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https://issues.apache.org/jira/browse/ARROW-5566?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17218903#comment-17218903
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Krisztian Szucs commented on ARROW-5566:
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[~jorisvandenbossche] My refactors have not touched the inference paths, so I'd
say that we should keep this issue open. We want to remove the numpy runtime
dependency at some point, where we'll need to update the inference code.
> [Python] Overhaul type unification from Python sequence in
> arrow::py::InferArrowType
> ------------------------------------------------------------------------------------
>
> Key: ARROW-5566
> URL: https://issues.apache.org/jira/browse/ARROW-5566
> Project: Apache Arrow
> Issue Type: Improvement
> Components: Python
> Reporter: Wes McKinney
> Priority: Major
> Labels: python-conversion
>
> I'm working on ARROW-4324 and there's some technical debt lying in
> arrow/python/inference.cc because the case where NumPy scalars are mixed with
> non-NumPy Python scalar values, all hell breaks loose. In particular, the
> innocuous {{numpy.nan}} is a Python float, not a NumPy float64, so the
> sequence {{[np.float16(1.5), np.nan]}} can be converted incorrectly.
> Part of what's messy is that NumPy dtype unification is split from general
> type unification. This should all be combined together with the NumPy types
> mapping onto an intermediate value (for unification purposes) that then maps
> ultimately onto an Arrow type
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