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Dynamic versioning #118
Dynamic versioning #118
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I tested now also how this will affect installation from e.g. a downloaded release zip folder without any additional metadata or SCM connected. In this case the version cannot be derived and will now fallback to |
bah, the tests are failing for pip + gpu testing on AWS. It looks like this is due to the instance running out of space. This didn't happen before. But probably we should change it so even with pip the venv is created on the mounted nvme drive, like is done when testing with pdm: https://github.com/observingClouds/neural-lam/blob/feat/dynamic_version/.github/workflows/install-and-test.yml#L60. What do you think? |
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Looking good. Just one minor comment (and we should probably ensure the tests pass, but maybe I will need to do a separate PR for that)
I think this is great! |
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If you merge |
Describe your changes
This PR introduces dynamic versioning, meaning the version of neural-lam would no longer be hard-coded in the pyproject.toml but derived from the git hash or from the metadata in e.g. wheels published to pypi.
The advantage of this method is that development changes to the neural-lam code become immediately visible in downstream applications, e.g. mlflow server and make it easier to track those changes.
No new dependencies are introduced.
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