
+----+-------------------+-----------------+-----------------------+","[{'contains_errors': [True, 1], 'current_speed': 9, 'current_temperature': 0}, {'contains_errors': [False, 0], 'current_speed': 4, 'current_temperature': 4}, {'contains_errors': [False, 0], 'current_speed': 3, 'current_temperature': 3}, {'contains_errors': [True, 1], 'current_speed': 3, 'current_temperature': 14}, {'contains_errors': [True, 1], 'current_speed': 4, 'current_temperature': 18}, {'contains_errors': [False, 0], 'current_speed': 6, 'current_temperature': 27}, {'contains_errors': [False, 0], 'current_speed': 3, 'current_temperature': 0}, {'contains_errors': [True, 2], 'current_speed': 7, 'current_temperature': 9}, {'contains_errors': [True, 1], 'current_speed': 5, 'current_temperature': 26}, {'contains_errors': [True, 2], 'current_speed': 4, 'current_temperature': 9}]","Compute a table that gives some information about the current session of diecutter 14. For each erroneous stack produced, the table should tell me (i) the type of error, (ii) the current session of the diecutter, (iii) the current speed of the diecutter, (iii) the current temperature of the diecutter and (iv) the total number of rotations until now. The table should contain data for the next 30 stacks.","from data_services.database import GetSerialCamera1IdFromDiecutterId
from data_services.database import GetSerialCamera2IdFromDiecutterId
from data_services.database import GetDiecuttersIdOfFactory

def pipeline_function():
    serial_number = 88888404

    results = []

    diecutters_ids = GetDiecuttersIdOfFactory.call()
    for diecutter_id in diecutters_ids:
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=diecutter_id)
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)
        if serial_camera1 == serial_number:
            camera_type = ""camera1""
            results.append({
                'serial number': serial_number,
                'diecutter_id': diecutter_id,
                'type': camera_type
            })
            break
        elif serial_camera2 == serial_number:
            camera_type = ""camera2""
            results.append({
                'serial number': serial_number,
                'diecutter_id': diecutter_id,
                'type': camera_type
            })
            break
    
    return results"
q4,1,"Generate a table displaying details concerning the current operation of diecutter 14. For each of the next 10 stacks produced, the table should include (i) whether the stack has errors, (ii) the error type if applicable, (iii) the running speed of the diecutter, and (iv) the current temperature of the diecutter.","brief_description: Data service that, given the id of a camera1, provides a frame captured from that camera1. - detailed_description: Data service that, given the id of a camera1, provides a frame captured from that camera1.
        In general instances of camera1 point downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera1 (an integer) and returns a frame captured from that camera1 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera1 is 123, then the data service would be called as follows:
        camera1_id = 123
        frame = GetFrameFromCamera1.call(camera1_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int'] - output_values: ['frame:np.matrix'] - module: camera1 - class_name: GetFrameFromCamera1brief_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors and provide the type of error. - detailed_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors.
        Recall that a camera1 is a camera device that points downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera1 to use and the frame captured from that camera1.
        It returns a boolean value, True if the frame contains a cardboard with errors, False otherwise.
        Also it returns a integer value, 0 if the frame does not contain errors, 1 if the errors are of type hole and 2 if the errors are of type fold. 

        Example usage:
        - If frame is a variable containing the frame captured from the camera1 with id 123, then the data service would be called as follows:
        camera1_id = 123
        contains_errors, type_errors = DetectErrorsInCardboardUsingCamera1.call(camera1_id=123, frame=frame)

        Things to keep in mind:
        - The output is a tuple of boolean and integer, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool', 'error_type:int'] - module: camera1 - class_name: DetectErrorsInCardboardUsingCamera1brief_description: Data service that, given the id of a camera2, provides a frame captured from that camera2. - detailed_description: Data service that, given the id of a camera2, provides a frame captured from that camera2.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera2 (an integer) and returns a frame captured from that camera2 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera2 is 123, then the data service would be called as follows:
        camera2_id = 123
        frame = GetFrameFromCamera2.call(camera2_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int'] - output_values: ['frame:np.matrix'] - module: camera2 - class_name: GetFrameFromCamera2brief_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors. - detailed_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera2 to use and the frame captured from that camera2 that contains a stack of cardboards.
        It returns a boolean value, True if the frame contains a stack of cardboards with errors, False otherwise.

        Example usage:
        - If frame is a variable containing the frame captured from the camera2 with id 123, then the data service would be called as follows:
        camera2_id = 123
        contains_errors, error_type = DetectErrorsInCardboardStack.call(camera2_id=123, frame=frame)

        Things to keep in mind:
        - The output value is a boolean, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool'] - module: camera2 - class_name: DetectErrorsInCardboardStackUsingCamera2brief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera1 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera1.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera1)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera1:int'] - module: database - class_name: GetSerialCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera2 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera2.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera2)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera2:int'] - module: database - class_name: GetSerialCamera2IdFromDiecutterIdbrief_description: Data service that provides the list of id of the diecutters installed in the factory. - detailed_description: Data service that provides the id of the diecutter installed in the factory.
        The data service relies on the management database of the cardboard factory to provide the list of diecutter id.
        The data service takes no parameter and returns a list of integers, which are the id of the diecutters installed in the factory.

        Example usage:
        - The data service would be called as follows:
        diecutters_id = GetDiecuttersIdOfFactory.call()
        # assuming the diecutters id are [1, 2, 3]
        print(diecutters_id)  # [1, 2, 3]

        Things to keep in mind:
        - The diecutters id is a list of integers, so avoid trying to access it as a dictionary. - input_parameters: [] - output_values: ['diecutters_id:list'] - module: database - class_name: GetDiecuttersIdOfFactorybrief_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter.
        The data service relies on the management database of the cardboard factory to provide the chip id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the chip id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=123)
        # assuming the chip id is 456
        print(chip_id)  # 456

        Things to keep in mind:
        - The chip id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['chip_id:int'] - module: database - class_name: GetDiecutterChipIdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera1 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera1 id is 456
        print(camera1_id)  # 456

        Things to keep in mind:
        - The camera1 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera1_id:int'] - module: database - class_name: GetCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera2 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera2 id is 456
        print(camera2_id)  # 456

        Things to keep in mind:
        - The camera2 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera2_id:int'] - module: database - class_name: GetCamera2IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter.
        The data service relies on the management database of the cardboard factory to provide the session id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the current session id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=123)
        # assuming the session id is 456
        print(session_id)  # 456

        Things to keep in mind:
        - The session id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['session_id:int'] - module: database - class_name: GetCurrentSessionIdFromDiecutterIdbrief_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip. - detailed_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip.
        In general each diecutter has exactly one chip embedded into it, and each chip is uniquely identified by an integer id. 
        This means that the chip id has a one-to-one correspondence with the id of the diecutter, but those two ids may not be the same.
        This data service takes a single parameter, namely the id of the chip (an integer) and returns a single dictionary containing the current speed, temperature and number of rotations of the diecutter it is attached to.
        The keys of the dictionary are ""speed"", ""temperature"" and ""rotations"". 
        
        Example usage:
        - If the id of the chip is 123, then the data service would be called as follows:
        chip_id = 123
        current_data = GetCurrentData.call(chip_id=123)
        # get the current speed, temperature and number of rotations
        current_speed = data[""speed""]
        current_temperature = data[""temperature""]
        current_rotations = data[""rotations""]
    
        Things to keep in mind:
        - The refresh rate of the data is 1 second, i.e. the data is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - Note that the values in the dictionary represents the current values of the speed, etc. of the diecutter, they are not aggregated values.
        - Remember that the output value is a dictionary with the above specified keys, so avoid trying to access it using keys not in the above example. - input_parameters: ['chip_id:int'] - output_values: ['diecutter_current_data:dict'] - module: diecutter - class_name: GetCurrentDataFromChip","from data_services.database import GetCamera2IdFromDiecutterId
from data_services.camera2 import GetFrameFromCamera2, DetectErrorsInCardboardStackUsingCamera2
from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
import time
import threading

def pipeline_function():
    diecutter_id = 14
    results = []

    # Get the camera2 ID for the diecutter
    camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)
    
    # Get the chip ID for the diecutter
    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    
    # Function to fetch and process data for each stack
    def process_stack(index):
        frame = GetFrameFromCamera2.call(camera2_id=camera2_id)
        contains_errors = DetectErrorsInCardboardStackUsingCamera2.call(camera2_id=camera2_id, frame=frame)
        current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
        
        result = {
            'stack_index': index,
            'has_errors': contains_errors,
            'running_speed': current_data['speed'],
            'current_temperature': current_data['temperature']
        }
        results.append(result)
    
    # Create and start threads for each of the next 10 stacks
    threads = []
    for i in range(10):
        thread = threading.Thread(target=process_stack, args=(i,))
        threads.append(thread)
        thread.start()
        time.sleep(1)  # Ensure each stack is processed at least 1 second apart
    
    # Wait for all threads to complete
    for thread in threads:
        thread.join()
    
    return results","+----+---------------+--------------+-----------------+-----------------------+
|    |   stack_index | has_errors   |   running_speed |   current_temperature |
|----+---------------+--------------+-----------------+-----------------------|
|  0 |             0 | [True, 1]    |               9 |                     0 |
|  1 |             1 | [False, 0]   |               4 |                     4 |
|  2 |             2 | [False, 0]   |               4 |                     4 |
|  3 |             3 | [True, 1]    |               3 |                     3 |
|  4 |             4 | [True, 1]    |               3 |                    14 |
|  5 |             5 | [False, 0]   |               4 |                    18 |
|  6 |             6 | [False, 0]   |               6 |                    27 |
|  7 |             7 | [True, 2]    |               3 |                     0 |
|  8 |             8 | [True, 1]    |               3 |                     0 |
|  9 |             9 | [True, 2]    |               7 |                     9 |
+----+---------------+--------------+-----------------+-----------------------+","[{'stack_index': 0, 'has_errors': [True, 1], 'running_speed': 9, 'current_temperature': 0}, {'stack_index': 1, 'has_errors': [False, 0], 'running_speed': 4, 'current_temperature': 4}, {'stack_index': 2, 'has_errors': [False, 0], 'running_speed': 4, 'current_temperature': 4}, {'stack_index': 3, 'has_errors': [True, 1], 'running_speed': 3, 'current_temperature': 3}, {'stack_index': 4, 'has_errors': [True, 1], 'running_speed': 3, 'current_temperature': 14}, {'stack_index': 5, 'has_errors': [False, 0], 'running_speed': 4, 'current_temperature': 18}, {'stack_index': 6, 'has_errors': [False, 0], 'running_speed': 6, 'current_temperature': 27}, {'stack_index': 7, 'has_errors': [True, 2], 'running_speed': 3, 'current_temperature': 0}, {'stack_index': 8, 'has_errors': [True, 1], 'running_speed': 3, 'current_temperature': 0}, {'stack_index': 9, 'has_errors': [True, 2], 'running_speed': 7, 'current_temperature': 9}]","Compute a table that gives some information about the current session of diecutter 14. For each erroneous stack produced, the table should tell me (i) the type of error, (ii) the current session of the diecutter, (iii) the current speed of the diecutter, (iii) the current temperature of the diecutter and (iv) the total number of rotations until now. The table should contain data for the next 30 stacks.","from data_services.database import GetSerialCamera1IdFromDiecutterId
from data_services.database import GetSerialCamera2IdFromDiecutterId
from data_services.database import GetDiecuttersIdOfFactory

def pipeline_function():
    serial_number = 88888404

    results = []

    diecutters_ids = GetDiecuttersIdOfFactory.call()
    for diecutter_id in diecutters_ids:
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=diecutter_id)
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)
        if serial_camera1 == serial_number:
            camera_type = ""camera1""
            results.append({
                'serial number': serial_number,
                'diecutter_id': diecutter_id,
                'type': camera_type
            })
            break
        elif serial_camera2 == serial_number:
            camera_type = ""camera2""
            results.append({
                'serial number': serial_number,
                'diecutter_id': diecutter_id,
                'type': camera_type
            })
            break
    
    return results"
q4,2,"Generate a table displaying details for the upcoming ten stacks from diecutter 14, including (i) presence of errors in each stack, (ii) types of errors if any exist, (iii) current operational speed of diecutter 14, and (iv) current operating temperature of diecutter 14.","brief_description: Data service that, given the id of a camera1, provides a frame captured from that camera1. - detailed_description: Data service that, given the id of a camera1, provides a frame captured from that camera1.
        In general instances of camera1 point downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera1 (an integer) and returns a frame captured from that camera1 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera1 is 123, then the data service would be called as follows:
        camera1_id = 123
        frame = GetFrameFromCamera1.call(camera1_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int'] - output_values: ['frame:np.matrix'] - module: camera1 - class_name: GetFrameFromCamera1brief_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors and provide the type of error. - detailed_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors.
        Recall that a camera1 is a camera device that points downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera1 to use and the frame captured from that camera1.
        It returns a boolean value, True if the frame contains a cardboard with errors, False otherwise.
        Also it returns a integer value, 0 if the frame does not contain errors, 1 if the errors are of type hole and 2 if the errors are of type fold. 

        Example usage:
        - If frame is a variable containing the frame captured from the camera1 with id 123, then the data service would be called as follows:
        camera1_id = 123
        contains_errors, type_errors = DetectErrorsInCardboardUsingCamera1.call(camera1_id=123, frame=frame)

        Things to keep in mind:
        - The output is a tuple of boolean and integer, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool', 'error_type:int'] - module: camera1 - class_name: DetectErrorsInCardboardUsingCamera1brief_description: Data service that, given the id of a camera2, provides a frame captured from that camera2. - detailed_description: Data service that, given the id of a camera2, provides a frame captured from that camera2.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera2 (an integer) and returns a frame captured from that camera2 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera2 is 123, then the data service would be called as follows:
        camera2_id = 123
        frame = GetFrameFromCamera2.call(camera2_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int'] - output_values: ['frame:np.matrix'] - module: camera2 - class_name: GetFrameFromCamera2brief_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors. - detailed_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera2 to use and the frame captured from that camera2 that contains a stack of cardboards.
        It returns a boolean value, True if the frame contains a stack of cardboards with errors, False otherwise.

        Example usage:
        - If frame is a variable containing the frame captured from the camera2 with id 123, then the data service would be called as follows:
        camera2_id = 123
        contains_errors, error_type = DetectErrorsInCardboardStack.call(camera2_id=123, frame=frame)

        Things to keep in mind:
        - The output value is a boolean, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool'] - module: camera2 - class_name: DetectErrorsInCardboardStackUsingCamera2brief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera1 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera1.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera1)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera1:int'] - module: database - class_name: GetSerialCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera2 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera2.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera2)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera2:int'] - module: database - class_name: GetSerialCamera2IdFromDiecutterIdbrief_description: Data service that provides the list of id of the diecutters installed in the factory. - detailed_description: Data service that provides the id of the diecutter installed in the factory.
        The data service relies on the management database of the cardboard factory to provide the list of diecutter id.
        The data service takes no parameter and returns a list of integers, which are the id of the diecutters installed in the factory.

        Example usage:
        - The data service would be called as follows:
        diecutters_id = GetDiecuttersIdOfFactory.call()
        # assuming the diecutters id are [1, 2, 3]
        print(diecutters_id)  # [1, 2, 3]

        Things to keep in mind:
        - The diecutters id is a list of integers, so avoid trying to access it as a dictionary. - input_parameters: [] - output_values: ['diecutters_id:list'] - module: database - class_name: GetDiecuttersIdOfFactorybrief_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter.
        The data service relies on the management database of the cardboard factory to provide the chip id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the chip id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=123)
        # assuming the chip id is 456
        print(chip_id)  # 456

        Things to keep in mind:
        - The chip id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['chip_id:int'] - module: database - class_name: GetDiecutterChipIdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera1 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera1 id is 456
        print(camera1_id)  # 456

        Things to keep in mind:
        - The camera1 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera1_id:int'] - module: database - class_name: GetCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera2 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera2 id is 456
        print(camera2_id)  # 456

        Things to keep in mind:
        - The camera2 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera2_id:int'] - module: database - class_name: GetCamera2IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter.
        The data service relies on the management database of the cardboard factory to provide the session id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the current session id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=123)
        # assuming the session id is 456
        print(session_id)  # 456

        Things to keep in mind:
        - The session id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['session_id:int'] - module: database - class_name: GetCurrentSessionIdFromDiecutterIdbrief_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip. - detailed_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip.
        In general each diecutter has exactly one chip embedded into it, and each chip is uniquely identified by an integer id. 
        This means that the chip id has a one-to-one correspondence with the id of the diecutter, but those two ids may not be the same.
        This data service takes a single parameter, namely the id of the chip (an integer) and returns a single dictionary containing the current speed, temperature and number of rotations of the diecutter it is attached to.
        The keys of the dictionary are ""speed"", ""temperature"" and ""rotations"". 
        
        Example usage:
        - If the id of the chip is 123, then the data service would be called as follows:
        chip_id = 123
        current_data = GetCurrentData.call(chip_id=123)
        # get the current speed, temperature and number of rotations
        current_speed = data[""speed""]
        current_temperature = data[""temperature""]
        current_rotations = data[""rotations""]
    
        Things to keep in mind:
        - The refresh rate of the data is 1 second, i.e. the data is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - Note that the values in the dictionary represents the current values of the speed, etc. of the diecutter, they are not aggregated values.
        - Remember that the output value is a dictionary with the above specified keys, so avoid trying to access it using keys not in the above example. - input_parameters: ['chip_id:int'] - output_values: ['diecutter_current_data:dict'] - module: diecutter - class_name: GetCurrentDataFromChip","from data_services.database import GetCamera2IdFromDiecutterId, GetDiecutterChipIdFromDiecutterId
from data_services.camera2 import GetFrameFromCamera2, DetectErrorsInCardboardStackUsingCamera2
from data_services.diecutter import GetCurrentDataFromChip
import time

def pipeline_function():
    diecutter_id = 14
    results = []
    
    # Get the camera2 ID and chip ID for diecutter 14
    camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)
    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    
    # Get current operational data from the chip
    operational_data = GetCurrentDataFromChip.call(chip_id=chip_id)
    current_speed = operational_data[""speed""]
    current_temperature = operational_data[""temperature""]
    
    # Collect data for the next 10 stacks
    for _ in range(10):
        frame = GetFrameFromCamera2.call(camera2_id=camera2_id)
        contains_errors = DetectErrorsInCardboardStackUsingCamera2.call(camera2_id=camera2_id, frame=frame)
        
        stack_details = {
            ""presence_of_errors"": contains_errors,
            ""current_operational_speed"": current_speed,
            ""current_operating_temperature"": current_temperature
        }
        results.append(stack_details)
        
        # Wait for 1 second to get the next stack (as per camera refresh rate)
        time.sleep(1)
    
    return results","+----+----------------------+-----------------------------+---------------------------------+
|    | presence_of_errors   |   current_operational_speed |   current_operating_temperature |
|----+----------------------+-----------------------------+---------------------------------|
|  0 | [True, 1]            |                           9 |                               0 |
|  1 | [False, 0]           |                           9 |                               0 |
|  2 | [False, 0]           |                           9 |                               0 |
|  3 | [True, 1]            |                           9 |                               0 |
|  4 | [True, 1]            |                           9 |                               0 |
|  5 | [False, 0]           |                           9 |                               0 |
|  6 | [False, 0]           |                           9 |                               0 |
|  7 | [True, 2]            |                           9 |                               0 |
|  8 | [True, 1]            |                           9 |                               0 |
|  9 | [True, 2]            |                           9 |                               0 |
+----+----------------------+-----------------------------+---------------------------------+","[{'presence_of_errors': [True, 1], 'current_operational_speed': 9, 'current_operating_temperature': 0}, {'presence_of_errors': [False, 0], 'current_operational_speed': 9, 'current_operating_temperature': 0}, {'presence_of_errors': [False, 0], 'current_operational_speed': 9, 'current_operating_temperature': 0}, {'presence_of_errors': [True, 1], 'current_operational_speed': 9, 'current_operating_temperature': 0}, {'presence_of_errors': [True, 1], 'current_operational_speed': 9, 'current_operating_temperature': 0}, {'presence_of_errors': [False, 0], 'current_operational_speed': 9, 'current_operating_temperature': 0}, {'presence_of_errors': [False, 0], 'current_operational_speed': 9, 'current_operating_temperature': 0}, {'presence_of_errors': [True, 2], 'current_operational_speed': 9, 'current_operating_temperature': 0}, {'presence_of_errors': [True, 1], 'current_operational_speed': 9, 'current_operating_temperature': 0}, {'presence_of_errors': [True, 2], 'current_operational_speed': 9, 'current_operating_temperature': 0}]","Compute a table that gives some information about the current session of diecutter 14. For each erroneous stack produced, the table should tell me (i) the type of error, (ii) the current session of the diecutter, (iii) the current speed of the diecutter, (iii) the current temperature of the diecutter and (iv) the total number of rotations until now. The table should contain data for the next 30 stacks.","from data_services.database import GetSerialCamera1IdFromDiecutterId
from data_services.database import GetSerialCamera2IdFromDiecutterId
from data_services.database import GetDiecuttersIdOfFactory

def pipeline_function():
    serial_number = 88888404

    results = []

    diecutters_ids = GetDiecuttersIdOfFactory.call()
    for diecutter_id in diecutters_ids:
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=diecutter_id)
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)
        if serial_camera1 == serial_number:
            camera_type = ""camera1""
            results.append({
                'serial number': serial_number,
                'diecutter_id': diecutter_id,
                'type': camera_type
            })
            break
        elif serial_camera2 == serial_number:
            camera_type = ""camera2""
            results.append({
                'serial number': serial_number,
                'diecutter_id': diecutter_id,
                'type': camera_type
            })
            break
    
    return results"
q4,3,"Create a table detailing key aspects of the current operating session for diecutter 14. For each of the next 10 stacks processed, the table should include: (i) presence of any errors in the stack, (ii) the specific type of error if present, (iii) the operational speed of the diecutter at the time, and (iv) the diecutters temperature during production.","brief_description: Data service that, given the id of a camera1, provides a frame captured from that camera1. - detailed_description: Data service that, given the id of a camera1, provides a frame captured from that camera1.
        In general instances of camera1 point downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera1 (an integer) and returns a frame captured from that camera1 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera1 is 123, then the data service would be called as follows:
        camera1_id = 123
        frame = GetFrameFromCamera1.call(camera1_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int'] - output_values: ['frame:np.matrix'] - module: camera1 - class_name: GetFrameFromCamera1brief_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors and provide the type of error. - detailed_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors.
        Recall that a camera1 is a camera device that points downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera1 to use and the frame captured from that camera1.
        It returns a boolean value, True if the frame contains a cardboard with errors, False otherwise.
        Also it returns a integer value, 0 if the frame does not contain errors, 1 if the errors are of type hole and 2 if the errors are of type fold. 

        Example usage:
        - If frame is a variable containing the frame captured from the camera1 with id 123, then the data service would be called as follows:
        camera1_id = 123
        contains_errors, type_errors = DetectErrorsInCardboardUsingCamera1.call(camera1_id=123, frame=frame)

        Things to keep in mind:
        - The output is a tuple of boolean and integer, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool', 'error_type:int'] - module: camera1 - class_name: DetectErrorsInCardboardUsingCamera1brief_description: Data service that, given the id of a camera2, provides a frame captured from that camera2. - detailed_description: Data service that, given the id of a camera2, provides a frame captured from that camera2.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera2 (an integer) and returns a frame captured from that camera2 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera2 is 123, then the data service would be called as follows:
        camera2_id = 123
        frame = GetFrameFromCamera2.call(camera2_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int'] - output_values: ['frame:np.matrix'] - module: camera2 - class_name: GetFrameFromCamera2brief_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors. - detailed_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera2 to use and the frame captured from that camera2 that contains a stack of cardboards.
        It returns a boolean value, True if the frame contains a stack of cardboards with errors, False otherwise.

        Example usage:
        - If frame is a variable containing the frame captured from the camera2 with id 123, then the data service would be called as follows:
        camera2_id = 123
        contains_errors, error_type = DetectErrorsInCardboardStack.call(camera2_id=123, frame=frame)

        Things to keep in mind:
        - The output value is a boolean, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool'] - module: camera2 - class_name: DetectErrorsInCardboardStackUsingCamera2brief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera1 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera1.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera1)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera1:int'] - module: database - class_name: GetSerialCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera2 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera2.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera2)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera2:int'] - module: database - class_name: GetSerialCamera2IdFromDiecutterIdbrief_description: Data service that provides the list of id of the diecutters installed in the factory. - detailed_description: Data service that provides the id of the diecutter installed in the factory.
        The data service relies on the management database of the cardboard factory to provide the list of diecutter id.
        The data service takes no parameter and returns a list of integers, which are the id of the diecutters installed in the factory.

        Example usage:
        - The data service would be called as follows:
        diecutters_id = GetDiecuttersIdOfFactory.call()
        # assuming the diecutters id are [1, 2, 3]
        print(diecutters_id)  # [1, 2, 3]

        Things to keep in mind:
        - The diecutters id is a list of integers, so avoid trying to access it as a dictionary. - input_parameters: [] - output_values: ['diecutters_id:list'] - module: database - class_name: GetDiecuttersIdOfFactorybrief_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter.
        The data service relies on the management database of the cardboard factory to provide the chip id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the chip id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=123)
        # assuming the chip id is 456
        print(chip_id)  # 456

        Things to keep in mind:
        - The chip id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['chip_id:int'] - module: database - class_name: GetDiecutterChipIdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera1 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera1 id is 456
        print(camera1_id)  # 456

        Things to keep in mind:
        - The camera1 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera1_id:int'] - module: database - class_name: GetCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera2 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera2 id is 456
        print(camera2_id)  # 456

        Things to keep in mind:
        - The camera2 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera2_id:int'] - module: database - class_name: GetCamera2IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter.
        The data service relies on the management database of the cardboard factory to provide the session id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the current session id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=123)
        # assuming the session id is 456
        print(session_id)  # 456

        Things to keep in mind:
        - The session id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['session_id:int'] - module: database - class_name: GetCurrentSessionIdFromDiecutterIdbrief_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip. - detailed_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip.
        In general each diecutter has exactly one chip embedded into it, and each chip is uniquely identified by an integer id. 
        This means that the chip id has a one-to-one correspondence with the id of the diecutter, but those two ids may not be the same.
        This data service takes a single parameter, namely the id of the chip (an integer) and returns a single dictionary containing the current speed, temperature and number of rotations of the diecutter it is attached to.
        The keys of the dictionary are ""speed"", ""temperature"" and ""rotations"". 
        
        Example usage:
        - If the id of the chip is 123, then the data service would be called as follows:
        chip_id = 123
        current_data = GetCurrentData.call(chip_id=123)
        # get the current speed, temperature and number of rotations
        current_speed = data[""speed""]
        current_temperature = data[""temperature""]
        current_rotations = data[""rotations""]
    
        Things to keep in mind:
        - The refresh rate of the data is 1 second, i.e. the data is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - Note that the values in the dictionary represents the current values of the speed, etc. of the diecutter, they are not aggregated values.
        - Remember that the output value is a dictionary with the above specified keys, so avoid trying to access it using keys not in the above example. - input_parameters: ['chip_id:int'] - output_values: ['diecutter_current_data:dict'] - module: diecutter - class_name: GetCurrentDataFromChip","from data_services.database import GetCamera2IdFromDiecutterId, GetCurrentSessionIdFromDiecutterId, GetDiecutterChipIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
from data_services.camera2 import GetFrameFromCamera2, DetectErrorsInCardboardStackUsingCamera2
import time

def pipeline_function():
    diecutter_id = 14
    results = []
    
    # Get the camera2 ID for the diecutter
    camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)
    
    # Get the current session ID for the diecutter
    session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=diecutter_id)
    
    # Get the chip ID for the diecutter
    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    
    # Get current operational data from the chip
    operational_data = GetCurrentDataFromChip.call(chip_id=chip_id)
    
    # Process the next 10 stacks
    for _ in range(10):
        # Get the frame from camera2
        frame = GetFrameFromCamera2.call(camera2_id=camera2_id)
        
        # Detect errors in the stack
        contains_errors, error_type = DetectErrorsInCardboardStackUsingCamera2.call(camera2_id=camera2_id, frame=frame)
        
        # Map error type to descriptive string
        error_description = ""none""
        if error_type == 1:
            error_description = ""hole""
        elif error_type == 2:
            error_description = ""fold""
        
        # Append the result for this stack
        results.append({
            ""session_id"": session_id,
            ""contains_errors"": contains_errors,
            ""error_type"": error_description,
            ""operational_speed"": operational_data[""speed""],
            ""temperature"": operational_data[""temperature""]
        })
        
        # Wait for 1 second to get the next stack
        time.sleep(1)
    
    return results","+----+--------------+-------------------+--------------+---------------------+---------------+
|    |   session_id | contains_errors   | error_type   |   operational_speed |   temperature |
|----+--------------+-------------------+--------------+---------------------+---------------|
|  0 |           88 | True              | hole         |                   9 |             0 |
|  1 |           88 | False             | none         |                   9 |             0 |
|  2 |           88 | False             | none         |                   9 |             0 |
|  3 |           88 | True              | hole         |                   9 |             0 |
|  4 |           88 | True              | hole         |                   9 |             0 |
|  5 |           88 | False             | none         |                   9 |             0 |
|  6 |           88 | False             | none         |                   9 |             0 |
|  7 |           88 | True              | fold         |                   9 |             0 |
|  8 |           88 | True              | hole         |                   9 |             0 |
|  9 |           88 | True              | fold         |                   9 |             0 |
+----+--------------+-------------------+--------------+---------------------+---------------+","[{'session_id': 88, 'contains_errors': True, 'error_type': 'hole', 'operational_speed': 9, 'temperature': 0}, {'session_id': 88, 'contains_errors': False, 'error_type': 'none', 'operational_speed': 9, 'temperature': 0}, {'session_id': 88, 'contains_errors': False, 'error_type': 'none', 'operational_speed': 9, 'temperature': 0}, {'session_id': 88, 'contains_errors': True, 'error_type': 'hole', 'operational_speed': 9, 'temperature': 0}, {'session_id': 88, 'contains_errors': True, 'error_type': 'hole', 'operational_speed': 9, 'temperature': 0}, {'session_id': 88, 'contains_errors': False, 'error_type': 'none', 'operational_speed': 9, 'temperature': 0}, {'session_id': 88, 'contains_errors': False, 'error_type': 'none', 'operational_speed': 9, 'temperature': 0}, {'session_id': 88, 'contains_errors': True, 'error_type': 'fold', 'operational_speed': 9, 'temperature': 0}, {'session_id': 88, 'contains_errors': True, 'error_type': 'hole', 'operational_speed': 9, 'temperature': 0}, {'session_id': 88, 'contains_errors': True, 'error_type': 'fold', 'operational_speed': 9, 'temperature': 0}]","Compute a table that gives some information about the current session of diecutter 14. For each erroneous stack produced, the table should tell me (i) the type of error, (ii) the current session of the diecutter, (iii) the current speed of the diecutter, (iii) the current temperature of the diecutter and (iv) the total number of rotations until now. The table should contain data for the next 30 stacks.","from data_services.database import GetSerialCamera1IdFromDiecutterId
from data_services.database import GetSerialCamera2IdFromDiecutterId
from data_services.database import GetDiecuttersIdOfFactory

def pipeline_function():
    serial_number = 88888404

    results = []

    diecutters_ids = GetDiecuttersIdOfFactory.call()
    for diecutter_id in diecutters_ids:
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=diecutter_id)
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)
        if serial_camera1 == serial_number:
            camera_type = ""camera1""
            results.append({
                'serial number': serial_number,
                'diecutter_id': diecutter_id,
                'type': camera_type
            })
            break
        elif serial_camera2 == serial_number:
            camera_type = ""camera2""
            results.append({
                'serial number': serial_number,
                'diecutter_id': diecutter_id,
                'type': camera_type
            })
            break
    
    return results"
q4,4,"Generate a table detailing specifics for the ongoing session of diecutter 14, including the following for the upcoming ten stacks: (i) presence of errors in each stack, (ii) error type if applicable, (iii) the operating speed of the diecutter, and (iv) the diecutter's current temperature.","brief_description: Data service that, given the id of a camera1, provides a frame captured from that camera1. - detailed_description: Data service that, given the id of a camera1, provides a frame captured from that camera1.
        In general instances of camera1 point downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera1 (an integer) and returns a frame captured from that camera1 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera1 is 123, then the data service would be called as follows:
        camera1_id = 123
        frame = GetFrameFromCamera1.call(camera1_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int'] - output_values: ['frame:np.matrix'] - module: camera1 - class_name: GetFrameFromCamera1brief_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors and provide the type of error. - detailed_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors.
        Recall that a camera1 is a camera device that points downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera1 to use and the frame captured from that camera1.
        It returns a boolean value, True if the frame contains a cardboard with errors, False otherwise.
        Also it returns a integer value, 0 if the frame does not contain errors, 1 if the errors are of type hole and 2 if the errors are of type fold. 

        Example usage:
        - If frame is a variable containing the frame captured from the camera1 with id 123, then the data service would be called as follows:
        camera1_id = 123
        contains_errors, type_errors = DetectErrorsInCardboardUsingCamera1.call(camera1_id=123, frame=frame)

        Things to keep in mind:
        - The output is a tuple of boolean and integer, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool', 'error_type:int'] - module: camera1 - class_name: DetectErrorsInCardboardUsingCamera1brief_description: Data service that, given the id of a camera2, provides a frame captured from that camera2. - detailed_description: Data service that, given the id of a camera2, provides a frame captured from that camera2.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera2 (an integer) and returns a frame captured from that camera2 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera2 is 123, then the data service would be called as follows:
        camera2_id = 123
        frame = GetFrameFromCamera2.call(camera2_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int'] - output_values: ['frame:np.matrix'] - module: camera2 - class_name: GetFrameFromCamera2brief_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors. - detailed_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera2 to use and the frame captured from that camera2 that contains a stack of cardboards.
        It returns a boolean value, True if the frame contains a stack of cardboards with errors, False otherwise.

        Example usage:
        - If frame is a variable containing the frame captured from the camera2 with id 123, then the data service would be called as follows:
        camera2_id = 123
        contains_errors, error_type = DetectErrorsInCardboardStack.call(camera2_id=123, frame=frame)

        Things to keep in mind:
        - The output value is a boolean, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool'] - module: camera2 - class_name: DetectErrorsInCardboardStackUsingCamera2brief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera1 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera1.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera1)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera1:int'] - module: database - class_name: GetSerialCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera2 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera2.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera2)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera2:int'] - module: database - class_name: GetSerialCamera2IdFromDiecutterIdbrief_description: Data service that provides the list of id of the diecutters installed in the factory. - detailed_description: Data service that provides the id of the diecutter installed in the factory.
        The data service relies on the management database of the cardboard factory to provide the list of diecutter id.
        The data service takes no parameter and returns a list of integers, which are the id of the diecutters installed in the factory.

        Example usage:
        - The data service would be called as follows:
        diecutters_id = GetDiecuttersIdOfFactory.call()
        # assuming the diecutters id are [1, 2, 3]
        print(diecutters_id)  # [1, 2, 3]

        Things to keep in mind:
        - The diecutters id is a list of integers, so avoid trying to access it as a dictionary. - input_parameters: [] - output_values: ['diecutters_id:list'] - module: database - class_name: GetDiecuttersIdOfFactorybrief_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter.
        The data service relies on the management database of the cardboard factory to provide the chip id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the chip id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=123)
        # assuming the chip id is 456
        print(chip_id)  # 456

        Things to keep in mind:
        - The chip id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['chip_id:int'] - module: database - class_name: GetDiecutterChipIdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera1 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera1 id is 456
        print(camera1_id)  # 456

        Things to keep in mind:
        - The camera1 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera1_id:int'] - module: database - class_name: GetCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera2 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera2 id is 456
        print(camera2_id)  # 456

        Things to keep in mind:
        - The camera2 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera2_id:int'] - module: database - class_name: GetCamera2IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter.
        The data service relies on the management database of the cardboard factory to provide the session id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the current session id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=123)
        # assuming the session id is 456
        print(session_id)  # 456

        Things to keep in mind:
        - The session id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['session_id:int'] - module: database - class_name: GetCurrentSessionIdFromDiecutterIdbrief_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip. - detailed_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip.
        In general each diecutter has exactly one chip embedded into it, and each chip is uniquely identified by an integer id. 
        This means that the chip id has a one-to-one correspondence with the id of the diecutter, but those two ids may not be the same.
        This data service takes a single parameter, namely the id of the chip (an integer) and returns a single dictionary containing the current speed, temperature and number of rotations of the diecutter it is attached to.
        The keys of the dictionary are ""speed"", ""temperature"" and ""rotations"". 
        
        Example usage:
        - If the id of the chip is 123, then the data service would be called as follows:
        chip_id = 123
        current_data = GetCurrentData.call(chip_id=123)
        # get the current speed, temperature and number of rotations
        current_speed = data[""speed""]
        current_temperature = data[""temperature""]
        current_rotations = data[""rotations""]
    
        Things to keep in mind:
        - The refresh rate of the data is 1 second, i.e. the data is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - Note that the values in the dictionary represents the current values of the speed, etc. of the diecutter, they are not aggregated values.
        - Remember that the output value is a dictionary with the above specified keys, so avoid trying to access it using keys not in the above example. - input_parameters: ['chip_id:int'] - output_values: ['diecutter_current_data:dict'] - module: diecutter - class_name: GetCurrentDataFromChip","from data_services.database import GetCurrentSessionIdFromDiecutterId, GetCamera2IdFromDiecutterId, GetDiecutterChipIdFromDiecutterId
from data_services.camera2 import GetFrameFromCamera2, DetectErrorsInCardboardStackUsingCamera2
from data_services.diecutter import GetCurrentDataFromChip
import time

def pipeline_function():
    diecutter_id = 14
    results = []
    
    # Get the current session ID for the diecutter
    session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=diecutter_id)
    
    # Get the camera2 ID associated with the diecutter
    camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)
    
    # Get the chip ID from the diecutter to fetch operating data
    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    
    # Get current operating data from the chip
    operating_data = GetCurrentDataFromChip.call(chip_id=chip_id)
    current_speed = operating_data['speed']
    current_temperature = operating_data['temperature']
    
    # Analyze the upcoming ten stacks
    for _ in range(10):
        # Capture a frame from camera2
        frame = GetFrameFromCamera2.call(camera2_id=camera2_id)
        
        # Detect errors in the stack
        contains_errors, error_type = DetectErrorsInCardboardStackUsingCamera2.call(camera2_id=camera2_id, frame=frame)
        
        # Map error type to descriptive string
        error_description = ""none""
        if error_type == 1:
            error_description = ""hole""
        elif error_type == 2:
            error_description = ""fold""
        
        # Append the result for this stack
        results.append({
            'session_id': session_id,
            'contains_errors': contains_errors,
            'error_type': error_description,
            'operating_speed': current_speed,
            'current_temperature': current_temperature
        })
        
        # Wait for 1 second to get the next stack
        time.sleep(1)
    
    return results","+----+--------------+-------------------+--------------+-------------------+-----------------------+
|    |   session_id | contains_errors   | error_type   |   operating_speed |   current_temperature |
|----+--------------+-------------------+--------------+-------------------+-----------------------|
|  0 |           88 | True              | hole         |                 9 |                     0 |
|  1 |           88 | False             | none         |                 9 |                     0 |
|  2 |           88 | False             | none         |                 9 |                     0 |
|  3 |           88 | True              | hole         |                 9 |                     0 |
|  4 |           88 | True              | hole         |                 9 |                     0 |
|  5 |           88 | False             | none         |                 9 |                     0 |
|  6 |           88 | False             | none         |                 9 |                     0 |
|  7 |           88 | True              | fold         |                 9 |                     0 |
|  8 |           88 | True              | hole         |                 9 |                     0 |
|  9 |           88 | True              | fold         |                 9 |                     0 |
+----+--------------+-------------------+--------------+-------------------+-----------------------+","[{'session_id': 88, 'contains_errors': True, 'error_type': 'hole', 'operating_speed': 9, 'current_temperature': 0}, {'session_id': 88, 'contains_errors': False, 'error_type': 'none', 'operating_speed': 9, 'current_temperature': 0}, {'session_id': 88, 'contains_errors': False, 'error_type': 'none', 'operating_speed': 9, 'current_temperature': 0}, {'session_id': 88, 'contains_errors': True, 'error_type': 'hole', 'operating_speed': 9, 'current_temperature': 0}, {'session_id': 88, 'contains_errors': True, 'error_type': 'hole', 'operating_speed': 9, 'current_temperature': 0}, {'session_id': 88, 'contains_errors': False, 'error_type': 'none', 'operating_speed': 9, 'current_temperature': 0}, {'session_id': 88, 'contains_errors': False, 'error_type': 'none', 'operating_speed': 9, 'current_temperature': 0}, {'session_id': 88, 'contains_errors': True, 'error_type': 'fold', 'operating_speed': 9, 'current_temperature': 0}, {'session_id': 88, 'contains_errors': True, 'error_type': 'hole', 'operating_speed': 9, 'current_temperature': 0}, {'session_id': 88, 'contains_errors': True, 'error_type': 'fold', 'operating_speed': 9, 'current_temperature': 0}]","Compute a table that gives some information about the current session of diecutter 14. For each erroneous stack produced, the table should tell me (i) the type of error, (ii) the current session of the diecutter, (iii) the current speed of the diecutter, (iii) the current temperature of the diecutter and (iv) the total number of rotations until now. The table should contain data for the next 30 stacks.","from data_services.database import GetSerialCamera1IdFromDiecutterId
from data_services.database import GetSerialCamera2IdFromDiecutterId
from data_services.database import GetDiecuttersIdOfFactory

def pipeline_function():
    serial_number = 88888404

    results = []

    diecutters_ids = GetDiecuttersIdOfFactory.call()
    for diecutter_id in diecutters_ids:
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=diecutter_id)
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)
        if serial_camera1 == serial_number:
            camera_type = ""camera1""
            results.append({
                'serial number': serial_number,
                'diecutter_id': diecutter_id,
                'type': camera_type
            })
            break
        elif serial_camera2 == serial_number:
            camera_type = ""camera2""
            results.append({
                'serial number': serial_number,
                'diecutter_id': diecutter_id,
                'type': camera_type
            })
            break
    
    return results"
q4,5,"Generate a table that displays details for the ongoing session of diecutter 14. For each of the next 10 stacks produced, the table should include: (i) whether the stack has errors, (ii) the error type if there are errors, (iii) the operating speed of the diecutter, and (iv) the operating temperature of the diecutter.","brief_description: Data service that, given the id of a camera1, provides a frame captured from that camera1. - detailed_description: Data service that, given the id of a camera1, provides a frame captured from that camera1.
        In general instances of camera1 point downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera1 (an integer) and returns a frame captured from that camera1 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera1 is 123, then the data service would be called as follows:
        camera1_id = 123
        frame = GetFrameFromCamera1.call(camera1_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int'] - output_values: ['frame:np.matrix'] - module: camera1 - class_name: GetFrameFromCamera1brief_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors and provide the type of error. - detailed_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors.
        Recall that a camera1 is a camera device that points downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera1 to use and the frame captured from that camera1.
        It returns a boolean value, True if the frame contains a cardboard with errors, False otherwise.
        Also it returns a integer value, 0 if the frame does not contain errors, 1 if the errors are of type hole and 2 if the errors are of type fold. 

        Example usage:
        - If frame is a variable containing the frame captured from the camera1 with id 123, then the data service would be called as follows:
        camera1_id = 123
        contains_errors, type_errors = DetectErrorsInCardboardUsingCamera1.call(camera1_id=123, frame=frame)

        Things to keep in mind:
        - The output is a tuple of boolean and integer, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool', 'error_type:int'] - module: camera1 - class_name: DetectErrorsInCardboardUsingCamera1brief_description: Data service that, given the id of a camera2, provides a frame captured from that camera2. - detailed_description: Data service that, given the id of a camera2, provides a frame captured from that camera2.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera2 (an integer) and returns a frame captured from that camera2 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera2 is 123, then the data service would be called as follows:
        camera2_id = 123
        frame = GetFrameFromCamera2.call(camera2_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int'] - output_values: ['frame:np.matrix'] - module: camera2 - class_name: GetFrameFromCamera2brief_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors. - detailed_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera2 to use and the frame captured from that camera2 that contains a stack of cardboards.
        It returns a boolean value, True if the frame contains a stack of cardboards with errors, False otherwise.

        Example usage:
        - If frame is a variable containing the frame captured from the camera2 with id 123, then the data service would be called as follows:
        camera2_id = 123
        contains_errors, error_type = DetectErrorsInCardboardStack.call(camera2_id=123, frame=frame)

        Things to keep in mind:
        - The output value is a boolean, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool'] - module: camera2 - class_name: DetectErrorsInCardboardStackUsingCamera2brief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera1 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera1.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera1)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera1:int'] - module: database - class_name: GetSerialCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera2 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera2.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera2)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera2:int'] - module: database - class_name: GetSerialCamera2IdFromDiecutterIdbrief_description: Data service that provides the list of id of the diecutters installed in the factory. - detailed_description: Data service that provides the id of the diecutter installed in the factory.
        The data service relies on the management database of the cardboard factory to provide the list of diecutter id.
        The data service takes no parameter and returns a list of integers, which are the id of the diecutters installed in the factory.

        Example usage:
        - The data service would be called as follows:
        diecutters_id = GetDiecuttersIdOfFactory.call()
        # assuming the diecutters id are [1, 2, 3]
        print(diecutters_id)  # [1, 2, 3]

        Things to keep in mind:
        - The diecutters id is a list of integers, so avoid trying to access it as a dictionary. - input_parameters: [] - output_values: ['diecutters_id:list'] - module: database - class_name: GetDiecuttersIdOfFactorybrief_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter.
        The data service relies on the management database of the cardboard factory to provide the chip id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the chip id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=123)
        # assuming the chip id is 456
        print(chip_id)  # 456

        Things to keep in mind:
        - The chip id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['chip_id:int'] - module: database - class_name: GetDiecutterChipIdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera1 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera1 id is 456
        print(camera1_id)  # 456

        Things to keep in mind:
        - The camera1 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera1_id:int'] - module: database - class_name: GetCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera2 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera2 id is 456
        print(camera2_id)  # 456

        Things to keep in mind:
        - The camera2 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera2_id:int'] - module: database - class_name: GetCamera2IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter.
        The data service relies on the management database of the cardboard factory to provide the session id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the current session id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=123)
        # assuming the session id is 456
        print(session_id)  # 456

        Things to keep in mind:
        - The session id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['session_id:int'] - module: database - class_name: GetCurrentSessionIdFromDiecutterIdbrief_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip. - detailed_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip.
        In general each diecutter has exactly one chip embedded into it, and each chip is uniquely identified by an integer id. 
        This means that the chip id has a one-to-one correspondence with the id of the diecutter, but those two ids may not be the same.
        This data service takes a single parameter, namely the id of the chip (an integer) and returns a single dictionary containing the current speed, temperature and number of rotations of the diecutter it is attached to.
        The keys of the dictionary are ""speed"", ""temperature"" and ""rotations"". 
        
        Example usage:
        - If the id of the chip is 123, then the data service would be called as follows:
        chip_id = 123
        current_data = GetCurrentData.call(chip_id=123)
        # get the current speed, temperature and number of rotations
        current_speed = data[""speed""]
        current_temperature = data[""temperature""]
        current_rotations = data[""rotations""]
    
        Things to keep in mind:
        - The refresh rate of the data is 1 second, i.e. the data is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - Note that the values in the dictionary represents the current values of the speed, etc. of the diecutter, they are not aggregated values.
        - Remember that the output value is a dictionary with the above specified keys, so avoid trying to access it using keys not in the above example. - input_parameters: ['chip_id:int'] - output_values: ['diecutter_current_data:dict'] - module: diecutter - class_name: GetCurrentDataFromChip","from data_services.database import GetCamera2IdFromDiecutterId
from data_services.database import GetCurrentSessionIdFromDiecutterId
from data_services.database import GetDiecutterChipIdFromDiecutterId
from data_services.diecutter import GetCurrentDataFromChip
from data_services.camera2 import GetFrameFromCamera2
from data_services.camera2 import DetectErrorsInCardboardStackUsingCamera2
import time

def pipeline_function():
    diecutter_id = 14
    results = []

    # Get the camera2 ID for the diecutter
    camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)
    
    # Get the current session ID for the diecutter
    session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=diecutter_id)
    
    # Get the chip ID for the diecutter
    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    
    # Get the current data from the chip
    current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
    
    # Collect data for the next 10 stacks
    for _ in range(10):
        # Get the frame from camera2
        frame = GetFrameFromCamera2.call(camera2_id=camera2_id)
        
        # Detect errors in the cardboard stack
        contains_errors, error_type = DetectErrorsInCardboardStackUsingCamera2.call(camera2_id=camera2_id, frame=frame)
        
        # Map error type to descriptive string
        error_description = ""none"" if error_type == 0 else (""hole"" if error_type == 1 else ""fold"")
        
        # Append the result for this stack
        results.append({
            'session_id': session_id,
            'has_errors': contains_errors,
            'error_type': error_description if contains_errors else ""none"",
            'operating_speed': current_data['speed'],
            'operating_temperature': current_data['temperature']
        })
        
        # Wait for 1 second to get the next stack
        time.sleep(1)
    
    return results","+----+--------------+--------------+--------------+-------------------+-------------------------+
|    |   session_id | has_errors   | error_type   |   operating_speed |   operating_temperature |
|----+--------------+--------------+--------------+-------------------+-------------------------|
|  0 |           88 | True         | hole         |                 9 |                       0 |
|  1 |           88 | False        | none         |                 9 |                       0 |
|  2 |           88 | False        | none         |                 9 |                       0 |
|  3 |           88 | True         | hole         |                 9 |                       0 |
|  4 |           88 | True         | hole         |                 9 |                       0 |
|  5 |           88 | False        | none         |                 9 |                       0 |
|  6 |           88 | False        | none         |                 9 |                       0 |
|  7 |           88 | True         | fold         |                 9 |                       0 |
|  8 |           88 | True         | hole         |                 9 |                       0 |
|  9 |           88 | True         | fold         |                 9 |                       0 |
+----+--------------+--------------+--------------+-------------------+-------------------------+","[{'session_id': 88, 'has_errors': True, 'error_type': 'hole', 'operating_speed': 9, 'operating_temperature': 0}, {'session_id': 88, 'has_errors': False, 'error_type': 'none', 'operating_speed': 9, 'operating_temperature': 0}, {'session_id': 88, 'has_errors': False, 'error_type': 'none', 'operating_speed': 9, 'operating_temperature': 0}, {'session_id': 88, 'has_errors': True, 'error_type': 'hole', 'operating_speed': 9, 'operating_temperature': 0}, {'session_id': 88, 'has_errors': True, 'error_type': 'hole', 'operating_speed': 9, 'operating_temperature': 0}, {'session_id': 88, 'has_errors': False, 'error_type': 'none', 'operating_speed': 9, 'operating_temperature': 0}, {'session_id': 88, 'has_errors': False, 'error_type': 'none', 'operating_speed': 9, 'operating_temperature': 0}, {'session_id': 88, 'has_errors': True, 'error_type': 'fold', 'operating_speed': 9, 'operating_temperature': 0}, {'session_id': 88, 'has_errors': True, 'error_type': 'hole', 'operating_speed': 9, 'operating_temperature': 0}, {'session_id': 88, 'has_errors': True, 'error_type': 'fold', 'operating_speed': 9, 'operating_temperature': 0}]","Compute a table that gives some information about the current session of diecutter 14. For each erroneous stack produced, the table should tell me (i) the type of error, (ii) the current session of the diecutter, (iii) the current speed of the diecutter, (iii) the current temperature of the diecutter and (iv) the total number of rotations until now. The table should contain data for the next 30 stacks.","from data_services.database import GetSerialCamera1IdFromDiecutterId
from data_services.database import GetSerialCamera2IdFromDiecutterId
from data_services.database import GetDiecuttersIdOfFactory

def pipeline_function():
    serial_number = 88888404

    results = []

    diecutters_ids = GetDiecuttersIdOfFactory.call()
    for diecutter_id in diecutters_ids:
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=diecutter_id)
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)
        if serial_camera1 == serial_number:
            camera_type = ""camera1""
            results.append({
                'serial number': serial_number,
                'diecutter_id': diecutter_id,
                'type': camera_type
            })
            break
        elif serial_camera2 == serial_number:
            camera_type = ""camera2""
            results.append({
                'serial number': serial_number,
                'diecutter_id': diecutter_id,
                'type': camera_type
            })
            break
    
    return results"
q4,6,"Generate a table detailing the ongoing session of diecutter 14. For each of the next 10 stacks, the table should display: (i) presence of errors in the stack, (ii) type of error if applicable, (iii) current operational speed of diecutter 14, and (iv) present temperature of the diecutter.","brief_description: Data service that, given the id of a camera1, provides a frame captured from that camera1. - detailed_description: Data service that, given the id of a camera1, provides a frame captured from that camera1.
        In general instances of camera1 point downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera1 (an integer) and returns a frame captured from that camera1 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera1 is 123, then the data service would be called as follows:
        camera1_id = 123
        frame = GetFrameFromCamera1.call(camera1_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int'] - output_values: ['frame:np.matrix'] - module: camera1 - class_name: GetFrameFromCamera1brief_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors and provide the type of error. - detailed_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors.
        Recall that a camera1 is a camera device that points downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera1 to use and the frame captured from that camera1.
        It returns a boolean value, True if the frame contains a cardboard with errors, False otherwise.
        Also it returns a integer value, 0 if the frame does not contain errors, 1 if the errors are of type hole and 2 if the errors are of type fold. 

        Example usage:
        - If frame is a variable containing the frame captured from the camera1 with id 123, then the data service would be called as follows:
        camera1_id = 123
        contains_errors, type_errors = DetectErrorsInCardboardUsingCamera1.call(camera1_id=123, frame=frame)

        Things to keep in mind:
        - The output is a tuple of boolean and integer, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool', 'error_type:int'] - module: camera1 - class_name: DetectErrorsInCardboardUsingCamera1brief_description: Data service that, given the id of a camera2, provides a frame captured from that camera2. - detailed_description: Data service that, given the id of a camera2, provides a frame captured from that camera2.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera2 (an integer) and returns a frame captured from that camera2 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera2 is 123, then the data service would be called as follows:
        camera2_id = 123
        frame = GetFrameFromCamera2.call(camera2_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int'] - output_values: ['frame:np.matrix'] - module: camera2 - class_name: GetFrameFromCamera2brief_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors. - detailed_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera2 to use and the frame captured from that camera2 that contains a stack of cardboards.
        It returns a boolean value, True if the frame contains a stack of cardboards with errors, False otherwise.

        Example usage:
        - If frame is a variable containing the frame captured from the camera2 with id 123, then the data service would be called as follows:
        camera2_id = 123
        contains_errors, error_type = DetectErrorsInCardboardStack.call(camera2_id=123, frame=frame)

        Things to keep in mind:
        - The output value is a boolean, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool'] - module: camera2 - class_name: DetectErrorsInCardboardStackUsingCamera2brief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera1 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera1.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera1)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera1:int'] - module: database - class_name: GetSerialCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera2 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera2.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera2)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera2:int'] - module: database - class_name: GetSerialCamera2IdFromDiecutterIdbrief_description: Data service that provides the list of id of the diecutters installed in the factory. - detailed_description: Data service that provides the id of the diecutter installed in the factory.
        The data service relies on the management database of the cardboard factory to provide the list of diecutter id.
        The data service takes no parameter and returns a list of integers, which are the id of the diecutters installed in the factory.

        Example usage:
        - The data service would be called as follows:
        diecutters_id = GetDiecuttersIdOfFactory.call()
        # assuming the diecutters id are [1, 2, 3]
        print(diecutters_id)  # [1, 2, 3]

        Things to keep in mind:
        - The diecutters id is a list of integers, so avoid trying to access it as a dictionary. - input_parameters: [] - output_values: ['diecutters_id:list'] - module: database - class_name: GetDiecuttersIdOfFactorybrief_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter.
        The data service relies on the management database of the cardboard factory to provide the chip id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the chip id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=123)
        # assuming the chip id is 456
        print(chip_id)  # 456

        Things to keep in mind:
        - The chip id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['chip_id:int'] - module: database - class_name: GetDiecutterChipIdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera1 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera1 id is 456
        print(camera1_id)  # 456

        Things to keep in mind:
        - The camera1 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera1_id:int'] - module: database - class_name: GetCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera2 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera2 id is 456
        print(camera2_id)  # 456

        Things to keep in mind:
        - The camera2 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera2_id:int'] - module: database - class_name: GetCamera2IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter.
        The data service relies on the management database of the cardboard factory to provide the session id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the current session id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=123)
        # assuming the session id is 456
        print(session_id)  # 456

        Things to keep in mind:
        - The session id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['session_id:int'] - module: database - class_name: GetCurrentSessionIdFromDiecutterIdbrief_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip. - detailed_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip.
        In general each diecutter has exactly one chip embedded into it, and each chip is uniquely identified by an integer id. 
        This means that the chip id has a one-to-one correspondence with the id of the diecutter, but those two ids may not be the same.
        This data service takes a single parameter, namely the id of the chip (an integer) and returns a single dictionary containing the current speed, temperature and number of rotations of the diecutter it is attached to.
        The keys of the dictionary are ""speed"", ""temperature"" and ""rotations"". 
        
        Example usage:
        - If the id of the chip is 123, then the data service would be called as follows:
        chip_id = 123
        current_data = GetCurrentData.call(chip_id=123)
        # get the current speed, temperature and number of rotations
        current_speed = data[""speed""]
        current_temperature = data[""temperature""]
        current_rotations = data[""rotations""]
    
        Things to keep in mind:
        - The refresh rate of the data is 1 second, i.e. the data is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - Note that the values in the dictionary represents the current values of the speed, etc. of the diecutter, they are not aggregated values.
        - Remember that the output value is a dictionary with the above specified keys, so avoid trying to access it using keys not in the above example. - input_parameters: ['chip_id:int'] - output_values: ['diecutter_current_data:dict'] - module: diecutter - class_name: GetCurrentDataFromChip","from data_services.database import GetCamera2IdFromDiecutterId, GetCurrentSessionIdFromDiecutterId, GetDiecutterChipIdFromDiecutterId
from data_services.camera2 import GetFrameFromCamera2, DetectErrorsInCardboardStackUsingCamera2
from data_services.diecutter import GetCurrentDataFromChip
import time

def pipeline_function():
    diecutter_id = 14
    results = []
    
    # Get the camera2 ID for the diecutter
    camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)
    
    # Get the current session ID for the diecutter
    session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=diecutter_id)
    
    # Get the chip ID for the diecutter
    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    
    # Get current operational data from the chip
    current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
    current_speed = current_data[""speed""]
    current_temperature = current_data[""temperature""]
    
    # Analyze the next 10 stacks
    for _ in range(10):
        # Get the frame from camera2
        frame = GetFrameFromCamera2.call(camera2_id=camera2_id)
        
        # Detect errors in the stack
        contains_errors = DetectErrorsInCardboardStackUsingCamera2.call(camera2_id=camera2_id, frame=frame)
        
        # Prepare the error type description
        error_type_description = ""None"" if not contains_errors else ""Detected""
        
        # Append the result for this stack
        results.append({
            ""presence_of_errors"": contains_errors,
            ""type_of_error"": error_type_description,
            ""current_operational_speed"": current_speed,
            ""present_temperature"": current_temperature
        })
        
        # Wait for 1 second to get the next stack
        time.sleep(1)
    
    return results","+----+----------------------+-----------------+-----------------------------+-----------------------+
|    | presence_of_errors   | type_of_error   |   current_operational_speed |   present_temperature |
|----+----------------------+-----------------+-----------------------------+-----------------------|
|  0 | [True, 1]            | Detected        |                           9 |                     0 |
|  1 | [False, 0]           | Detected        |                           9 |                     0 |
|  2 | [False, 0]           | Detected        |                           9 |                     0 |
|  3 | [True, 1]            | Detected        |                           9 |                     0 |
|  4 | [True, 1]            | Detected        |                           9 |                     0 |
|  5 | [False, 0]           | Detected        |                           9 |                     0 |
|  6 | [False, 0]           | Detected        |                           9 |                     0 |
|  7 | [True, 2]            | Detected        |                           9 |                     0 |
|  8 | [True, 1]            | Detected        |                           9 |                     0 |
|  9 | [True, 2]            | Detected        |                           9 |                     0 |
+----+----------------------+-----------------+-----------------------------+-----------------------+","[{'presence_of_errors': [True, 1], 'type_of_error': 'Detected', 'current_operational_speed': 9, 'present_temperature': 0}, {'presence_of_errors': [False, 0], 'type_of_error': 'Detected', 'current_operational_speed': 9, 'present_temperature': 0}, {'presence_of_errors': [False, 0], 'type_of_error': 'Detected', 'current_operational_speed': 9, 'present_temperature': 0}, {'presence_of_errors': [True, 1], 'type_of_error': 'Detected', 'current_operational_speed': 9, 'present_temperature': 0}, {'presence_of_errors': [True, 1], 'type_of_error': 'Detected', 'current_operational_speed': 9, 'present_temperature': 0}, {'presence_of_errors': [False, 0], 'type_of_error': 'Detected', 'current_operational_speed': 9, 'present_temperature': 0}, {'presence_of_errors': [False, 0], 'type_of_error': 'Detected', 'current_operational_speed': 9, 'present_temperature': 0}, {'presence_of_errors': [True, 2], 'type_of_error': 'Detected', 'current_operational_speed': 9, 'present_temperature': 0}, {'presence_of_errors': [True, 1], 'type_of_error': 'Detected', 'current_operational_speed': 9, 'present_temperature': 0}, {'presence_of_errors': [True, 2], 'type_of_error': 'Detected', 'current_operational_speed': 9, 'present_temperature': 0}]","Compute a table that gives some information about the current session of diecutter 14. For each erroneous stack produced, the table should tell me (i) the type of error, (ii) the current session of the diecutter, (iii) the current speed of the diecutter, (iii) the current temperature of the diecutter and (iv) the total number of rotations until now. The table should contain data for the next 30 stacks.","from data_services.database import GetSerialCamera1IdFromDiecutterId
from data_services.database import GetSerialCamera2IdFromDiecutterId
from data_services.database import GetDiecuttersIdOfFactory

def pipeline_function():
    serial_number = 88888404

    results = []

    diecutters_ids = GetDiecuttersIdOfFactory.call()
    for diecutter_id in diecutters_ids:
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=diecutter_id)
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)
        if serial_camera1 == serial_number:
            camera_type = ""camera1""
            results.append({
                'serial number': serial_number,
                'diecutter_id': diecutter_id,
                'type': camera_type
            })
            break
        elif serial_camera2 == serial_number:
            camera_type = ""camera2""
            results.append({
                'serial number': serial_number,
                'diecutter_id': diecutter_id,
                'type': camera_type
            })
            break
    
    return results"
q4,7,"Generate a table detailing information on the current session for diecutter 14. For each of the upcoming 10 stacks, the table should provide (i) whether the stack has any errors, (ii) the specific type of error if present, (iii) the operating speed of the diecutter, and (iv) the present temperature of the diecutter.","brief_description: Data service that, given the id of a camera1, provides a frame captured from that camera1. - detailed_description: Data service that, given the id of a camera1, provides a frame captured from that camera1.
        In general instances of camera1 point downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera1 (an integer) and returns a frame captured from that camera1 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera1 is 123, then the data service would be called as follows:
        camera1_id = 123
        frame = GetFrameFromCamera1.call(camera1_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int'] - output_values: ['frame:np.matrix'] - module: camera1 - class_name: GetFrameFromCamera1brief_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors and provide the type of error. - detailed_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors.
        Recall that a camera1 is a camera device that points downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera1 to use and the frame captured from that camera1.
        It returns a boolean value, True if the frame contains a cardboard with errors, False otherwise.
        Also it returns a integer value, 0 if the frame does not contain errors, 1 if the errors are of type hole and 2 if the errors are of type fold. 

        Example usage:
        - If frame is a variable containing the frame captured from the camera1 with id 123, then the data service would be called as follows:
        camera1_id = 123
        contains_errors, type_errors = DetectErrorsInCardboardUsingCamera1.call(camera1_id=123, frame=frame)

        Things to keep in mind:
        - The output is a tuple of boolean and integer, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool', 'error_type:int'] - module: camera1 - class_name: DetectErrorsInCardboardUsingCamera1brief_description: Data service that, given the id of a camera2, provides a frame captured from that camera2. - detailed_description: Data service that, given the id of a camera2, provides a frame captured from that camera2.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera2 (an integer) and returns a frame captured from that camera2 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera2 is 123, then the data service would be called as follows:
        camera2_id = 123
        frame = GetFrameFromCamera2.call(camera2_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int'] - output_values: ['frame:np.matrix'] - module: camera2 - class_name: GetFrameFromCamera2brief_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors. - detailed_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera2 to use and the frame captured from that camera2 that contains a stack of cardboards.
        It returns a boolean value, True if the frame contains a stack of cardboards with errors, False otherwise.

        Example usage:
        - If frame is a variable containing the frame captured from the camera2 with id 123, then the data service would be called as follows:
        camera2_id = 123
        contains_errors, error_type = DetectErrorsInCardboardStack.call(camera2_id=123, frame=frame)

        Things to keep in mind:
        - The output value is a boolean, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool'] - module: camera2 - class_name: DetectErrorsInCardboardStackUsingCamera2brief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera1 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera1.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera1)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera1:int'] - module: database - class_name: GetSerialCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera2 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera2.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera2)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera2:int'] - module: database - class_name: GetSerialCamera2IdFromDiecutterIdbrief_description: Data service that provides the list of id of the diecutters installed in the factory. - detailed_description: Data service that provides the id of the diecutter installed in the factory.
        The data service relies on the management database of the cardboard factory to provide the list of diecutter id.
        The data service takes no parameter and returns a list of integers, which are the id of the diecutters installed in the factory.

        Example usage:
        - The data service would be called as follows:
        diecutters_id = GetDiecuttersIdOfFactory.call()
        # assuming the diecutters id are [1, 2, 3]
        print(diecutters_id)  # [1, 2, 3]

        Things to keep in mind:
        - The diecutters id is a list of integers, so avoid trying to access it as a dictionary. - input_parameters: [] - output_values: ['diecutters_id:list'] - module: database - class_name: GetDiecuttersIdOfFactorybrief_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter.
        The data service relies on the management database of the cardboard factory to provide the chip id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the chip id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=123)
        # assuming the chip id is 456
        print(chip_id)  # 456

        Things to keep in mind:
        - The chip id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['chip_id:int'] - module: database - class_name: GetDiecutterChipIdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera1 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera1 id is 456
        print(camera1_id)  # 456

        Things to keep in mind:
        - The camera1 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera1_id:int'] - module: database - class_name: GetCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera2 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera2 id is 456
        print(camera2_id)  # 456

        Things to keep in mind:
        - The camera2 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera2_id:int'] - module: database - class_name: GetCamera2IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter.
        The data service relies on the management database of the cardboard factory to provide the session id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the current session id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=123)
        # assuming the session id is 456
        print(session_id)  # 456

        Things to keep in mind:
        - The session id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['session_id:int'] - module: database - class_name: GetCurrentSessionIdFromDiecutterIdbrief_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip. - detailed_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip.
        In general each diecutter has exactly one chip embedded into it, and each chip is uniquely identified by an integer id. 
        This means that the chip id has a one-to-one correspondence with the id of the diecutter, but those two ids may not be the same.
        This data service takes a single parameter, namely the id of the chip (an integer) and returns a single dictionary containing the current speed, temperature and number of rotations of the diecutter it is attached to.
        The keys of the dictionary are ""speed"", ""temperature"" and ""rotations"". 
        
        Example usage:
        - If the id of the chip is 123, then the data service would be called as follows:
        chip_id = 123
        current_data = GetCurrentData.call(chip_id=123)
        # get the current speed, temperature and number of rotations
        current_speed = data[""speed""]
        current_temperature = data[""temperature""]
        current_rotations = data[""rotations""]
    
        Things to keep in mind:
        - The refresh rate of the data is 1 second, i.e. the data is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - Note that the values in the dictionary represents the current values of the speed, etc. of the diecutter, they are not aggregated values.
        - Remember that the output value is a dictionary with the above specified keys, so avoid trying to access it using keys not in the above example. - input_parameters: ['chip_id:int'] - output_values: ['diecutter_current_data:dict'] - module: diecutter - class_name: GetCurrentDataFromChip","from data_services.database import GetCamera1IdFromDiecutterId, GetCamera2IdFromDiecutterId, GetCurrentSessionIdFromDiecutterId, GetDiecutterChipIdFromDiecutterId
from data_services.camera1 import GetFrameFromCamera1, DetectErrorsInCardboardUsingCamera1
from data_services.camera2 import GetFrameFromCamera2, DetectErrorsInCardboardStackUsingCamera2
from data_services.diecutter import GetCurrentDataFromChip
import time
import threading

def pipeline_function():
    diecutter_id = 14
    num_stacks = 10
    results = []

    # Get camera IDs and chip ID
    camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=diecutter_id)
    camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)
    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=diecutter_id)

    # Get current data from the chip
    current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
    current_speed = current_data[""speed""]
    current_temperature = current_data[""temperature""]

    # Function to process each stack
    def process_stack(index):
        frame = GetFrameFromCamera2.call(camera2_id=camera2_id)
        contains_errors = DetectErrorsInCardboardStackUsingCamera2.call(camera2_id=camera2_id, frame=frame)
        stack_info = {
            ""stack_index"": index,
            ""has_errors"": contains_errors,
            ""operating_speed"": current_speed,
            ""temperature"": current_temperature
        }
        results.append(stack_info)

    # Create threads for each stack
    threads = []
    for i in range(num_stacks):
        thread = threading.Thread(target=process_stack, args=(i,))
        threads.append(thread)
        thread.start()
        time.sleep(1)  # Ensure each stack is processed at different times

    # Wait for all threads to complete
    for thread in threads:
        thread.join()

    return results","+----+---------------+--------------+-------------------+---------------+
|    |   stack_index | has_errors   |   operating_speed |   temperature |
|----+---------------+--------------+-------------------+---------------|
|  0 |             0 | [True, 1]    |                 9 |             0 |
|  1 |             1 | [False, 0]   |                 9 |             0 |
|  2 |             2 | [False, 0]   |                 9 |             0 |
|  3 |             3 | [True, 1]    |                 9 |             0 |
|  4 |             4 | [True, 1]    |                 9 |             0 |
|  5 |             5 | [False, 0]   |                 9 |             0 |
|  6 |             6 | [False, 0]   |                 9 |             0 |
|  7 |             7 | [True, 2]    |                 9 |             0 |
|  8 |             8 | [True, 1]    |                 9 |             0 |
|  9 |             9 | [True, 2]    |                 9 |             0 |
+----+---------------+--------------+-------------------+---------------+","[{'stack_index': 0, 'has_errors': [True, 1], 'operating_speed': 9, 'temperature': 0}, {'stack_index': 1, 'has_errors': [False, 0], 'operating_speed': 9, 'temperature': 0}, {'stack_index': 2, 'has_errors': [False, 0], 'operating_speed': 9, 'temperature': 0}, {'stack_index': 3, 'has_errors': [True, 1], 'operating_speed': 9, 'temperature': 0}, {'stack_index': 4, 'has_errors': [True, 1], 'operating_speed': 9, 'temperature': 0}, {'stack_index': 5, 'has_errors': [False, 0], 'operating_speed': 9, 'temperature': 0}, {'stack_index': 6, 'has_errors': [False, 0], 'operating_speed': 9, 'temperature': 0}, {'stack_index': 7, 'has_errors': [True, 2], 'operating_speed': 9, 'temperature': 0}, {'stack_index': 8, 'has_errors': [True, 1], 'operating_speed': 9, 'temperature': 0}, {'stack_index': 9, 'has_errors': [True, 2], 'operating_speed': 9, 'temperature': 0}]","Compute a table that gives some information about the current session of diecutter 14. For each erroneous stack produced, the table should tell me (i) the type of error, (ii) the current session of the diecutter, (iii) the current speed of the diecutter, (iii) the current temperature of the diecutter and (iv) the total number of rotations until now. The table should contain data for the next 30 stacks.","from data_services.database import GetSerialCamera1IdFromDiecutterId
from data_services.database import GetSerialCamera2IdFromDiecutterId
from data_services.database import GetDiecuttersIdOfFactory

def pipeline_function():
    serial_number = 88888404

    results = []

    diecutters_ids = GetDiecuttersIdOfFactory.call()
    for diecutter_id in diecutters_ids:
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=diecutter_id)
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)
        if serial_camera1 == serial_number:
            camera_type = ""camera1""
            results.append({
                'serial number': serial_number,
                'diecutter_id': diecutter_id,
                'type': camera_type
            })
            break
        elif serial_camera2 == serial_number:
            camera_type = ""camera2""
            results.append({
                'serial number': serial_number,
                'diecutter_id': diecutter_id,
                'type': camera_type
            })
            break
    
    return results"
q4,8,"Generate a table displaying details for the upcoming 10 stacks from diecutter 14. The table should include: (i) whether any stack has errors, (ii) the specific error type if present, (iii) the current operating speed of diecutter 14, and (iv) the present operating temperature of diecutter 14.","brief_description: Data service that, given the id of a camera1, provides a frame captured from that camera1. - detailed_description: Data service that, given the id of a camera1, provides a frame captured from that camera1.
        In general instances of camera1 point downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera1 (an integer) and returns a frame captured from that camera1 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera1 is 123, then the data service would be called as follows:
        camera1_id = 123
        frame = GetFrameFromCamera1.call(camera1_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int'] - output_values: ['frame:np.matrix'] - module: camera1 - class_name: GetFrameFromCamera1brief_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors and provide the type of error. - detailed_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors.
        Recall that a camera1 is a camera device that points downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera1 to use and the frame captured from that camera1.
        It returns a boolean value, True if the frame contains a cardboard with errors, False otherwise.
        Also it returns a integer value, 0 if the frame does not contain errors, 1 if the errors are of type hole and 2 if the errors are of type fold. 

        Example usage:
        - If frame is a variable containing the frame captured from the camera1 with id 123, then the data service would be called as follows:
        camera1_id = 123
        contains_errors, type_errors = DetectErrorsInCardboardUsingCamera1.call(camera1_id=123, frame=frame)

        Things to keep in mind:
        - The output is a tuple of boolean and integer, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool', 'error_type:int'] - module: camera1 - class_name: DetectErrorsInCardboardUsingCamera1brief_description: Data service that, given the id of a camera2, provides a frame captured from that camera2. - detailed_description: Data service that, given the id of a camera2, provides a frame captured from that camera2.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera2 (an integer) and returns a frame captured from that camera2 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera2 is 123, then the data service would be called as follows:
        camera2_id = 123
        frame = GetFrameFromCamera2.call(camera2_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int'] - output_values: ['frame:np.matrix'] - module: camera2 - class_name: GetFrameFromCamera2brief_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors. - detailed_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera2 to use and the frame captured from that camera2 that contains a stack of cardboards.
        It returns a boolean value, True if the frame contains a stack of cardboards with errors, False otherwise.

        Example usage:
        - If frame is a variable containing the frame captured from the camera2 with id 123, then the data service would be called as follows:
        camera2_id = 123
        contains_errors, error_type = DetectErrorsInCardboardStack.call(camera2_id=123, frame=frame)

        Things to keep in mind:
        - The output value is a boolean, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool'] - module: camera2 - class_name: DetectErrorsInCardboardStackUsingCamera2brief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera1 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera1.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera1)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera1:int'] - module: database - class_name: GetSerialCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera2 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera2.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera2)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera2:int'] - module: database - class_name: GetSerialCamera2IdFromDiecutterIdbrief_description: Data service that provides the list of id of the diecutters installed in the factory. - detailed_description: Data service that provides the id of the diecutter installed in the factory.
        The data service relies on the management database of the cardboard factory to provide the list of diecutter id.
        The data service takes no parameter and returns a list of integers, which are the id of the diecutters installed in the factory.

        Example usage:
        - The data service would be called as follows:
        diecutters_id = GetDiecuttersIdOfFactory.call()
        # assuming the diecutters id are [1, 2, 3]
        print(diecutters_id)  # [1, 2, 3]

        Things to keep in mind:
        - The diecutters id is a list of integers, so avoid trying to access it as a dictionary. - input_parameters: [] - output_values: ['diecutters_id:list'] - module: database - class_name: GetDiecuttersIdOfFactorybrief_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter.
        The data service relies on the management database of the cardboard factory to provide the chip id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the chip id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=123)
        # assuming the chip id is 456
        print(chip_id)  # 456

        Things to keep in mind:
        - The chip id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['chip_id:int'] - module: database - class_name: GetDiecutterChipIdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera1 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera1 id is 456
        print(camera1_id)  # 456

        Things to keep in mind:
        - The camera1 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera1_id:int'] - module: database - class_name: GetCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera2 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera2 id is 456
        print(camera2_id)  # 456

        Things to keep in mind:
        - The camera2 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera2_id:int'] - module: database - class_name: GetCamera2IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter.
        The data service relies on the management database of the cardboard factory to provide the session id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the current session id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=123)
        # assuming the session id is 456
        print(session_id)  # 456

        Things to keep in mind:
        - The session id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['session_id:int'] - module: database - class_name: GetCurrentSessionIdFromDiecutterIdbrief_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip. - detailed_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip.
        In general each diecutter has exactly one chip embedded into it, and each chip is uniquely identified by an integer id. 
        This means that the chip id has a one-to-one correspondence with the id of the diecutter, but those two ids may not be the same.
        This data service takes a single parameter, namely the id of the chip (an integer) and returns a single dictionary containing the current speed, temperature and number of rotations of the diecutter it is attached to.
        The keys of the dictionary are ""speed"", ""temperature"" and ""rotations"". 
        
        Example usage:
        - If the id of the chip is 123, then the data service would be called as follows:
        chip_id = 123
        current_data = GetCurrentData.call(chip_id=123)
        # get the current speed, temperature and number of rotations
        current_speed = data[""speed""]
        current_temperature = data[""temperature""]
        current_rotations = data[""rotations""]
    
        Things to keep in mind:
        - The refresh rate of the data is 1 second, i.e. the data is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - Note that the values in the dictionary represents the current values of the speed, etc. of the diecutter, they are not aggregated values.
        - Remember that the output value is a dictionary with the above specified keys, so avoid trying to access it using keys not in the above example. - input_parameters: ['chip_id:int'] - output_values: ['diecutter_current_data:dict'] - module: diecutter - class_name: GetCurrentDataFromChip","from data_services.database import GetCamera2IdFromDiecutterId, GetDiecutterChipIdFromDiecutterId
from data_services.camera2 import GetFrameFromCamera2, DetectErrorsInCardboardStackUsingCamera2
from data_services.diecutter import GetCurrentDataFromChip
import threading

def pipeline_function():
    diecutter_id = 14
    num_stacks = 10
    results = []

    # Get the camera2 ID and chip ID for the diecutter
    camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)
    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)

    # Get current operating data from the chip
    current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
    current_speed = current_data[""speed""]
    current_temperature = current_data[""temperature""]

    # Function to process each stack
    def process_stack(index):
        frame = GetFrameFromCamera2.call(camera2_id=camera2_id)
        contains_errors, error_type = DetectErrorsInCardboardStackUsingCamera2.call(camera2_id=camera2_id, frame=frame)
        error_type_description = ""none"" if error_type == 0 else (""hole"" if error_type == 1 else ""fold"")
        results.append({
            ""stack_index"": index,
            ""has_errors"": contains_errors,
            ""error_type"": error_type_description,
            ""current_speed"": current_speed,
            ""current_temperature"": current_temperature
        })

    # Create threads for each stack processing
    threads = []
    for i in range(num_stacks):
        thread = threading.Thread(target=process_stack, args=(i,))
        threads.append(thread)
        thread.start()

    # Wait for all threads to complete
    for thread in threads:
        thread.join()

    return results","+----+---------------+--------------+--------------+-----------------+-----------------------+
|    |   stack_index | has_errors   | error_type   |   current_speed |   current_temperature |
|----+---------------+--------------+--------------+-----------------+-----------------------|
|  0 |             1 | True         | fold         |               9 |                     0 |
|  1 |             7 | True         | hole         |               9 |                     0 |
|  2 |             2 | True         | hole         |               9 |                     0 |
|  3 |             4 | True         | hole         |               9 |                     0 |
|  4 |             6 | False        | none         |               9 |                     0 |
|  5 |             5 | True         | hole         |               9 |                     0 |
|  6 |             3 | False        | none         |               9 |                     0 |
|  7 |             9 | True         | fold         |               9 |                     0 |
|  8 |             8 | True         | fold         |               9 |                     0 |
|  9 |             0 | False        | none         |               9 |                     0 |
+----+---------------+--------------+--------------+-----------------+-----------------------+","[{'stack_index': 1, 'has_errors': True, 'error_type': 'fold', 'current_speed': 9, 'current_temperature': 0}, {'stack_index': 7, 'has_errors': True, 'error_type': 'hole', 'current_speed': 9, 'current_temperature': 0}, {'stack_index': 2, 'has_errors': True, 'error_type': 'hole', 'current_speed': 9, 'current_temperature': 0}, {'stack_index': 4, 'has_errors': True, 'error_type': 'hole', 'current_speed': 9, 'current_temperature': 0}, {'stack_index': 6, 'has_errors': False, 'error_type': 'none', 'current_speed': 9, 'current_temperature': 0}, {'stack_index': 5, 'has_errors': True, 'error_type': 'hole', 'current_speed': 9, 'current_temperature': 0}, {'stack_index': 3, 'has_errors': False, 'error_type': 'none', 'current_speed': 9, 'current_temperature': 0}, {'stack_index': 9, 'has_errors': True, 'error_type': 'fold', 'current_speed': 9, 'current_temperature': 0}, {'stack_index': 8, 'has_errors': True, 'error_type': 'fold', 'current_speed': 9, 'current_temperature': 0}, {'stack_index': 0, 'has_errors': False, 'error_type': 'none', 'current_speed': 9, 'current_temperature': 0}]","Compute a table that gives some information about the current session of diecutter 14. For each erroneous stack produced, the table should tell me (i) the type of error, (ii) the current session of the diecutter, (iii) the current speed of the diecutter, (iii) the current temperature of the diecutter and (iv) the total number of rotations until now. The table should contain data for the next 30 stacks.","from data_services.database import GetSerialCamera1IdFromDiecutterId
from data_services.database import GetSerialCamera2IdFromDiecutterId
from data_services.database import GetDiecuttersIdOfFactory

def pipeline_function():
    serial_number = 88888404

    results = []

    diecutters_ids = GetDiecuttersIdOfFactory.call()
    for diecutter_id in diecutters_ids:
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=diecutter_id)
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)
        if serial_camera1 == serial_number:
            camera_type = ""camera1""
            results.append({
                'serial number': serial_number,
                'diecutter_id': diecutter_id,
                'type': camera_type
            })
            break
        elif serial_camera2 == serial_number:
            camera_type = ""camera2""
            results.append({
                'serial number': serial_number,
                'diecutter_id': diecutter_id,
                'type': camera_type
            })
            break
    
    return results"
q4,9,"Generate a table presenting details on the ongoing operation of diecutter 14. The table should include for each of the next 10 stacks: (i) error presence, (ii) specific error types if applicable, (iii) present operating speed, and (iv) current operating temperature of the diecutter.","brief_description: Data service that, given the id of a camera1, provides a frame captured from that camera1. - detailed_description: Data service that, given the id of a camera1, provides a frame captured from that camera1.
        In general instances of camera1 point downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera1 (an integer) and returns a frame captured from that camera1 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera1 is 123, then the data service would be called as follows:
        camera1_id = 123
        frame = GetFrameFromCamera1.call(camera1_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int'] - output_values: ['frame:np.matrix'] - module: camera1 - class_name: GetFrameFromCamera1brief_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors and provide the type of error. - detailed_description: Data service that, given a frame captured from a specific camera1 and the identifier of that camera1, detects whether the frame contains a cardboard with errors.
        Recall that a camera1 is a camera device that points downwards to a conveyor belt of a specific production line that trasports single cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera1 to use and the frame captured from that camera1.
        It returns a boolean value, True if the frame contains a cardboard with errors, False otherwise.
        Also it returns a integer value, 0 if the frame does not contain errors, 1 if the errors are of type hole and 2 if the errors are of type fold. 

        Example usage:
        - If frame is a variable containing the frame captured from the camera1 with id 123, then the data service would be called as follows:
        camera1_id = 123
        contains_errors, type_errors = DetectErrorsInCardboardUsingCamera1.call(camera1_id=123, frame=frame)

        Things to keep in mind:
        - The output is a tuple of boolean and integer, so avoid trying to access it as a dictionary. - input_parameters: ['camera1_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool', 'error_type:int'] - module: camera1 - class_name: DetectErrorsInCardboardUsingCamera1brief_description: Data service that, given the id of a camera2, provides a frame captured from that camera2. - detailed_description: Data service that, given the id of a camera2, provides a frame captured from that camera2.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        The data service takes a single parameter, namely the id of the camera2 (an integer) and returns a frame captured from that camera2 as a numpy matrix.
        The matrix is a 2D array having a shape of (1080, 1920, 3) where 1080 is the height, 1920 is the width and 3 is the number of channels (RGB).

        Example usage:
        - If the id of the camera2 is 123, then the data service would be called as follows:
        camera2_id = 123
        frame = GetFrameFromCamera2.call(camera2_id=123)
        # assuming the frame is a numpy matrix
        print(frame.shape)  # (1080, 1920, 3)

        Things to keep in mind:
        - The refresh rate of the camera is 1 second, i.e. the frame is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - The frame is a numpy matrix, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int'] - output_values: ['frame:np.matrix'] - module: camera2 - class_name: GetFrameFromCamera2brief_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors. - detailed_description: Data service that, given a frame captured from a specific camera2 and the identifier of that camera2, detects whether the frame contains a stack of cardboards with errors.
        Recall that a camera2 is a camera device that points downwards to a conveyor belt of a specific production line that trasports stack of cutout cardboards produced by a specific diecutter.
        It takes two parameters, the id of the camera2 to use and the frame captured from that camera2 that contains a stack of cardboards.
        It returns a boolean value, True if the frame contains a stack of cardboards with errors, False otherwise.

        Example usage:
        - If frame is a variable containing the frame captured from the camera2 with id 123, then the data service would be called as follows:
        camera2_id = 123
        contains_errors, error_type = DetectErrorsInCardboardStack.call(camera2_id=123, frame=frame)

        Things to keep in mind:
        - The output value is a boolean, so avoid trying to access it as a dictionary. - input_parameters: ['camera2_id:int', 'frame:np.matrix'] - output_values: ['contains_errors:bool'] - module: camera2 - class_name: DetectErrorsInCardboardStackUsingCamera2brief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera1 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera1.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera1)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera1:int'] - module: database - class_name: GetSerialCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed. - detailed_description: Data service that, given the id of a diecutter, provides the serial of the camera1 installed.
        The data service relies on the management database of the cardboard factory to provide the camera2 serial.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the serial of the camera2.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the serial is 4561245
        print(serial_camera2)  # 4561245

        Things to keep in mind:
        - The serial is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['serial_camera2:int'] - module: database - class_name: GetSerialCamera2IdFromDiecutterIdbrief_description: Data service that provides the list of id of the diecutters installed in the factory. - detailed_description: Data service that provides the id of the diecutter installed in the factory.
        The data service relies on the management database of the cardboard factory to provide the list of diecutter id.
        The data service takes no parameter and returns a list of integers, which are the id of the diecutters installed in the factory.

        Example usage:
        - The data service would be called as follows:
        diecutters_id = GetDiecuttersIdOfFactory.call()
        # assuming the diecutters id are [1, 2, 3]
        print(diecutters_id)  # [1, 2, 3]

        Things to keep in mind:
        - The diecutters id is a list of integers, so avoid trying to access it as a dictionary. - input_parameters: [] - output_values: ['diecutters_id:list'] - module: database - class_name: GetDiecuttersIdOfFactorybrief_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the chip embedded into that diecutter.
        The data service relies on the management database of the cardboard factory to provide the chip id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the chip id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=123)
        # assuming the chip id is 456
        print(chip_id)  # 456

        Things to keep in mind:
        - The chip id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['chip_id:int'] - module: database - class_name: GetDiecutterChipIdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera1 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera1 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera1 id is 456
        print(camera1_id)  # 456

        Things to keep in mind:
        - The camera1 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera1_id:int'] - module: database - class_name: GetCamera1IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.
        The data service relies on the management database of the cardboard factory to provide the camera2 id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the id of the camera2 used to capture the frames of the cardboard cutouts produced by that diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=123)
        # assuming the camera2 id is 456
        print(camera2_id)  # 456

        Things to keep in mind:
        - The camera2 id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['camera2_id:int'] - module: database - class_name: GetCamera2IdFromDiecutterIdbrief_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter. - detailed_description: Data service that, given the id of a diecutter, provides the current session id of that diecutter.
        The data service relies on the management database of the cardboard factory to provide the session id.
        The data service takes a single parameter, namely the id of the diecutter (an integer) and returns a single integer, which is the current session id of the diecutter.

        Example usage:
        - If the id of the diecutter is 123, then the data service would be called as follows:
        diecutter_id = 123
        session_id = GetCurrentSessionIdFromDiecutterId.call(diecutter_id=123)
        # assuming the session id is 456
        print(session_id)  # 456

        Things to keep in mind:
        - The session id is an integer, so avoid trying to access it as a dictionary. - input_parameters: ['diecutter_id:int'] - output_values: ['session_id:int'] - module: database - class_name: GetCurrentSessionIdFromDiecutterIdbrief_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip. - detailed_description: Data service that, given a chip id of a chip embedded into a diecutter, provides the current speed, temperature and number of rotations measured by that chip.
        In general each diecutter has exactly one chip embedded into it, and each chip is uniquely identified by an integer id. 
        This means that the chip id has a one-to-one correspondence with the id of the diecutter, but those two ids may not be the same.
        This data service takes a single parameter, namely the id of the chip (an integer) and returns a single dictionary containing the current speed, temperature and number of rotations of the diecutter it is attached to.
        The keys of the dictionary are ""speed"", ""temperature"" and ""rotations"". 
        
        Example usage:
        - If the id of the chip is 123, then the data service would be called as follows:
        chip_id = 123
        current_data = GetCurrentData.call(chip_id=123)
        # get the current speed, temperature and number of rotations
        current_speed = data[""speed""]
        current_temperature = data[""temperature""]
        current_rotations = data[""rotations""]
    
        Things to keep in mind:
        - The refresh rate of the data is 1 second, i.e. the data is updated every second, so if the data service is called multiple times within a second, it will return the same value.
        - Note that the values in the dictionary represents the current values of the speed, etc. of the diecutter, they are not aggregated values.
        - Remember that the output value is a dictionary with the above specified keys, so avoid trying to access it using keys not in the above example. - input_parameters: ['chip_id:int'] - output_values: ['diecutter_current_data:dict'] - module: diecutter - class_name: GetCurrentDataFromChip","from data_services.database import GetCamera1IdFromDiecutterId, GetCamera2IdFromDiecutterId, GetDiecutterChipIdFromDiecutterId
from data_services.camera1 import GetFrameFromCamera1, DetectErrorsInCardboardUsingCamera1
from data_services.camera2 import GetFrameFromCamera2, DetectErrorsInCardboardStackUsingCamera2
from data_services.diecutter import GetCurrentDataFromChip
import time

def pipeline_function():
    diecutter_id = 14
    results = []
    
    # Get camera IDs from diecutter ID
    camera1_id = GetCamera1IdFromDiecutterId.call(diecutter_id=diecutter_id)
    camera2_id = GetCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)
    
    # Get chip ID from diecutter ID
    chip_id = GetDiecutterChipIdFromDiecutterId.call(diecutter_id=diecutter_id)
    
    # Get current data from chip
    current_data = GetCurrentDataFromChip.call(chip_id=chip_id)
    
    # Collect data for the next 10 stacks
    for _ in range(10):
        # Get frames from both cameras
        frame_camera1 = GetFrameFromCamera1.call(camera1_id=camera1_id)
        frame_camera2 = GetFrameFromCamera2.call(camera2_id=camera2_id)
        
        # Detect errors in single cardboard and stack
        contains_errors_cardboard, error_type_cardboard = DetectErrorsInCardboardUsingCamera1.call(camera1_id=camera1_id, frame=frame_camera1)
        contains_errors_stack = DetectErrorsInCardboardStackUsingCamera2.call(camera2_id=camera2_id, frame=frame_camera2)
        
        # Map error types
        error_types = {0: ""None"", 1: ""Hole"", 2: ""Fold""}
        error_description = error_types[error_type_cardboard] if contains_errors_cardboard else ""None""
        
        # Append result for this stack
        results.append({
            ""error_presence"": contains_errors_stack,
            ""specific_error_types"": error_description,
            ""present_operating_speed"": current_data[""speed""],
            ""current_operating_temperature"": current_data[""temperature""]
        })
        
        # Wait for the next stack (simulate real-time data fetching)
        time.sleep(1)
    
    return results","+----+------------------+------------------------+---------------------------+---------------------------------+
|    | error_presence   | specific_error_types   |   present_operating_speed |   current_operating_temperature |
|----+------------------+------------------------+---------------------------+---------------------------------|
|  0 | [True, 1]        | Hole                   |                         9 |                               0 |
|  1 | [False, 0]       | Hole                   |                         9 |                               0 |
|  2 | [False, 0]       | None                   |                         9 |                               0 |
|  3 | [True, 1]        | None                   |                         9 |                               0 |
|  4 | [True, 1]        | Fold                   |                         9 |                               0 |
|  5 | [False, 0]       | Hole                   |                         9 |                               0 |
|  6 | [False, 0]       | Fold                   |                         9 |                               0 |
|  7 | [True, 2]        | Hole                   |                         9 |                               0 |
|  8 | [True, 1]        | None                   |                         9 |                               0 |
|  9 | [True, 2]        | Hole                   |                         9 |                               0 |
+----+------------------+------------------------+---------------------------+---------------------------------+","[{'error_presence': [True, 1], 'specific_error_types': 'Hole', 'present_operating_speed': 9, 'current_operating_temperature': 0}, {'error_presence': [False, 0], 'specific_error_types': 'Hole', 'present_operating_speed': 9, 'current_operating_temperature': 0}, {'error_presence': [False, 0], 'specific_error_types': 'None', 'present_operating_speed': 9, 'current_operating_temperature': 0}, {'error_presence': [True, 1], 'specific_error_types': 'None', 'present_operating_speed': 9, 'current_operating_temperature': 0}, {'error_presence': [True, 1], 'specific_error_types': 'Fold', 'present_operating_speed': 9, 'current_operating_temperature': 0}, {'error_presence': [False, 0], 'specific_error_types': 'Hole', 'present_operating_speed': 9, 'current_operating_temperature': 0}, {'error_presence': [False, 0], 'specific_error_types': 'Fold', 'present_operating_speed': 9, 'current_operating_temperature': 0}, {'error_presence': [True, 2], 'specific_error_types': 'Hole', 'present_operating_speed': 9, 'current_operating_temperature': 0}, {'error_presence': [True, 1], 'specific_error_types': 'None', 'present_operating_speed': 9, 'current_operating_temperature': 0}, {'error_presence': [True, 2], 'specific_error_types': 'Hole', 'present_operating_speed': 9, 'current_operating_temperature': 0}]","Compute a table that gives some information about the current session of diecutter 14. For each erroneous stack produced, the table should tell me (i) the type of error, (ii) the current session of the diecutter, (iii) the current speed of the diecutter, (iii) the current temperature of the diecutter and (iv) the total number of rotations until now. The table should contain data for the next 30 stacks.","from data_services.database import GetSerialCamera1IdFromDiecutterId
from data_services.database import GetSerialCamera2IdFromDiecutterId
from data_services.database import GetDiecuttersIdOfFactory

def pipeline_function():
    serial_number = 88888404

    results = []

    diecutters_ids = GetDiecuttersIdOfFactory.call()
    for diecutter_id in diecutters_ids:
        serial_camera1 = GetSerialCamera1IdFromDiecutterId.call(diecutter_id=diecutter_id)
        serial_camera2 = GetSerialCamera2IdFromDiecutterId.call(diecutter_id=diecutter_id)
        if serial_camera1 == serial_number:
            camera_type = ""camera1""
            results.append({
                'serial number': serial_number,
                'diecutter_id': diecutter_id,
                'type': camera_type
            })
            break
        elif serial_camera2 == serial_number:
            camera_type = ""camera2""
            results.append({
                'serial number': serial_number,
                'diecutter_id': diecutter_id,
                'type': camera_type
            })
            break
    
    return results"