First take at using multiprocessing with UCFOpen's canvasapi in Python

pool_test.py

import multiprocessing as mp 
from canvasapi import Canvas
import json

def process_submissions(assignment):

    obj = {}

    canvas = Canvas(url, key)

    course = canvas.get_course(28869)

    assignment = course.get_assignment(assignment)

    obj['id'] = assignment.id
    obj['sub_data'] = []

    submissions = assignment.get_submissions(include='user')

    for sub in submissions:
        data = json.loads(sub.to_json())
        obj['sub_data'].append((data['user_id'], data['score']))

    return obj

def main():

    # Connect with Canvas
    canvas = Canvas(url, key)

    # Get the course object
    course = canvas.get_course(course_id)

    assignments = course.get_assignments()

    # Pull only the IDs of the assignments into a list
    assignment_id_list = [item.id for item in assignments]

    # Instantiate a pool
    pool = mp.Pool(mp.cpu_count())

    # Post the list to the process function, wait for the results
    result = pool.map(process_submissions, assignment_id_list)

    print(result)

if __name__ == "__main__":
    main()