Create script file to fetch submissions

scripts/README.md

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+# Utility Scripts
+
+## Setup
+
+1. Install requirements.
+
+> It is recommended to install packages in a virtual environment, such as with `virtualenv` or `pipenv`.
+
+```bash
+pip install pandas
+pip install requests
+```
+
+1. Obtain API Key
+
+Navigate to Campus -> Settings -> API Key. Create a new API Key, copy the value, and save it as you will need it for step 3.
+
+3. Update script with API Key and Course Slug values. To view the course slug, navigate to your course and copy the course slug after the `.../courses/` part. From the value in the address bar. For example for:
+
+```bash
+https://uofmichigan.illumidesk.com/app/courses/rob101-fa-2024/lessons/activity/8c804205-e5d7-4640-8f88-8cdbfdaf5b23
+```
+
+The course slug is `rob101-fa-2024`.
+
+## Fetch Submissions
+
+1. Run the script to fetch student submissions:
+
+```python
+python fetch_course_submissions.py
+```
+
+2. A CSV file with the results will save to the same folder where you ran your script.

scripts/fetch_submissions.py

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+import requests
+import pandas as pd
+from datetime import datetime
+
+
+COURSE_SLUG = "rob101-fa-2023"
+API_KEY = "38c47c2ad80d3a584b79601b60d9b3b36affd209"
+url = f"https://api.illumidesk.com/api/v1/courses/{COURSE_SLUG}/submissions/"
+
+headers = {
+    "accept": "application/json",
+    "Authorization": f"Token {API_KEY}",
+}
+
+# Initialize parameters for pagination
+limit = 100
+offset = 0
+all_data = []  # List to hold all fetched submissions
+
+# Continue fetching while there are more results
+while True:
+    # Create the URL with pagination parameters
+    paginated_url = f"{url}?limit={limit}&offset={offset}"
+
+    # Send the GET request
+    response = requests.get(paginated_url, headers=headers)
+
+    # Check if the request was successful
+    if response.status_code == 200:
+        # Parse the JSON response
+        data = response.json()
+        results = data.get('results', [])
+
+        # If no more results, break the loop
+        if not results:
+            break
+
+        # Append results to all_data
+        all_data.extend(results)
+
+        # Update the offset for the next request
+        offset += limit
+    else:
+        print(f"Failed to retrieve data. Status code: {response.status_code}")
+        break
+
+# Convert the data to a DataFrame
+if all_data:
+    df = pd.json_normalize(all_data)
+
+    # Generate a unique filename using the current date and time
+    timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
+    csv_file_name = f"submissions_data_{timestamp}.csv"
+
+    # Save the DataFrame to a CSV file
+    df.to_csv(csv_file_name, index=False)
+    print(f"All submissions have been saved to CSV file '{csv_file_name}'.")
+else:
+    print("No data was retrieved.")