DEV: add a conda environment.yml with all development dependencies#18659
DEV: add a conda environment.yml with all development dependencies#18659charris merged 3 commits intonumpy:mainfrom
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mattip
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Using conda could be mentioned in the documentation:
and maybe even describe conda in describing virtualenvs
How do we keep the versions synced with the requirements.txt files? Does dependabot see this file?
I think that's the one place I'd like to update.
Dependabot doesn't see it AFAIK. There's only a few pins, which are easy enough to update by hand if any test fails. I don't expect that to happen often, probably only once a year or less. |
There are enough dependencies now that it's too hard to remember. This set is comprehensive, so a single `conda env create -f environment.yml` gives you everything in a fresh environment named numpy-dev. [ci skip]
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Should this be included in CI to make sure it doesn't get out of date? |
I think that's a good idea, however I'd like to file a follow-up issue for that. Adding an environment file is a useful enhancement in itself, and I don't have the bandwidth to switch some CI jobs to conda right now. |
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This could use a release note, probably under |
I think yes, they should. Not that they'll be used much that way (the only way to do so is to manually download the tarball and go from there), but an sdist is also a snapshot of a release with archiving/historical value. I'll update this. |
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I fixed the Decided against a release note. This is not a user-accessible feature from a release artifact, so it only belongs in the developer docs. |
Not only environment.yml is added, setup.cfg was missing too. Current result of `ls -a` in the top-level directory of the unpacked sdist: ``` . LICENSE.txt pytest.ini site.cfg.example .. linter_requirements.txt README.md test_requirements.txt benchmarks MANIFEST.in release_requirements.txt THANKS.txt doc numpy runtests.py tools doc_requirements.txt pavement.py setup.cfg tox.ini environment.yml PKG-INFO setup.py versioneer.py INSTALL.rst.txt pyproject.toml ```
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Thanks Ralf. |
There are enough dependencies now that it's too hard to remember. This set is comprehensive, so a single
conda env create -f environment.ymlgives you everything in a fresh environment namednumpy-dev.