fix: fix 4524

data/clean/f_387_jenny.py

@@ -27,6 +27,9 @@ def f_387(epoch_milliseconds, seed=0):
         - 'Time': The timestamp of when the activity occurred, incrementally
                   increasing from the starting epoch time to the current time.
 
+    Raises:
+    - ValueError: If the start time is after the current system time.
+    
     Requirements:
     - pandas
     - datetime.datetime.fromtimestamp

data/clean/f_388_jenny.py

@@ -19,6 +19,9 @@ def f_388(epoch_milliseconds, seed=None):
     - sales_data (dict): Sales data for different categories over days.
     - ax (plt.Axes): The plot depicting the sales trend.
 
+    Raises:
+    - ValueError: If the start time is negative or after the current time.
+    
     Requirements:
     - random
     - datetime.datetime

data/clean/f_393_jenny.py

@@ -19,6 +19,9 @@ def f_393(days_in_past=7, random_seed=0):
                                      with 'Date' on the a-xis and 'Temperature (°C)' on the y-axis.
 
 
+    Raises:
+    ValueError: If days_in_past is less than 1.
+    
     Requirements:
     - datetime.datetime
     - datetime.timedelta

data/clean/f_394_jenny.py

@@ -18,6 +18,9 @@ def f_394(days_in_past=7):
     Returns:
     weekday (str)     : The name of the weekday (e.g., 'Monday', 'Tuesday') for the computed date.
 
+    Raises:
+    ValueError: If 'days_in_past' is negative.
+    
     Requirements:
     - datetime.datetime
     - datetime.timedelta

data/clean/f_398_jenny.py

@@ -13,7 +13,6 @@ def f_398(column, data):
     - data (list of lists): A list where each element is a list representing stock data for a single day.
                             Each inner list should contain values in the following order:
                             'Date', 'Open', 'High', 'Low', 'Close', 'Volume'.
-                            Function will raise ValueError if the structure is not as expected.
     Returns:
     - dict: A dictionary containing the calculated 'sum', 'mean', 'min' (minimum), and 'max' (maximum)
             for the specified column. If the input data is empty, 'sum' will be 0, and 'mean', 'min', and
@@ -23,6 +22,9 @@ def f_398(column, data):
     - pandas
     - numpy
 
+    Raises:
+    - ValueError: If the specified column name is not valid.
+    
     Example:
     >>> data = [[datetime(2022, 1, 1), 100, 105, 95, 102, 10000]]
     >>> results = f_398('Open', data)

data/clean/f_399_jenny.py

@@ -16,7 +16,7 @@ def f_399(column, data):
 
     Returns:
     tuple: A tuple containing:
-        - dict: A dictionary with the sum, mean, min, and max of the column.
+        - dict: A dictionary with the 'sum', 'mean', 'min', and 'max' of the column.
         - Axes object: The pie chart visualizing the column data.
 
     Requirements:

data/clean/f_400_jenny.py

@@ -22,6 +22,9 @@ def f_400(column, data):
     - pandas
     - numpy
 
+    Raises:
+    - ValueError: If the quantity sold or total sales is negative.
+    
     Example:
     >>> data = [['Product A', 100, 10000], ['Product B', 150, 15000], ['Product C', 200, 20000]]
     >>> stats, plot = f_400('Total Sales', data)

data/clean/f_401_jenny.py

@@ -30,6 +30,10 @@ def f_401(column, data):
     - numpy
     - matplotlib.pyplot
 
+    Raises:
+    - KeyError: If the specified column is not valid.
+    - ValueError: If the data list is empty or if any of the numeric values for
+                    steps, calories burned, and distance walked are negative.
     Example:
     >>> data = [[datetime(2022, 1, 1), 5000, 200, 3.5],
     ...         [datetime(2022, 1, 2), 5500, 220, 4.0],

data/clean/f_4524_hanhu.py

@@ -65,34 +65,34 @@ def test_return_type(self):
         pub_key, filename, _, _ = f_4526()
         self.assertIsInstance(pub_key, rsa.PublicKey)
         self.assertIsInstance(filename, str)
-        TestCases.filenames.append(filename)
+        self.filenames.append(filename)
 
     def test_file_creation(self):
         _, filename, _, _ = f_4526()
         self.assertTrue(os.path.exists(filename))
-        TestCases.filenames.append(filename)
+        self.filenames.append(filename)
 
     def test_file_content(self):
         _, filename, _, _ = f_4526()
         with open(filename, 'r') as f:
             content = f.read()
             self.assertTrue(content)
-        TestCases.filenames.append(filename)
+        self.filenames.append(filename)
 
     def test_key_size(self):
         pub_key, filename, _, _ = f_4526()
         self.assertEqual(pub_key.n.bit_length(), 512)
-        TestCases.filenames.append(filename)
+        self.filenames.append(filename)
 
     def test_unique_file_per_call(self):
         _, filename1, _, _ = f_4526()
         _, filename2, _, _ = f_4526()
         self.assertNotEqual(filename1, filename2)
-        TestCases.filenames.extend([filename1, filename2])
+        self.filenames.extend([filename1, filename2])
 
     def test_encryption_decryption(self):
         pub_key, filename, password, nonce = f_4526()
-        TestCases.filenames.append(filename)
+        self.filenames.append(filename)
         with open(filename, 'r') as f:
             encrypted_key = b64decode(f.read())
         cipher = AES.new(password, AES.MODE_EAX, nonce=nonce)
@@ -103,7 +103,8 @@ def test_encryption_decryption(self):
 
     def tearDown(self):
         for filename in self.filenames:
-            os.remove(filename)
+            if os.path.exists(filename):
+                os.remove(filename)
 
 
 def run_tests():

data/processed/f_387_jenny_wo_doc.py

@@ -27,6 +27,9 @@ def f_519(epoch_milliseconds, seed=0):
         - 'Time': The timestamp of when the activity occurred, incrementally
                   increasing from the starting epoch time to the current time.
 
+    Raises:
+    - ValueError: If the start time is after the current system time.
+    
     Requirements:
     - pandas
     - datetime.datetime.fromtimestamp

data/processed/f_388_jenny_wo_doc.py

@@ -19,6 +19,9 @@ def f_2(epoch_milliseconds, seed=None):
     - sales_data (dict): Sales data for different categories over days.
     - ax (plt.Axes): The plot depicting the sales trend.
 
+    Raises:
+    - ValueError: If the start time is negative or after the current time.
+    
     Requirements:
     - random
     - datetime.datetime

data/processed/f_393_jenny_wo_doc.py

@@ -19,6 +19,9 @@ def f_659(days_in_past=7, random_seed=0):
                                      with 'Date' on the a-xis and 'Temperature (°C)' on the y-axis.
 
 
+    Raises:
+    ValueError: If days_in_past is less than 1.
+    
     Requirements:
     - datetime.datetime
     - datetime.timedelta

data/processed/f_394_jenny_wo_doc.py

@@ -18,6 +18,9 @@ def f_103(days_in_past=7):
     Returns:
     weekday (str)     : The name of the weekday (e.g., 'Monday', 'Tuesday') for the computed date.
 
+    Raises:
+    ValueError: If 'days_in_past' is negative.
+    
     Requirements:
     - datetime.datetime
     - datetime.timedelta

data/processed/f_398_jenny_w_doc.py

@@ -13,7 +13,6 @@ def f_581(column, data):
     - data (list of lists): A list where each element is a list representing stock data for a single day.
                             Each inner list should contain values in the following order:
                             'Date', 'Open', 'High', 'Low', 'Close', 'Volume'.
-                            Function will raise ValueError if the structure is not as expected.
     Returns:
     - dict: A dictionary containing the calculated 'sum', 'mean', 'min' (minimum), and 'max' (maximum)
             for the specified column. If the input data is empty, 'sum' will be 0, and 'mean', 'min', and
@@ -23,6 +22,9 @@ def f_581(column, data):
     - pandas
     - numpy
 
+    Raises:
+    - ValueError: If the specified column name is not valid.
+    
     Example:
     >>> data = [[datetime(2022, 1, 1), 100, 105, 95, 102, 10000]]
     >>> results = f_581('Open', data)

data/processed/f_399_jenny_w_doc.py

@@ -16,7 +16,7 @@ def f_85(column, data):
 
     Returns:
     tuple: A tuple containing:
-        - dict: A dictionary with the sum, mean, min, and max of the column.
+        - dict: A dictionary with the 'sum', 'mean', 'min', and 'max' of the column.
         - Axes object: The pie chart visualizing the column data.
 
     Requirements:

data/processed/f_400_jenny_w_doc.py

@@ -22,6 +22,9 @@ def f_256(column, data):
     - pandas
     - numpy
 
+    Raises:
+    - ValueError: If the quantity sold or total sales is negative.
+    
     Example:
     >>> data = [['Product A', 100, 10000], ['Product B', 150, 15000], ['Product C', 200, 20000]]
     >>> stats, plot = f_256('Total Sales', data)

data/processed/f_401_jenny_w_doc.py

@@ -30,6 +30,10 @@ def f_183(column, data):
     - numpy
     - matplotlib.pyplot
 
+    Raises:
+    - KeyError: If the specified column is not valid.
+    - ValueError: If the data list is empty or if any of the numeric values for
+                    steps, calories burned, and distance walked are negative.
     Example:
     >>> data = [[datetime(2022, 1, 1), 5000, 200, 3.5],
     ...         [datetime(2022, 1, 2), 5500, 220, 4.0],

data/processed/f_4524_hanhu_wo_doc.py

@@ -63,29 +63,29 @@ def test_return_type(self):
         pub_key, filename, _, _ = f_350()
         self.assertIsInstance(pub_key, rsa.PublicKey)
         self.assertIsInstance(filename, str)
-        TestCases.filenames.append(filename)
+        self.filenames.append(filename)
     def test_file_creation(self):
         _, filename, _, _ = f_350()
         self.assertTrue(os.path.exists(filename))
-        TestCases.filenames.append(filename)
+        self.filenames.append(filename)
     def test_file_content(self):
         _, filename, _, _ = f_350()
         with open(filename, 'r') as f:
             content = f.read()
             self.assertTrue(content)
-        TestCases.filenames.append(filename)
+        self.filenames.append(filename)
     def test_key_size(self):
         pub_key, filename, _, _ = f_350()
         self.assertEqual(pub_key.n.bit_length(), 512)
-        TestCases.filenames.append(filename)
+        self.filenames.append(filename)
     def test_unique_file_per_call(self):
         _, filename1, _, _ = f_350()
         _, filename2, _, _ = f_350()
         self.assertNotEqual(filename1, filename2)
-        TestCases.filenames.extend([filename1, filename2])
+        self.filenames.extend([filename1, filename2])
     def test_encryption_decryption(self):
         pub_key, filename, password, nonce = f_350()
-        TestCases.filenames.append(filename)
+        self.filenames.append(filename)
         with open(filename, 'r') as f:
             encrypted_key = b64decode(f.read())
         cipher = AES.new(password, AES.MODE_EAX, nonce=nonce)
@@ -95,4 +95,5 @@ def test_encryption_decryption(self):
         self.assertIsInstance(priv_key, rsa.PrivateKey)
     def tearDown(self):
         for filename in self.filenames:
-            os.remove(filename)
+            if os.path.exists(filename):
+                os.remove(filename)

data/raw/f_387_jenny.py

@@ -27,6 +27,9 @@ def f_387(epoch_milliseconds, seed=0):
         - 'Time': The timestamp of when the activity occurred, incrementally
                   increasing from the starting epoch time to the current time.
 
+    Raises:
+    - ValueError: If the start time is after the current system time.
+    
     Requirements:
     - pandas
     - datetime.datetime.fromtimestamp

data/raw/f_388_jenny.py

@@ -19,6 +19,9 @@ def f_388(epoch_milliseconds, seed=None):
     - sales_data (dict): Sales data for different categories over days.
     - ax (plt.Axes): The plot depicting the sales trend.
 
+    Raises:
+    - ValueError: If the start time is negative or after the current time.
+    
     Requirements:
     - random
     - datetime.datetime

data/raw/f_393_jenny.py

@@ -19,6 +19,9 @@ def f_393(days_in_past=7, random_seed=0):
                                      with 'Date' on the a-xis and 'Temperature (°C)' on the y-axis.
 
 
+    Raises:
+    ValueError: If days_in_past is less than 1.
+    
     Requirements:
     - datetime.datetime
     - datetime.timedelta

data/raw/f_394_jenny.py

@@ -18,6 +18,9 @@ def f_394(days_in_past=7):
     Returns:
     weekday (str)     : The name of the weekday (e.g., 'Monday', 'Tuesday') for the computed date.
 
+    Raises:
+    ValueError: If 'days_in_past' is negative.
+    
     Requirements:
     - datetime.datetime
     - datetime.timedelta

data/raw/f_398_jenny.py

@@ -13,7 +13,6 @@ def f_398(column, data):
     - data (list of lists): A list where each element is a list representing stock data for a single day.
                             Each inner list should contain values in the following order:
                             'Date', 'Open', 'High', 'Low', 'Close', 'Volume'.
-                            Function will raise ValueError if the structure is not as expected.
     Returns:
     - dict: A dictionary containing the calculated 'sum', 'mean', 'min' (minimum), and 'max' (maximum)
             for the specified column. If the input data is empty, 'sum' will be 0, and 'mean', 'min', and
@@ -23,6 +22,9 @@ def f_398(column, data):
     - pandas
     - numpy
 
+    Raises:
+    - ValueError: If the specified column name is not valid.
+    
     Example:
     >>> data = [[datetime(2022, 1, 1), 100, 105, 95, 102, 10000]]
     >>> results = f_398('Open', data)

data/raw/f_399_jenny.py

@@ -16,7 +16,7 @@ def f_399(column, data):
 
     Returns:
     tuple: A tuple containing:
-        - dict: A dictionary with the sum, mean, min, and max of the column.
+        - dict: A dictionary with the 'sum', 'mean', 'min', and 'max' of the column.
         - Axes object: The pie chart visualizing the column data.
 
     Requirements:

data/raw/f_400_jenny.py

@@ -22,6 +22,9 @@ def f_400(column, data):
     - pandas
     - numpy
 
+    Raises:
+    - ValueError: If the quantity sold or total sales is negative.
+    
     Example:
     >>> data = [['Product A', 100, 10000], ['Product B', 150, 15000], ['Product C', 200, 20000]]
     >>> stats, plot = f_400('Total Sales', data)

data/raw/f_401_jenny.py

@@ -30,6 +30,10 @@ def f_401(column, data):
     - numpy
     - matplotlib.pyplot
 
+    Raises:
+    - KeyError: If the specified column is not valid.
+    - ValueError: If the data list is empty or if any of the numeric values for
+                    steps, calories burned, and distance walked are negative.
     Example:
     >>> data = [[datetime(2022, 1, 1), 5000, 200, 3.5],
     ...         [datetime(2022, 1, 2), 5500, 220, 4.0],