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Conda managing Julia binary dependencies
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Add satified_skip_solve as a keyword argument for Conda.add #241

Closed mkitti closed 1 year ago

mkitti commented 1 year ago

Add --satisified-skip-solve as an argument for Conda.add.

This will allow PyCall.jl to ensure that numpy is installed, but not update it if it already in the environment.

MilesCranmer commented 1 year ago

LGTM

The CI is broken FYI, so just merge

mkitti commented 1 year ago

Yes, but why?

MilesCranmer commented 1 year ago

Broken since November: https://github.com/JuliaPy/Conda.jl/commits/master

mkitti commented 1 year ago

Yes, but why is CI so broken.

MilesCranmer commented 1 year ago

@stevengj any idea?

mkitti commented 1 year ago

What is happening on Windows?

AttributeError: module 'brotli' has no attribute 'error'

stevengj commented 1 year ago

LGTM. The CI problem on Windows is not a regression so it shouldn't be blocking.

davidanthoff commented 12 months ago

This seems to breaks CI on x86 ubuntu workflows, see here.

Could this be reverted for now?

Also, the CI here seems unfortunately limited, shouldn't it run on more Julia versions and on things like x86?

mkitti commented 12 months ago

I guess that is because there is no miniforge for x86: https://github.com/conda-forge/miniforge

mkitti commented 12 months ago

Is there commercial miniconda for x86? https://docs.conda.io/en/latest/miniconda.html

davidanthoff commented 12 months ago

There seems to be something, right? It does look like some kind of conda gets installed... There is an info that says that miniconda is being installed.

mkitti commented 12 months ago

My guess is that we are pulling in a very old version of conda when x86 was supported. I will investigate further before trying to sort out the fix.

mkitti commented 11 months ago

@davidanthoff My proposed fix is https://github.com/JuliaPy/PyCall.jl/pull/1045