concat does not respect Series.dtype

[cmp0xff]

Describe the bug
Concatenating Series of the same dtype leads to Series[Any].

To Reproduce

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

   from typing import reveal_type
   
   import pandas as pd
   
   reveal_type(pd.concat([pd.Series([1, 2]), pd.Series([3, 4])]).dtype)

2. Indicate which type checker you are using (mypy or pyright).
   pyright
3. Show the error message received from that type checker while checking your example.

   concat.py:5:13 - information: Type of "pd.concat([pd.Series([1, 2]), pd.Series([3, 4])])" is "Series[Any]"
   

Please complete the following information:

• OS: Windows
• OS Version: 11
• python version: 3.13.4
• version of type checker: 1.1.403
• version of installed pandas-stubs: 2.3.0.250703

Additional context
None

[loicdiridollou]

We don't have all the overloads for concat in pandas/core/reshape/concat.py.
Probably worth a shot at adding pd.Series[T] in there so that if the two Series are the same type they get the right type at after concatenating.

[loicdiridollou]

I have played a little bit with it and something like below should work (need to be carely with the axis since it only works with vertical concat and not horizontal as it gives a Dataframe):

@overload
def concat(  # type: ignore[overload-overlap] # pyright: ignore[reportOverlappingOverload]
    objs: Iterable[Series[S2]],
    *,
    axis: AxisIndex = ...,
    join: Literal["inner", "outer"] = ...,
    ignore_index: bool = ...,
    keys: Iterable[HashableT2] = ...,
    levels: Sequence[list[HashableT3] | tuple[HashableT3, ...]] = ...,
    names: list[HashableT4] | None = ...,
    verify_integrity: bool = ...,
    sort: bool = ...,
    copy: bool = ...,
) -> Series[S2]: ...