Python LTI 1.3 Template Cookiecutter

This is a cookiecutter template for creating a Python LTI 1.3 tool. It allows you to bootstrap a new project with the necessary files and structure to get started quickly.

Usage

1. Make sure you have Python installed. Then, install Cookiecutter with the instructions from the Cookiecutter Documentation. If you are on a Mac and have Homebrew, you can install Cookiecutter with the command brew install cookiecutter.

2. Go to the directory where you would like to create your project and run the following command to create a new project:

cookiecutter gh:ucfopen/cookiecutter-python-lti

You can also clone this repo and and run cookiecutter locally with:

cookiecutter /path/to/cookiecutter-python-lti/

3. Follow the prompts. See Prompts for more information on the options.

Prompts

• Select a template:
  • flask: Use the Flask Python web framework
  • django: Use the Django Python web framework
  • Depending on which option you select, not all of the below options will be presented
• project_name: The name of the project
• project_slug: The slug of the project
• author_name: The name of the author
• author_email: The email of the author
• author_github: The GitHub username of the author
• license: The license for the project. If your preferred license is not listed, select 'none' and add it manually once your project is created.
• db_type: The type of database to use
• api_access: If and how to authenticate with Canvas API. If you do not need data from Canvas, choose 'None'. If the permissions of the user of the tool are sufficient (e.g. an instructor accessing their own resources, course files, rosters, pages that they have access to), you should use OAauth 2.0. If the tool needs higher permissions (e.g. admin), you should not use OAauth 2.0, instead use a developer access key. This last option is not generally recommended unless necessary, as it is less secure.
• use_celery: Whether to use Celery for a distributed task queue (includes Redis Docker image)
• use_sentry: Whether to use Sentry for error tracking

Acknowledgements:

• Cookiecutter
• 1EdTech's LTI 1.3 Specification
• Univeristy of Central Florida's
  • Flask LTI 1.3 Template and
  • canvasapi
• Univeristy of Michigan's django-lti
• pylti1.3