[ARROW-5566] [Python] Overhaul type unification from Python sequence in arrow::py::InferArrowType

• Type: Improvement
• Status: Open
• Priority: Major
• Resolution: Unresolved
• Component/s: Python
• Labels: python-conversion
• External issue URL: https://github.com/apache/arrow/issues/16758
• Assignee: Unassigned
• Reporter: Wes McKinney
• Created: 12/Jun/19 03:13
• Updated: 11/Jan/23 07:41

Description

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

Issue Links

• is related to: ARROW-4324 [Python] Array dtype inference incorrect when created from list of mixed numpy scalars