Overview
Testing
Documentation
Installation
Usage
Contributing
References
This is a library for making requests to a Canvas LMS API.
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 to pypi is done with tox:
$ tox -e deploy
Make sure to bump the version in setup.py before deploying.
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
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
Adding the client as a dependency in your project's requirements.txt
file is the intended way to use the client.
$ 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
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())
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.
Building the wheel:
python setup.py bdist_wheel
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.)
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.
This project was originally created with the following "cookiecutter" tool:
https://github.com/wdm0006/cookiecutter-pipproject