BUG: pd.concat raises ValueError if I have the same column with datetime.datetime type and pd.Timestamp type.

[WindSoilder]

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
a = pd.DataFrame({'a': [pd.Timestamp("2023-01-01")]})
b = pd.DataFrame(index=[1])
b['a'] = datetime(2023, 1, 2)
pd.concat([a, b])

Issue Description

It seems that pd.concat runs to failed because a.a and b.a have two different dtypes.

a.a is datetime64[ns], but b.a is datetime64[us].

But it's strange..I think pd.Timestamp and datetime.datetime should be the same thing at user level.

Actually the following one is failed too:

import pandas as pd
a = pd.DataFrame({'a': [pd.Timestamp("2023-01-01")]})
b = pd.DataFrame(index=[1])
b['a'] = pd.Timestamp("2023-01-01")
pd.concat([a, b])

Only the following is fine:

import pandas as pd
a = pd.DataFrame({'a': [pd.Timestamp("2023-01-01")]})
b = pd.DataFrame({'a': [pd.Timestamp("2023-01-01")]}, index=[1])
pd.concat([a, b])

Expected Behavior

I'd expected it runs to success, it runs success on 2.0.3.

Installed Versions

INSTALLED VERSIONS

commit : a6445df
python : 3.11.0.final.0
python-bits : 64
OS : Darwin
OS-release : 22.4.0
Version : Darwin Kernel Version 22.4.0: Mon Mar 6 21:00:17 PST 2023; root:xnu-8796.101.5~3/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : None
LOCALE : None.UTF-8

pandas : 2.1.0+22.ga6445df90
numpy : 1.24.2
pytz : 2022.7.1
dateutil : 2.8.2
setuptools : 65.5.0
pip : 22.2.2
Cython : 0.29.36
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : 1.0.2
psycopg2 : None
jinja2 : 3.1.2
IPython : 8.12.0
pandas_datareader : None
bs4 : None
bottleneck : None
dataframe-api-compat: None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : None
numba : None
numexpr : None
odfpy : None
openpyxl : 3.1.2
pandas_gbq : None
pyarrow : 12.0.0
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : 1.10.1
sqlalchemy : 1.4.39
tables : None
tabulate : None
xarray : None
xlrd : None
zstandard : 0.20.0
tzdata : 2023.3
qtpy : None
pyqt5 : None

[WindSoilder]

Closing this because it's duplicate #53640