versioning #113
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versioning #113
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evansd
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Dec 5, 2023
This new version is based on 22.04 and python3.10, and has an up to date version of all python packages. The versioning scheme is arbitrary major version, e.g. v1, v2, etc. The previous image is retained as v1, and the new image is v2. This move from maintaining 1 to 2 images requires some refactoring. Each major version has its own directory, and associated configuration files to track dependencies. They both share the same parameterised `Dockerfile` and `docker-compose.yaml`. In the process, I have also improved the local development tooling: - move from Makefile to parameterised justfile - some small reording of Dockerfile steps for efficiency and reuse - a proper solution for user the docker images themselves to add new dependencies and/or upgrade existing ones. This means you a) do not need all the python versions installed on your machine and b) this can be built on macos, in theory.
The github workflows have been updated to publish the v1 image as *both* `v1` and `latest` tags for now, as well as under the jupyter alias. The `v2` is published separately as just `v2`.
Used in docker image label and tag Refactored publishing script too.
This can be enhanced as needed, but the basic versions and tooling is there. Jinja2 is installed in the images, so we re-use the images themselves to render the template.
- Completely new user-facing README.md content - DEVELOPERS.md with playbook style info - Issue template for requesting packages
Seems like a useful thing to bundle documentation.
Also, updated missed rendering of v1/packages.md
Also, switch from generic end-user package `jupyter` package to specific packages we need. This drops the dependency on qtconsole.
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Fixes #112