Repository: pandas-dev/pandas
File: pandas/core/dtypes/dtypes.py (Python)

Code before:
                return datetime
        elif pa.types.is_date(pa_type):
            return date
        elif pa.types.is_time(pa_type):
            return time
        elif pa.types.is_decimal(pa_type):
            return Decimal
        elif pa.types.is_dictionary(pa_type):
            # TODO: Potentially change this & CategoricalDtype.type to
            #  something more representative of the scalar
            return CategoricalDtypeType
        elif pa.types.is_list(pa_type) or pa.types.is_large_list(pa_type):
            return list
        elif pa.types.is_fixed_size_list(pa_type):
            return list
        elif pa.types.is_map(pa_type):
            return list
        elif pa.types.is_struct(pa_type):
            return dict
        elif pa.types.is_null(pa_type):
            # TODO: None? pd.NA? pa.null?
            return type(pa_type)
        elif isinstance(pa_type, pa.ExtensionType):
            return type(self)(pa_type.storage_type).type
        elif isinstance(pa_type, pa.JsonType):
            return str
        raise NotImplementedError(pa_type)

    @property
    def name(self) -> str:  # type: ignore[override]
        """
        A string identifying the data type.
        """
        return f"{self.pyarrow_dtype!s}[{self.storage}]"

    @cache_readonly
    def numpy_dtype(self) -> np.dtype:
        """Return an instance of the related numpy dtype"""
        if pa.types.is_timestamp(self.pyarrow_dtype):
            # pa.timestamp(unit).to_pandas_dtype() returns ns units
            # regardless of the pyarrow timestamp units.
            # This can be removed if/when pyarrow addresses it:
            # https://github.com/apache/arrow/issues/34462
            return np.dtype(f"datetime64[{self.pyarrow_dtype.unit}]")
        if pa.types.is_duration(self.pyarrow_dtype):
            # pa.duration(unit).to_pandas_dtype() returns ns units
            # regardless of the pyarrow duration units
            # This can be removed if/when pyarrow addresses it:
            # https://github.com/apache/arrow/issues/34462
            return np.dtype(f"timedelta64[{self.pyarrow_dtype.unit}]")
        if pa.types.is_string(self.pyarrow_dtype) or pa.types.is_large_string(

Review comment (suggestion):
```suggestion
        elif isinstance(pa_type, pa.BaseExtensionType):
            return type(self)(pa_type.storage_type).type
```

Code after:
                return datetime
        elif pa.types.is_date(pa_type):
            return date
        elif pa.types.is_time(pa_type):
            return time
        elif pa.types.is_decimal(pa_type):
            return Decimal
        elif pa.types.is_dictionary(pa_type):
            # TODO: Potentially change this & CategoricalDtype.type to
            #  something more representative of the scalar
            return CategoricalDtypeType
        elif pa.types.is_list(pa_type) or pa.types.is_large_list(pa_type):
            return list
        elif pa.types.is_fixed_size_list(pa_type):
            return list
        elif pa.types.is_map(pa_type):
            return list
        elif pa.types.is_struct(pa_type):
            return dict
        elif pa.types.is_null(pa_type):
            # TODO: None? pd.NA? pa.null?
            return type(pa_type)
        elif isinstance(pa_type, pa.BaseExtensionType):
            return type(self)(pa_type.storage_type).type
        raise NotImplementedError(pa_type)

    @property
    def name(self) -> str:  # type: ignore[override]
        """
        A string identifying the data type.
        """
        return f"{self.pyarrow_dtype!s}[{self.storage}]"

    @cache_readonly
    def numpy_dtype(self) -> np.dtype:
        """Return an instance of the related numpy dtype"""
        if pa.types.is_timestamp(self.pyarrow_dtype):
            # pa.timestamp(unit).to_pandas_dtype() returns ns units
            # regardless of the pyarrow timestamp units.
            # This can be removed if/when pyarrow addresses it:
            # https://github.com/apache/arrow/issues/34462
            return np.dtype(f"datetime64[{self.pyarrow_dtype.unit}]")
        if pa.types.is_duration(self.pyarrow_dtype):
            # pa.duration(unit).to_pandas_dtype() returns ns units
            # regardless of the pyarrow duration units
            # This can be removed if/when pyarrow addresses it:
            # https://github.com/apache/arrow/issues/34462
            return np.dtype(f"timedelta64[{self.pyarrow_dtype.unit}]")
        if pa.types.is_string(self.pyarrow_dtype) or pa.types.is_large_string(
            self.pyarrow_dtype
        ):