def verify_challenge()

in lambda/app.py [0:0]

• 39 lines of code
• 7 McCabe index (conditional complexity)

def verify_challenge(challenge_id):
    if not challenge_id:
        return 422, {'message': 'Missing path parameter \'challengeId\''}
    # Looking up challenge on DynamoDB table
    item = table.get_item(Key={'id': challenge_id})
    if 'Item' not in item:
        return 404, {'message': 'Challenge not found'}
    challenge = read_item(item['Item'])
    # Getting frames from challenge
    frames = challenge['frames']
    # Invoking Rekognition with parallel threads
    with ThreadPoolExecutor(max_workers=10) as pool:
        futures = [
            pool.submit(
                detect_faces, frame
            ) for frame in frames
        ]
        frames = [r.result() for r in as_completed(futures)]
    frames.sort(key=lambda frame: frame['key'])
    # Setting up state manager
    first_state = FaceState(challenge)
    state_manager = StateManager(first_state)
    current_state_name = state_manager.get_current_state_name()
    # Processing Rekognition results with state manager
    for frame in frames:
        state_manager.process(frame)
        current_state_name = state_manager.get_current_state_name()
        if current_state_name in {"SuccessState", "FailState"}:  # Final state
            break
    # Returning result based on final state
    response = {'success': current_state_name == "SuccessState"}
    # Updating challenge on DynamoDB table
    table.update_item(
        Key={'id': challenge_id},
        UpdateExpression='set #frames = :frames, #success = :success',
        ExpressionAttributeNames={
            '#frames': 'frames',
            '#success': 'success'
        },
        ExpressionAttributeValues={
            ':frames': write_item(frames),
            ':success': response['success']
        },
        ReturnValues='NONE'
    )
    return 200, response