Do not fail when markers are numpy integers #30838
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jklymak
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Dec 22, 2025
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jklymak
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We are a library that supports Numpy. I don't think this is overly scope-creep to accept numpy integers here.
tacaswell
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Dec 23, 2025
This is a better expression of intent for a change introduced in commit #2e5f5ff.
Seems justifiable, so I won’t block. Nevertheless I think the numeric markers a a design flaw, and we should work on replacements and discourage their use rather than trying to make them work better for edge cases.
scottshambaugh
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Jan 16, 2026
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In line with the robustness principle, I think the more liberal Hashable check is appropriate. I don't see an a-priori reason to restrict the types here.
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PR summary
Do not fail when marker values are numpy integers e.g.
np.int64(4).The rationale is, matplotlib exists in an ecosystem where pandas and numpy container types are prevalent. When the containers (
pd.Series,np.array) contain only integer values, they do not preserve the originalinttype when the values come out. i.e.ints go innp.int64s come out. With this PR aninttype marker that goes into these containers will still recognised as a marker when it comes out.closes #30836
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