This repo is a testing ground for GitHub Actions to evaluate it in comparison to the CircleCI setup we're currently using for lcdb-wf.

Notes on testing:

• building the envs is a constant ~8mins per env (env and env-r)

• github cache has a 5 GB limit across all files in the cache. The environments as-is are too big (3.8 GB and 4.8 GB for non-r and r respectively). So the workaround here is to run conda-pack and cache that instead of the full env directories.

• docker takes 3m30s to pull an image no matter what

• once envs are created (both packed and in docker containers), the timings are 1m51s for conda and 3m42s for docker

• might be able to tag docker containers based on hash of requirements files and dockerfile?

• what about using docker ADD to include the unpacked tarballs from the cache, followed by a conda-unpack? Then there will always be a docker container named after the branch that can be pulled by users. That is, the container is not used for testing -- it's built for later use.

• artifacts from each build then become the conda env tarball(s) and a Docker image containing them.

• Docker image is available from https://github.com/lcdb/github-action-testing/packages/