These tools leverage the Canvas LMS REST API to create a more pleasant environment for working with Absalon.
"Staffeli" is Danish for "easel" — a support frame for holding up a canvas.
Contents
The purpose of Staffeli is two-fold:
- Leverage the Canvas LMS REST API to get things done better, faster, stronger.
- Quick prototyping of new features for Canvas LMS.
Initially, Staffeli is not intended for managing course content, merely to snapshot course data (e.g., enrolled students, groups, sections, submissions), and to get grading done efficiently.
Although Staffeli is written in Python 3, it is not intent on forcing you to manage your course using Python, or to have to get intimate with the Staffeli API to get things done. Staffeli extensively uses YAML files for storage, enabling the easy use of both command-line utilities and the programming language of your choice, to get things done quickly, and efficiently.
Staffeli is maturing. It is being transitioned to be annotated with type hints, with the types checked statically with mypy, and a test-suite has been set up, but full-blown continuous integration remains to be set up.
We are still covering a fairly small subset of the API. Brace yourself. Lend a hand.
These are instructions for installing Staffeli on your system.
- Download this repository
or
git clone https://github.com/DIKU-EDU/staffeli.git - Enter directory and run
pip3 install -e .
These are instructions for installing Staffeli in a user directory.
- Check that you have Python 3 and pip installed:
which python3 pip3 - Install virtualenv globally,
e.g. with
sudo pip3 install virtualenv - Download this repository
or
git clone https://github.com/DIKU-EDU/staffeli.git - Enter directory and create virtualenv with
virtualenv . - Activate virtualenv with
source bin/activate - Install Staffeli in virtualenv,
pip3 install -e .
With Staffeli, we work with local course clones. We aim to keep these clones compatible with git.
We recommend that you create a local directory canvas, absalon,
or similar, for all of you Canvas-related local course clones. Staffeli
needs some initial help to be able to login with your credentials. You
need to generate a
token
for Staffeli to use, and save it as .token, token, or
token.txt in this high-level directory.
NB! This is your personal token so do not share it with others, else they can easily impersonate you using a tool like Staffeli. Unfortunately, to the best of our knowledge, Canvas has no means to segregate or specialize tokens, so this is really "all or nothing".
To clone a course:
$ staffeli clone '<course name>' [dir]
The 'course name' is any case-insensitive substring of the course name as
it appears on your dashboard. Use quotes in case the substring contains spaces.
If there are multiple conflicting names matching the substring, Staffeli will
complain and let you try again.
The [dir] is an optional destination directory for the local working area,
in case it should not be named <course string>. For example:
$ staffeli clone 'Advanced programming' ap17 Cloning '5100-B1-1E17;Advanced programming' into 'ap17'...
Use staffeli fetch. For instance, to fetch all submissions for "A3":
$ staffeli fetch subs/A3
To fetch just the metadata for all submissions, but not the submissions themselves:
$ staffeli fetch subs
This is a good idea to make sure you are up-to-date with canvas.
$ staffeli fetch groups
Assuming you are in the submission directory, you can use
staffeli grade to grade the submission:
staffeli grade GRADE [-m COMMENT] [FILEPATH]...
Where
GRADE pass, fail, or an int.
[-m COMMENT] An optional comment to write.
[-f FILEPATH] Upload the contents of a file as a comment.
[FILEPATH]... Optional files to upload alongside.
See the groups contrib.
It is up-and-coming on [ReadTheDocs](http://staffeli.readthedocs.io/en/latest/). The source files for that page are under [docs/source](docs/source), and they are, much like this README, written in reStructured Text. It is also suggested to follow the Python documentation style guide.
First, take a look at our design guide and style guide.
Contact us at dikunix at dikumail dot dk.
Take a look at our on-going issues.
Currently, Travis CI will
only check that you roughly conform to the PEP 8 Python Style
Guide (using
flake8), and perform static type-checking
with mypy, all only for selected Python
files in this repository. See (and run?)
`static_tests.py <static_tests.py>`__ for further details.
Before you do that however, you might want to do this:
$ pip3 install -r test-requirements.txt
This will also install what you need to run the dynamic tests we have in
store under tests, except for Docker:
`start_local_canvas.py <start_local_canvas.py>`__ will fire up a
Docker image with a local Canvas instance for use with our
tests. You will also find it in your browser under the
address localhost:3000. The user is canvas@example.edu and the
password is canvas.
The static and dynamic tests are also part of the
`pre-commit <hooks/pre-commit>`__ and
`pre-push <hooks/pre-push>`__ hooks, respectively. Install these
hooks by executing `hooks/install.sh <hooks/install.sh>`__.
Unfortunately, neither these hooks, nor the hooks installer will work on
Windows.
We use flake8 for style-checking and mypy for static type-checking.
Assuming you have these tools installed, you can do this:
$ ./static_tests.py
This is also part of the `pre-commit <hooks/pre-commit>`__ hook.
We use pytest together with hypothesis.
Assuming you have these tools installed, you can do this:
$ pytest
This is also part of the pre-push hook.
Run pytest with the option --cov=staffeli to get an idea of the
test coverage of Staffeli proper.
It is pretty lousy ATM. As of 2017-05-24, the numbers were:
Name Stmts Miss Cover ------------------------------------------------- staffeli/assignment.py 28 28 0% staffeli/cachable.py 22 13 41% staffeli/canvas.py 326 326 0% staffeli/cli.py 295 295 0% staffeli/course.py 43 4 91% staffeli/files.py 57 41 28% staffeli/gcat.py 29 5 83% staffeli/group.py 23 23 0% staffeli/listed.py 31 8 74% staffeli/names.py 3 1 67% staffeli/resubmissions.py 121 121 0% staffeli/speedgrader_url.py 9 9 0% staffeli/submission.py 22 22 0% staffeli/typed_canvas.py 112 4 96% staffeli/upload.py 17 17 0% ------------------------------------------------- TOTAL 1138 917 19%