This command-line tool is a software development toolkit to help instructional teams author asynchronous graders for Coursera (typically programming assignments). Coursera's asynchronous grading environment is based upon docker. While use of this tool is by no means required to develop the docker container images, we believe it is helpful in the endavour. See below for brief descriptions of this tool's capabilities.

To install this sdk, simply execute:

sudo pip install courseraprogramming

pip is a python package manager. If you do not have pip installed on your machine, please follow the installation instructions for your platform found at: <https://pip.pypa.io/en/latest/installing.html#install-or-upgrade-pip>

The tool includes its own usage information and documentation. Simply run:

courseraprogramming -h

or:

courseraprogramming --help

for a complete list of features, flags, and documentation.

Note: the tool requires docker to already be installed on your machine. Please see the docker installation instructions for further information.

Runs a number of sanity checks on your development environment and the Dockerfile that builds your grader to help catch pitfalls early.

These subcommands help you veriy that a built docker container image actually has what you expect inside of it. You can use these commands to poke at the file system and verify that everything is where it should be.

Allows for interactive inspection of your docker grading container image to help debug grader issues. By default, it provides a shell that runs in a simulation of the hardened sandbox environment.

This grade subcommand loosely replicates the production grading environment on your local machine, including applying CPU and memory limits, running as the correct user id, mounting the external file systems correctly, and relinquishing the appropriate extra linux capabilities. Note that because the GrID system has adoped a defense-in-depth or layered defensive posture, not all layers of the production environment can be faithfully replicated locally.

The grade subcommand has 2 sub-sub-commands. local runs a local grader container image on a sample submission found on the local file system. The future remote sub-sub-command will run a local grader container image on a sample submission downloaded from Coursera.org. This sub-sub-command is intended to help instructional teams verify new versions of their graders correctly handle problematic submissions.

Allows an instructional team to upload their containers to Coursera without using a web browser. It is designed to even work in an unattended fashion (i.e. from a jenkins job). In order to make the upload command work from a Jenkins automated build machine, simply copy the ~/.coursera directory from a working machine, and install it in the jenkins home folder. Beware that the oauth2_cache file within that directory contains a refresh token for the user who authorized themselves. This refresh token should be treated as if it were a password and not shared or otherwise disclosed!

Please us the github issue tracker to document any bugs or other issues you encounter while using this tool.

Note: We do not have the bandwidth to officially support this tool on windows. That said, patches to add / maintain windows support are welcome!

We recommend developing courseraprogramming within a python virtualenv. To get your environment set up properly, do the following:

virtualenv venv
source venv/bin/activate
python setup.py develop
pip install -r test_requirements.txt

To run tests, simply run: nosetests, or tox.

Code should conform to pep8 style requirements. To check, simply run:

pep8 courseraprogramming tests