astropy v6.0.0

[regro-cf-autotick-bot]

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Dependency Analysis

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Analysis by source code inspection shows a discrepancy between it and the the package's stated requirements in the meta.yaml.

Packages found by source code inspection but not in the meta.yaml:

• pyinstaller
• dask
• pytest
• arm_pyart
• requests
• extension-helpers
• matplotlib
• astropy-iers-data

Packages found in the meta.yaml but not found by source code inspection:

• importlib-metadata

_{This PR was created by the regro-cf-autotick-bot. The regro-cf-autotick-bot is a service to automatically track the dependency graph, migrate packages, and propose package version updates for conda-forge. Feel free to drop us a line if there are any issues! This PR was generated by https://github.com/regro/cf-scripts/actions/runs/7013543937, please use this URL for debugging.}

[conda-forge-webservices]

Hi! This is the friendly automated conda-forge-linting service.

I just wanted to let you know that I linted all conda-recipes in your PR (recipe) and found it was in an excellent condition.

[saimn]

cython > 3.0.0 is needed (just below)

[saimn]

also probably good to pin numpy<2.0 for now (build and runtime)

[maxnoe]

Instead of

{{ pin_compatible("numpy") }}

should we no require the minimum numpy required to build the ABI compatible bindings (i.e. numpy >=1.25) in run and host and then the lowest supported numpy under run?

This is what I have done now in eventio, see this diff:
https://github.com/conda-forge/eventio-feedstock/pull/29/files#diff-f3725a55bf339595bf865fec73bda8ac99f283b0810c205442021f29c06eea9a

or is pin_compatible still the right choice?

[neutrinoceros]

https://numpy.org/doc/stable/dev/depending_on_numpy.html#adding-a-dependency-on-numpy still redirects to https://conda-forge.org/docs/maintainer/knowledge_base.html#building-against-numpy, which leads me to believe that we're already doing it the recommended way; as far as I understand, conda-forge has its own way to provide backward compatibility for packages built against numpy and there is no need to leverage numpy 1.25+ builtin mechanism here.

[pllim]

Maybe for now we just pin numpy >= 1.25 for build here? I don't think conda reads pyproject.toml .

[neutrinoceros]

I don't think conda reads pyproject.toml

I confirm that it doesn't

[maxnoe]

conda-forge/conda-forge.github.io#2037

[pllim]

I got a bit further but I think we need to add astropy-iers-data to the recipe. Anyone knows if astropy-iers-data ever got into conda-forge? @astrofrog ?

#132

[astrofrog]

Yes: https://github.com/conda-forge/astropy-iers-data-feedstock (and that repo has auto merge enabled so that updates are fully automated)

[saimn]

From https://conda-forge.org/docs/maintainer/knowledge_base.html#building-against-numpy I think there is no need to change anything about Numpy, at least for now: it will build with the oldest Numpy supported for a given Python version, which should be fine.
So we need to update the version of Cython, and indeed add astropy-iers-data 👍

[pllim]

it will build with the oldest Numpy supported for a given Python version, which should be fine.

Really? But we force numpy>=1.25 for build requirements in pip.

[maxnoe]

Really? But we force numpy>=1.25 for build requirements in pip.

Because you make use of the new API to produce the wheels, as discussed in the issue(s) linked in the issue I opened above, that's not how conda-forge currently does it.

Building against the oldest supported numpy by conda-forge will have the same effect, being forward compatible with all newer versions of numpy.

[pllim]

Thanks for the help! It is green over at #132 but I cannot merge it.