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Canvas LMS API Client Library

Overview
Testing
Documentation
Installation
Usage
Contributing
References

Overview

This is a library for making requests to a Canvas LMS API.

Testing

This project is tested with tox.

Run the tox command to run checks and unit tests:

$ tox

By default, this project's tox runs:

To create test coverage reports:

$ tox -e cov

Deployment

Deployment to pypi is done with tox:

$ tox -e deploy

Make sure to bump the version in setup.py before deploying.

Documentation

This project has Sphinx documentation at the following url:
https://wgwz.github.io/canvas-lms-tools/

The public Canvas LMS API documentation is also very useful:
https://canvas.instructure.com/doc/api/index.html

Installation

To install, use pip:

pip install canvas_api_client

Or clone the repo:

git clone https://github.com/lcary/canvas-lms-tools.git
cd canvas-lms-tools/canvas_api_client
python setup.py install

Usage

Adding the client as a dependency in your project's requirements.txt file is the intended way to use the client.

REPL Example

$ python
>>> from canvas_api_client.v1_client import CanvasAPIv1
>>> url = 'https://my.canvas.instance.com/api/v1/'
>>> token = '1396~xxxxxxxxxxxxxxxxxxxTHISxISxNOTxAxREALxTOKENxxxxxxxxxxxxxxxxxxxxx'
>>> api = CanvasAPIv1(url, token)
>>> l = api.get_account_blueprint_courses('1234')
>>> for r in l.json():
...     print(r['id'], r['name'])
...
49400 Course_9000_Blueprint
57600 Spring_2018_Blueprint

Script Example

This very simple example requires a few environment variables. The API URL and token should be something like:

CANVAS_API_URL=https://my.canvas.instance.com/api/v1/
CANVAS_API_TOKEN=1396~xxxxxxxxxxxxxxxxxxxTHISxISxNOTxAxREALxTOKENxxxxxxxxxxxxxxxxxxxxx

The recommended approach is to use a config file with limited read permissions instead of environment variables, but bear with me here.

Once installed in your project via pip, use as follows:

from os import environ
from pprint import pprint

from canvas_api_client.v1_client import CanvasAPIv1 

url = environ.get('CANVAS_API_URL')
token = environ.get('CANVAS_API_TOKEN')

api = CanvasAPIv1(url, token)
params = {"override_sis_stickiness": "true"}
response = api.import_sis_data('1', './courses.csv', params=params)

print('SIS Import Response:')
pprint(response.json())

CanvasAPIv1

This library is meant to be imported into your code. The CanvasAPIv1 client object requires a api_url argument and a api_token argument. The api_url should likely be defined in a configuration file, and should be the full API URL without the endpoint, e.g. https://canvas.com/api/v1/. The api_token should similarly be defined in a config file, and is the token generated in the Canvas settings page.

The CanvasAPIv1 client object can also be called with any of the following optional requirements. They can be overridden by arguments to the individual methods.

  • per_page: passed to the Canvas API in requests that receive paginated responses. Sets the page size; the default is 100, the largest size respected by the Canvas API.

  • flatten_response: If the Canvas API returns a paginated response, return the results as a simple list.

  • is_sis_course_id: Prepend 'sis_course_id' to the course ID argument when passing it to the Canvas API. This allows you to use your SIS course IDs instead of Canvas serial numbers.

  • is_sis_account_id: Prepend 'sis_account_id' to the account ID argument when passing it to the Canvas API. This allows you to use your SIS account IDs instead of Canvas serial numbers.

There are a few helper functions that assist in sharing code between methods in CanvasAPIv1 which are worth pointing out. For example, there is a method for each request type, such as ._get() for GET requests, etc. Each one of these request type methods invokes self._send_request() which takes a number of parameters and returns a requests.Response object by default. Most of the public methods of the api client thus return a Response object, so the caller will have access to the typical response methods, such as response.json().

I say "by default", because it is possible to pass in your own requests library. This is not necessarily recommended; this capability only exists for the sake of easy dependency injection in unit testing as well as compatibility with libraries such as requests-oauthlib.

Refer to the client interface documentation for more information.

Contributing

Building Wheels

Building the wheel:

python setup.py bdist_wheel

Installing Wheels

How to install the client for testing:

pip uninstall canvas_api_client || echo "Already uninstalled."
pip install --no-index --find-links=dist canvas_api_client

Alternatively, install by specifying the full or relative path to the .whl file:

pip install --no-index /path/to/canvas-lms-tools/canvas_api_client/dist/canvas_api_client-<version>-py2.py3-none-any.whl

(You may need to pip install wheel first if you are installing from another project. Consult stack overflow for more help.)

Sphinx Docs

Creating the docs:

cd docs
pip install -r requirements.txt
pip install canvas_api_client
make html
open build/html/index.html

Deploying the docs to GitHub pages:

git checkout master
git pull
git branch -D gh-pages
git checkout -b gh-pages
rm -rf ./*
touch .nojekyll
git checkout master canvas_api_client/docs/
< build the docs as above > 
mv canvas_api_client/docs/build/html/* ./
rm -rf canvas_api_client
git add -A
git commit
git push -f origin gh-pages

For more info see the GitHub Pages documentation, the Sphinx docs, or the following script docs.

References

This project was originally created with the following "cookiecutter" tool:
https://github.com/wdm0006/cookiecutter-pipproject