Introduction

The Canvas Student Data Export Tool can export nearly all of a student's data from Instructure Canvas Learning Management System (Canvas LMS). This is useful when you are graduating or leaving your college or university, and would like to have a backup of all the data you had in canvas.

The tool exports all of the following data:

• Course Assignments
• Course Announcements
• Course Discussions
• Course Pages
• Course Files
• Course Modules

The tool will export your data in JSON format, and will organize it nicely into folders named for every term of every year. Example:

• Fall 2013
  • Econ 101
    • files
    • modules
    • Econ 101.json
  • English 101
    • files
    • modules
    • English 101.json
• Fall 2014
• Fall 2015
• Fall 2016
• Spring 2014
• Spring 2015
• Spring 2016
• Spring 2017
• Winter 2014
• Winter 2015
• Winter 2016
• Winter 2017
• all_output.json

Getting Started

Dependencies

To run the program, you will need the following dependencies: pip install requests pip install jsonpickle pip install canvasapi

Then run from the command line: python export.py

Configuration

These are the configuration parameters for the program:

• Canvas API URL - this is the URL of your institution, for example https://example.instructure.com
• Canvas API key - this can be created by going to Canvas and navigating to Account > Settings > Approved Integrations > New Access Token
• Canvas User ID - this can be found at https://example.instructure.com/api/v1/users/self in the id field
• Directory in which to download course information to (will be created if not present)
• List of Course IDs that should be skipped

Loading credentials from a file

To avoid manually entering credentials every time you run the program, you can create a credentials.yaml file in the same directory as the script that has the following fields:

API_URL: < URL of your institution >
API_KEY: < API Key from Canvas >
USER_ID: < User ID from Canvas >

You can then run the script as normal: python export.py

Contribute

I would love to see this script's functionality expanded and improved! I welcome all pull requests :) Thank you!