These images are used to run code packages in controlled containers. The names of the images follow the namespacing as used in the polyglot Coursemology::Polyglot::Language subclasses.

The images are built on top of a base image, which installs make and configures the container command. Base images are tagged with the OS images they are built on: Debian 8 or 10. All other images install the required packages for a particular language.

Each image should have its own folder/subfolder.

For Python, it can be found in python/pythonX.X where X.X is the version number.
You can build the Dockerfile locally by entering into the directory and executing the docker build command.

docker build -t coursemology/evaluator-image-<language>:<version> .

Once built and tested, you can push to dockerhub.
You will need to docker login using the dockerhub credentials.

docker push coursemology/evaluator-image-<language>:<version>

The image

If your code cannot pass Coursemology's autograder, you can manually simulate the autograding process with these Docker images to help with debugging.

Install Docker to run the images on your own machine.

Python has separate tags for each version. The default tag latest does not exist.

You can see available versions in the python folder of this repository.

docker pull coursemology/evaluator-image-python:3.7

There is only 1 image for each of these languages.

docker pull coursemology/evaluator-image-c_cpp

docker pull coursemology/evaluator-image-java

When editing a programming question on Coursemology, there is a link to a package zip file. Download and extract it.

Copy the code you want to debug into the files in the submission folder. More information about the package structure can be found at the evaluator-samples repository.

Use docker run to start a container with the same environment as Coursemology's autograder. Specify -it and --entrypoint=/bin/bash or the container will attempt to run the evaluation script and exit immediately.

For convenience when debugging, mount the host folder where the package files have been unzipped and prepared to /home/coursemology/package in the container.

docker run -it --entrypoint=/bin/bash --mount type=bind,source="$(pwd)",target=/home/coursemology/package coursemology/evaluator-image-java

Change to the /home/coursemology/package directory.

root@someid:/# cd /home/coursemology/package
root@someid:~/package#

The coursemology-evaluate.sh script runs the sequence of steps for autograding.

In the package folder, run the following commands to run the public tests.

make prepare
make compile
make public

You can edit the files used by the test runner and run the tests again to debug. See the output from the prepare step to figure out the file is. Remember to run the compile step again for compiled languages.

Open the report.xml file generated in the package folder.

Running the private tests:

make private

Running the evaluation tests:

make evaluation

Cleaning up if the prepared file has been messed up:

make clean