BUG: DataFrame.astype(dict) causes mypy error if dict includes 'datetime64[ns]' among mixed types

[bjfar]

Pandas version checks

• I have checked that this issue has not already been reported.

• I have confirmed this bug exists on the latest version of pandas.

• I have confirmed this bug exists on the main branch of pandas.

Reproducible Example

import pandas as pd
df = pd.DataFrame({'ID':[], 'col_2':[]})
dtypes = dict(ID=int, col_2='datetime64[ns]')
df2 = df.astype(dtypes)
print(df2.dtypes)

Issue Description

Output is:

ID                int64
col_1    datetime64[ns]
dtype: object

Seems fine. But running mypy we get:

error: Argument 1 to "astype" of "DataFrame" has incompatible type "dict[str, object]"; expected "Literal['bool', 'boolean', '?', 'b1', 'bool8', 'bool_', 'bool[pyarrow]', 'boolean[pyarrow]'] | type[builtins.bool] | BooleanDtype | type[numpy.bool] | Literal['int', 'Int8', 'Int16', 'Int32', 'Int64', 'b', 'i1', 'int8', 'byte', 'h', 'i2', 'int16', 'short', 'i', 'i4', 'int32', 'intc', 'l', 'i8', 'int64', 'int_', 'long', 'q', 'longlong', 'p', 'intp', 'int0', 'int8[pyarrow]', 'int16[pyarrow]', 'int32[pyarrow]', 'int64[pyarrow]'] | type[int] | Int8Dtype | Int16Dtype | Int32Dtype | Int64Dtype | <6 more items> | Literal['UInt8', 'UInt16', 'UInt32', 'UInt64', 'B', 'u1', 'uint8', 'ubyte', 'H', 'u2', 'uint16', 'ushort', 'I', 'u4', 'uint32', 'uintc', 'L', 'u8', 'uint', 'ulong', 'uint64', 'Q', 'ulonglong', 'P', 'uintp', 'uint0', 'uint8[pyarrow]', 'uint16[pyarrow]', 'uint32[pyarrow]', 'uint64[pyarrow]'] | UInt8Dtype | UInt16Dtype | UInt32Dtype | UInt64Dtype | type[unsignedinteger[Any]] | type[unsignedinteger[Any]] | type[unsignedinteger[Any]] | type[unsignedinteger[Any]] | type[unsignedinteger[Any]] | type[unsignedinteger[Any]] | Literal['str', 'string', 'U', 'str_', 'str0', 'unicode', 'unicode_', 'string[pyarrow]'] | type[str] | StringDtype | type[str_] | Literal['bytes', 'S', 'a', 'bytes_', 'bytes0', 'string_', 'binary[pyarrow]'] | type[bytes] | type[bytes_] | <8 more items> | Mapping[Any, ExtensionDtype | str | dtype[generic] | type[str] | type[complex] | type[builtins.bool] | type[object]] | Series[Any]"  [arg-type]
Found 1 error in 1 file (checked 1 source file)

Note that if both types are datetime64[ns] then mypy is fine with it.

Expected Behavior

I don't see anything in the docs for astype that would forbid this, and indeed the code seems to work fine. So I would expect mypy not to report an error for this.

Installed Versions

pd.show_versions()

INSTALLED VERSIONS

commit : d9cdd2e
python : 3.12.4.final.0
python-bits : 64
OS : Linux
OS-release : 6.5.0-44-generic
Version : #44~22.04.1-Ubuntu SMP PREEMPT_DYNAMIC Tue Jun 18 14:36:16 UTC 2
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_AU.UTF-8
LOCALE : en_AU.UTF-8

pandas : 2.2.2
numpy : 2.0.1
pytz : 2024.1
dateutil : 2.9.0
setuptools : 72.1.0
pip : 24.2
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 : None
pandas_datareader : None
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : None
bottleneck : None
dataframe-api-compat : None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : None
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyreadstat : None
python-calamine : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
zstandard : None
tzdata : 2024.1
qtpy : None
pyqt5 : None

[Patsnoop]

I would like to work on this

[loicdiridollou]

I am not sure this is really a pandas issue but more a pandas-stubs issue.
The error raised by mypy is that the type you are passing is of type <class 'type'> which is not explicitly allowed in the pandas-stubs for the astype method, see https://github.com/pandas-dev/pandas-stubs/blob/8a41508683212d6e861f07d053d86df796460124/pandas-stubs/core/frame.pyi#L1631.
I believe you should be better reporting it on the pandas-stubs https://github.com/pandas-dev/pandas-stubs/issues.

[rhshadrach]

Agreed @loicdiridollou. @bjfar - can you open an issue there.