Rich comparison methods, e.g. Series.eq, do not like non-SeriesDType objects

[cmp0xff]

Describe the bug

For example, when Thing is an Enum, series.eq(Thing.MEMBER) gives an error from mypy.

To Reproduce

Provide a minimal runnable pandas example that is not properly checked by the stubs.

from enum import Enum, auto

import pandas as pd


class Thing(Enum):
    ONE = auto()
    TWO = auto()


series = pd.Series([Thing.ONE])
series.eq(Thing.ONE)  # error: Argument 1 to "eq" of "Series" has incompatible type "Thing"; expected "str | bytes | date | datetime | timedelta | <12 more items>"  [arg-type]

Indicate which type checker you are using (mypy or pyright).

mypy

Show the error message received from that type checker while checking your example.

compare_enums.py:13: error: Argument 1 to "eq" of "Series" has incompatible type "Thing"; expected "str | bytes | date | datetime | timedelta | <12 more items>"  [arg-type]
Found 1 error in 1 file (checked 1 source file)

Please complete the following information:

OS: [e.g. Windows, Linux, MacOS]

Windows

OS Version [e.g. 22]

10

python version

3.12.10

version of type checker

1.17.0

version of installed pandas-stubs

2.3.0.250703

Additional context

None

[Dr-Irv]

This is about what kinds of objects we want to type check that can go into a Series. In order to do better type checking for the most common types (int, str, float, datetime, etc.), we make Series generic based on a list of "common" types used with pandas. While it is certainly possible at runtime that any object can be stored in a Series, we disallow that to allow better type checking of the "common" types. In the example above series is inferred as Series[Any].

So the question is whether allowing an Any type in Series.eq() would actually cause incorrect code to get past the type checker.

One possible solution is to allow Enum to be a valid Scalar for the appropriate comparison methods.