BUG: to_sql fails with arrow date column

[NMAC427]

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• 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
import pyarrow as pa
import datetime as dt
import sqlalchemy as sa

engine = sa.create_engine("duckdb:///:memory:")
df = pd.DataFrame({"date": [dt.date(1970, 1, 1)]}, dtype=pd.ArrowDtype(pa.date32()))
df.to_sql("dataframe", con=engine, dtype=sa.Date(), index=False)

Issue Description

When calling .to_sql on a dataframe with a column of dtype pd.ArrowDtype(pa.date32()) or pd.ArrowDtype(pa.date64()), pandas calls to_pydatetime on it. However, this is only supported for pyarrow timestamp columns.

tests/test_large.py:38 (test_with_arrow)
def test_with_arrow():
        import pandas as pd
        import pyarrow as pa
        import datetime as dt
        import sqlalchemy as sa
    
        engine = sa.create_engine("duckdb:///:memory:")
        df = pd.DataFrame({"date": [dt.date(1970, 1, 1)]}, dtype=pd.ArrowDtype(pa.date32()))
>       df.to_sql("dataframe", con=engine, dtype=sa.Date(), index=False)

test_large.py:47: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
../../../../Library/Caches/pypoetry/virtualenvs/pydiverse-pipedag-JBY4b-V4-py3.11/lib/python3.11/site-packages/pandas/core/generic.py:2878: in to_sql
    return sql.to_sql(
../../../../Library/Caches/pypoetry/virtualenvs/pydiverse-pipedag-JBY4b-V4-py3.11/lib/python3.11/site-packages/pandas/io/sql.py:769: in to_sql
    return pandas_sql.to_sql(
../../../../Library/Caches/pypoetry/virtualenvs/pydiverse-pipedag-JBY4b-V4-py3.11/lib/python3.11/site-packages/pandas/io/sql.py:1920: in to_sql
    total_inserted = sql_engine.insert_records(
../../../../Library/Caches/pypoetry/virtualenvs/pydiverse-pipedag-JBY4b-V4-py3.11/lib/python3.11/site-packages/pandas/io/sql.py:1461: in insert_records
    return table.insert(chunksize=chunksize, method=method)
../../../../Library/Caches/pypoetry/virtualenvs/pydiverse-pipedag-JBY4b-V4-py3.11/lib/python3.11/site-packages/pandas/io/sql.py:1001: in insert
    keys, data_list = self.insert_data()
../../../../Library/Caches/pypoetry/virtualenvs/pydiverse-pipedag-JBY4b-V4-py3.11/lib/python3.11/site-packages/pandas/io/sql.py:967: in insert_data
    d = ser.dt.to_pydatetime()
../../../../Library/Caches/pypoetry/virtualenvs/pydiverse-pipedag-JBY4b-V4-py3.11/lib/python3.11/site-packages/pandas/core/indexes/accessors.py:213: in to_pydatetime
    return cast(ArrowExtensionArray, self._parent.array)._dt_to_pydatetime()
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <ArrowExtensionArray>
[datetime.date(1970, 1, 1)]
Length: 1, dtype: date32[day][pyarrow]

    def _dt_to_pydatetime(self):
        if pa.types.is_date(self.dtype.pyarrow_dtype):
>           raise ValueError(
                f"to_pydatetime cannot be called with {self.dtype.pyarrow_dtype} type. "
                "Convert to pyarrow timestamp type."
            )
E           ValueError: to_pydatetime cannot be called with date32[day] type. Convert to pyarrow timestamp type.

../../../../Library/Caches/pypoetry/virtualenvs/pydiverse-pipedag-JBY4b-V4-py3.11/lib/python3.11/site-packages/pandas/core/arrays/arrow/array.py:2174: ValueError

I was able to fix this by patching the following part of the insert_data function:

if ser.dtype.kind == "M":
    import pyarrow as pa
    if isinstance(ser.dtype, pd.ArrowDtype) and pa.types.is_date(ser.dtype.pyarrow_dtype):
        d = ser._values.astype(object)
    else:
        d = ser.dt.to_pydatetime()

Expected Behavior

If you leave the date column as an object column (don't set dtype=pd.ArrowDtype(pa.date32())), everything works, and a proper date column gets stored in the database.

Installed Versions

INSTALLED VERSIONS

commit : 965ceca
python : 3.11.3.final.0
python-bits : 64
OS : Darwin
OS-release : 22.4.0
Version : Darwin Kernel Version 22.4.0: Mon Mar 6 20:59:28 PST 2023; root:xnu-8796.101.5~3/RELEASE_ARM64_T6000
machine : arm64
processor : arm
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8

pandas : 2.0.2
numpy : 1.25.0
pytz : 2023.3
dateutil : 2.8.2
setuptools : 68.0.0
pip : 23.1.2
Cython : None
pytest : 7.4.0
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : 2.9.6
jinja2 : 3.1.2
IPython : 8.14.0
pandas_datareader: None
bs4 : 4.12.2
bottleneck : None
brotli : None
fastparquet : None
fsspec : 2023.6.0
gcsfs : None
matplotlib : None
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 12.0.1
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : None
snappy : None
sqlalchemy : 2.0.17
tables : None
tabulate : 0.9.0
xarray : None
xlrd : None
zstandard : None
tzdata : 2023.3
qtpy : None
pyqt5 : None