Pandas version checks

  • [X] I have checked that this issue has not already been reported.
  • [X] I have confirmed this bug exists on the latest version of pandas.
  • [X] I have confirmed this bug exists on the main branch of pandas.

Reproducible Example

import pandas as pd

pd.Series([b"hi"], dtype="V2")

Issue Description

I assume you mean what numpy calls “structured dtype” when you say “compound dtype” here:

https://github.com/pandas-dev/pandas/blob/ca429943c70cee2077941f052281b92afc0c2054/pandas/core/generic.py#L492-L497

Unless you mean something totally different, that code is wrong. There’s other applications for void dtypes than structured arrays. void means “we don’t validate bit patterns here”, i.e. it corresponds to builtins.bytes (unlike S, a, which according to numpy are “zero terminated byte strings (not recommended)” so those codes aren’t a valid alternative).

If I’m right about your intention and you want to prevent structured arrays / recarrays, you should instead check if getattr(dtype, "fields", None) is not None.

Expected Behavior

Being able to create an ExtensionDtype with kind = 'V...' and sticking it into a Series.

Installed Versions

INSTALLED VERSIONS ------------------ commit : 0f437949513225922d851e9581723d82120684a6 python : 3.11.3.final.0 python-bits : 64 OS : Linux OS-release : 6.4.12-zen1-1-zen Version : #1 ZEN SMP PREEMPT_DYNAMIC Thu, 24 Aug 2023 00:37:46 +0000 machine : x86_64 processor : byteorder : little LC_ALL : None LANG : de_DE.UTF-8 LOCALE : de_DE.UTF-8 pandas : 2.0.3 numpy : 1.25.2 pytz : 2023.3 dateutil : 2.8.2 setuptools : 68.0.0 pip : 23.2.1 Cython : None pytest : None hypothesis : None sphinx : None blosc : None feather : None xlsxwriter : None lxml.etree : None html5lib : None pymysql : None psycopg2 : None jinja2 : None IPython : 8.14.0 pandas_datareader: None bs4 : None bottleneck : None brotli : None fastparquet : None fsspec : None gcsfs : None matplotlib : None numba : None numexpr : None odfpy : None openpyxl : None pandas_gbq : None pyarrow : 13.0.0 pyreadstat : None pyxlsb : None s3fs : None scipy : 1.11.2 snappy : None sqlalchemy : None tables : None tabulate : None xarray : None xlrd : None zstandard : None tzdata : 2023.3 qtpy : None pyqt5 : None

Comment From: flying-sheep

This is still an issue.

Who implemented that check? Can that person please explain what it’s for so we can fix it?

Comment From: flying-sheep

I have a lovely ExtensionDType that I’d like to use, but it’s blocked on this issue for 11 months now.

Could someone please take a look?

https://gist.github.com/flying-sheep/99f2ceafdc494f97424222611b4f9474

Comment From: flying-sheep

Hello?

Comment From: flying-sheep

Anyone home?

Comment From: ilan-gold

@shoyer Having a UUID extension array would be amazing for anndata, specifically the xarray integration.

Since we have to load coords in xarray, one way around that (that I'm pursuing) is loading the true index elsewhere and using an in-memory range index so that people have good first-load times. The issue, though, is that once you index a range indexer, you end up with an integer index after indexing into it, and we disallow this in AnnData to prevent confusion i.e., how iloc is its own method. So having a UUID index instead would be great - it would also help us avoid things like stacking two range indices.

I think either Phil or I can implement a fix, but the explanation would be helpful if it's solvable.

Comment From: ilan-gold

I have also run into "distinguishing between void and structured" in zarr so understanding that difference and how to check for it (at least from you) would be amazing for my own knowledge.