chore: Add Version.dtypes, remove import_dtypes_module

.pre-commit-config.yaml

@@ -60,7 +60,7 @@ repos:
       language: pygrep
       files: ^narwhals/
     - id: dtypes-import
-      name: don't import from narwhals.dtypes (use `import_dtypes_module` instead)
+      name: don't import from narwhals.dtypes (use `Version.dtypes` instead)
       entry: |
           (?x)
             import\ narwhals.dtypes|

narwhals/_arrow/namespace.py

@@ -22,7 +22,6 @@
 from narwhals._expression_parsing import combine_alias_output_names
 from narwhals._expression_parsing import combine_evaluate_output_names
 from narwhals.utils import Implementation
-from narwhals.utils import import_dtypes_module
 
 if TYPE_CHECKING:
     from narwhals._arrow.typing import ArrayOrScalarAny
@@ -135,15 +134,15 @@ def func(df: ArrowDataFrame) -> list[ArrowSeries]:
         )
 
     def mean_horizontal(self, *exprs: ArrowExpr) -> ArrowExpr:
-        dtypes = import_dtypes_module(self._version)
+        int_64 = self._version.dtypes.Int64()
 
         def func(df: ArrowDataFrame) -> list[ArrowSeries]:
             expr_results = list(chain.from_iterable(expr(df) for expr in exprs))
             series = align_series_full_broadcast(
                 *(s.fill_null(0, strategy=None, limit=None) for s in expr_results)
             )
             non_na = align_series_full_broadcast(
-                *(1 - s.is_null().cast(dtypes.Int64()) for s in expr_results)
+                *(1 - s.is_null().cast(int_64) for s in expr_results)
             )
             return [reduce(operator.add, series) / reduce(operator.add, non_na)]
 

narwhals/_arrow/series.py

@@ -32,7 +32,6 @@
 from narwhals.exceptions import InvalidOperationError
 from narwhals.utils import Implementation
 from narwhals.utils import generate_temporary_column_name
-from narwhals.utils import import_dtypes_module
 from narwhals.utils import is_list_of
 from narwhals.utils import not_implemented
 from narwhals.utils import requires
@@ -865,7 +864,7 @@ def is_finite(self) -> Self:
         return self._with_native(pc.is_finite(self.native))
 
     def cum_count(self, *, reverse: bool) -> Self:
-        dtypes = import_dtypes_module(self._version)
+        dtypes = self._version.dtypes
         return (~self.is_null()).cast(dtypes.UInt32()).cum_sum(reverse=reverse)
 
     @requires.backend_version((13,))

narwhals/_arrow/series_dt.py

@@ -10,7 +10,6 @@
 from narwhals._arrow.utils import ArrowSeriesNamespace
 from narwhals._arrow.utils import floordiv_compat
 from narwhals._arrow.utils import lit
-from narwhals.utils import import_dtypes_module
 
 if TYPE_CHECKING:
     from narwhals._arrow.series import ArrowSeries
@@ -47,7 +46,7 @@ def convert_time_zone(self, time_zone: str) -> ArrowSeries:
 
     def timestamp(self, time_unit: TimeUnit) -> ArrowSeries:
         ser = self.compliant
-        dtypes = import_dtypes_module(ser._version)
+        dtypes = ser._version.dtypes
         if isinstance(ser.dtype, dtypes.Datetime):
             unit = ser.dtype.time_unit
             s_cast = self.native.cast(pa.int64())

narwhals/_arrow/utils.py

@@ -13,7 +13,6 @@
 
 from narwhals._compliant.series import _SeriesNamespace
 from narwhals.exceptions import ShapeError
-from narwhals.utils import import_dtypes_module
 from narwhals.utils import isinstance_or_issubclass
 
 if TYPE_CHECKING:
@@ -92,7 +91,7 @@ def nulls_like(n: int, series: ArrowSeries) -> ArrowArray:
 
 @lru_cache(maxsize=16)
 def native_to_narwhals_dtype(dtype: pa.DataType, version: Version) -> DType:
-    dtypes = import_dtypes_module(version)
+    dtypes = version.dtypes
     if pa.types.is_int64(dtype):
         return dtypes.Int64()
     if pa.types.is_int32(dtype):
@@ -157,7 +156,7 @@ def native_to_narwhals_dtype(dtype: pa.DataType, version: Version) -> DType:
 
 
 def narwhals_to_native_dtype(dtype: DType | type[DType], version: Version) -> pa.DataType:
-    dtypes = import_dtypes_module(version)
+    dtypes = version.dtypes
     if isinstance_or_issubclass(dtype, dtypes.Decimal):
         msg = "Casting to Decimal is not supported yet."
         raise NotImplementedError(msg)

narwhals/_compliant/selectors.py

@@ -18,7 +18,6 @@
 from narwhals.utils import _parse_time_unit_and_time_zone
 from narwhals.utils import dtype_matches_time_unit_and_time_zone
 from narwhals.utils import get_column_names
-from narwhals.utils import import_dtypes_module
 from narwhals.utils import is_compliant_dataframe
 
 if not TYPE_CHECKING:  # pragma: no cover
@@ -150,13 +149,13 @@ def names(df: FrameT) -> Sequence[str]:
         return self._selector.from_callables(series, names, context=self)
 
     def categorical(self) -> CompliantSelector[FrameT, SeriesOrExprT]:
-        return self._is_dtype(import_dtypes_module(self._version).Categorical)
+        return self._is_dtype(self._version.dtypes.Categorical)
 
     def string(self) -> CompliantSelector[FrameT, SeriesOrExprT]:
-        return self._is_dtype(import_dtypes_module(self._version).String)
+        return self._is_dtype(self._version.dtypes.String)
 
     def boolean(self) -> CompliantSelector[FrameT, SeriesOrExprT]:
-        return self._is_dtype(import_dtypes_module(self._version).Boolean)
+        return self._is_dtype(self._version.dtypes.Boolean)
 
     def all(self) -> CompliantSelector[FrameT, SeriesOrExprT]:
         def series(df: FrameT) -> Sequence[SeriesOrExprT]:
@@ -172,7 +171,7 @@ def datetime(
         time_units, time_zones = _parse_time_unit_and_time_zone(time_unit, time_zone)
         matches = partial(
             dtype_matches_time_unit_and_time_zone,
-            dtypes=import_dtypes_module(version=self._version),
+            dtypes=self._version.dtypes,
             time_units=time_units,
             time_zones=time_zones,
         )

narwhals/_dask/expr_dt.py

@@ -6,7 +6,6 @@
 from narwhals._pandas_like.utils import calculate_timestamp_datetime
 from narwhals._pandas_like.utils import native_to_narwhals_dtype
 from narwhals.utils import Implementation
-from narwhals.utils import import_dtypes_module
 
 if TYPE_CHECKING:
     try:
@@ -115,7 +114,7 @@ def func(s: dx.Series, time_unit: TimeUnit) -> dx.Series:
             )
             is_pyarrow_dtype = "pyarrow" in str(dtype)
             mask_na = s.isna()
-            dtypes = import_dtypes_module(self._compliant_expr._version)
+            dtypes = self._compliant_expr._version.dtypes
             if dtype == dtypes.Date:
                 # Date is only supported in pandas dtypes if pyarrow-backed
                 s_cast = s.astype("Int32[pyarrow]")

narwhals/_dask/utils.py

@@ -10,7 +10,6 @@
 from narwhals.dependencies import get_pyarrow
 from narwhals.utils import Implementation
 from narwhals.utils import Version
-from narwhals.utils import import_dtypes_module
 from narwhals.utils import isinstance_or_issubclass
 from narwhals.utils import parse_version
 
@@ -96,7 +95,7 @@ def validate_comparand(lhs: dx.Series, rhs: dx.Series) -> None:
 
 
 def narwhals_to_native_dtype(dtype: DType | type[DType], version: Version) -> Any:
-    dtypes = import_dtypes_module(version)
+    dtypes = version.dtypes
     if isinstance_or_issubclass(dtype, dtypes.Float64):
         return "float64"
     if isinstance_or_issubclass(dtype, dtypes.Float32):

narwhals/_duckdb/dataframe.py

@@ -26,7 +26,6 @@
 from narwhals.utils import Implementation
 from narwhals.utils import Version
 from narwhals.utils import generate_temporary_column_name
-from narwhals.utils import import_dtypes_module
 from narwhals.utils import not_implemented
 from narwhals.utils import parse_columns_to_drop
 from narwhals.utils import parse_version
@@ -414,7 +413,7 @@ def drop_nulls(self, subset: Sequence[str] | None) -> Self:
         return self._with_native(self.native.filter(keep_condition))
 
     def explode(self, columns: Sequence[str]) -> Self:
-        dtypes = import_dtypes_module(self._version)
+        dtypes = self._version.dtypes
         schema = self.collect_schema()
         for name in columns:
             dtype = schema[name]

narwhals/_duckdb/utils.py

@@ -8,7 +8,6 @@
 import duckdb
 
 from narwhals.utils import Version
-from narwhals.utils import import_dtypes_module
 from narwhals.utils import isinstance_or_issubclass
 
 if TYPE_CHECKING:
@@ -83,7 +82,7 @@ def evaluate_exprs(
 
 def native_to_narwhals_dtype(duckdb_dtype: DuckDBPyType, version: Version) -> DType:
     duckdb_dtype_id = duckdb_dtype.id
-    dtypes = import_dtypes_module(version)
+    dtypes = version.dtypes
 
     # Handle nested data types first
     if duckdb_dtype_id == "list":
@@ -121,7 +120,7 @@ def native_to_narwhals_dtype(duckdb_dtype: DuckDBPyType, version: Version) -> DT
 
 @lru_cache(maxsize=16)
 def _non_nested_native_to_narwhals_dtype(duckdb_dtype_id: str, version: Version) -> DType:
-    dtypes = import_dtypes_module(version)
+    dtypes = version.dtypes
     return {
         "hugeint": dtypes.Int128(),
         "bigint": dtypes.Int64(),
@@ -150,7 +149,7 @@ def _non_nested_native_to_narwhals_dtype(duckdb_dtype_id: str, version: Version)
 
 
 def narwhals_to_native_dtype(dtype: DType | type[DType], version: Version) -> str:  # noqa: PLR0915
-    dtypes = import_dtypes_module(version)
+    dtypes = version.dtypes
     if isinstance_or_issubclass(dtype, dtypes.Decimal):
         msg = "Casting to Decimal is not supported yet."
         raise NotImplementedError(msg)

narwhals/_ibis/dataframe.py

@@ -9,7 +9,6 @@
 from narwhals.dependencies import get_ibis
 from narwhals.utils import Implementation
 from narwhals.utils import Version
-from narwhals.utils import import_dtypes_module
 from narwhals.utils import validate_backend_version
 
 if TYPE_CHECKING:
@@ -25,7 +24,7 @@
 
 @lru_cache(maxsize=16)
 def native_to_narwhals_dtype(ibis_dtype: Any, version: Version) -> DType:
-    dtypes = import_dtypes_module(version)
+    dtypes = version.dtypes
     if ibis_dtype.is_int64():
         return dtypes.Int64()
     if ibis_dtype.is_int32():

narwhals/_interchange/dataframe.py

@@ -5,7 +5,6 @@
 from typing import Any
 from typing import NoReturn
 
-from narwhals.utils import import_dtypes_module
 from narwhals.utils import parse_version
 
 if TYPE_CHECKING:
@@ -33,7 +32,7 @@ class DtypeKind(enum.IntEnum):
 def map_interchange_dtype_to_narwhals_dtype(
     interchange_dtype: tuple[DtypeKind, int, Any, Any], version: Version
 ) -> DType:
-    dtypes = import_dtypes_module(version)
+    dtypes = version.dtypes
     if interchange_dtype[0] == DtypeKind.INT:
         if interchange_dtype[1] == 64:
             return dtypes.Int64()

narwhals/_pandas_like/dataframe.py

@@ -34,7 +34,6 @@
 from narwhals.utils import _remap_full_join_keys
 from narwhals.utils import check_column_exists
 from narwhals.utils import generate_temporary_column_name
-from narwhals.utils import import_dtypes_module
 from narwhals.utils import parse_columns_to_drop
 from narwhals.utils import parse_version
 from narwhals.utils import scale_bytes
@@ -838,12 +837,11 @@ def to_numpy(self, dtype: Any = None, *, copy: bool | None = None) -> _2DArray:
                 return self.native.to_numpy(dtype=dtype, copy=copy)
             return self.native.to_numpy(copy=copy)
 
-        dtypes = import_dtypes_module(self._version)
-
+        dtype_datetime = self._version.dtypes.Datetime
         to_convert = [
             key
             for key, val in self.schema.items()
-            if val == dtypes.Datetime and val.time_zone is not None  # type: ignore[attr-defined]
+            if isinstance(val, dtype_datetime) and val.time_zone is not None
         ]
         if to_convert:
             df = self.with_columns(
@@ -1053,7 +1051,7 @@ def unpivot(
         )
 
     def explode(self, columns: Sequence[str]) -> Self:
-        dtypes = import_dtypes_module(self._version)
+        dtypes = self._version.dtypes
 
         schema = self.collect_schema()
         for col_to_explode in columns:
@@ -1078,8 +1076,6 @@ def explode(self, columns: Sequence[str]) -> Self:
                 (native_frame[col_name].list.len() == anchor_series).all()
                 for col_name in columns[1:]
             ):
-                from narwhals.exceptions import ShapeError
-
                 msg = "exploded columns must have matching element counts"
                 raise ShapeError(msg)
 

narwhals/_pandas_like/namespace.py

@@ -18,7 +18,6 @@
 from narwhals._pandas_like.selectors import PandasSelectorNamespace
 from narwhals._pandas_like.series import PandasLikeSeries
 from narwhals._pandas_like.utils import align_series_full_broadcast
-from narwhals.utils import import_dtypes_module
 
 if TYPE_CHECKING:
     import pandas as pd
@@ -283,13 +282,11 @@ def concat_str(
         separator: str,
         ignore_nulls: bool,
     ) -> PandasLikeExpr:
-        dtypes = import_dtypes_module(self._version)
+        string = self._version.dtypes.String()
 
         def func(df: PandasLikeDataFrame) -> list[PandasLikeSeries]:
             expr_results = [s for _expr in exprs for s in _expr(df)]
-            series = align_series_full_broadcast(
-                *(s.cast(dtypes.String()) for s in expr_results)
-            )
+            series = align_series_full_broadcast(*(s.cast(string) for s in expr_results))
             null_mask = align_series_full_broadcast(*(s.is_null() for s in expr_results))
 
             if not ignore_nulls:

narwhals/_pandas_like/series.py

@@ -28,7 +28,6 @@
 from narwhals.dependencies import is_pandas_like_series
 from narwhals.exceptions import InvalidOperationError
 from narwhals.utils import Implementation
-from narwhals.utils import import_dtypes_module
 from narwhals.utils import is_list_of
 from narwhals.utils import parse_version
 from narwhals.utils import validate_backend_version
@@ -678,31 +677,25 @@ def __array__(self, dtype: Any, *, copy: bool | None) -> _1DArray:
     def to_numpy(self, dtype: Any = None, *, copy: bool | None = None) -> _1DArray:
         # the default is meant to be None, but pandas doesn't allow it?
         # https://numpy.org/doc/stable/reference/generated/numpy.ndarray.__array__.html
-        copy = copy or self._implementation is Implementation.CUDF
-        dtypes = import_dtypes_module(self._version)
+        dtypes = self._version.dtypes
         if isinstance(self.dtype, dtypes.Datetime) and self.dtype.time_zone is not None:
             s = self.dt.convert_time_zone("UTC").dt.replace_time_zone(None).native
         else:
             s = self.native
 
         has_missing = s.isna().any()
+        kwargs: dict[Any, Any] = {"copy": copy or self._implementation.is_cudf()}
         if has_missing and str(s.dtype) in PANDAS_TO_NUMPY_DTYPE_MISSING:
             if self._implementation is Implementation.PANDAS and self._backend_version < (
                 1,
             ):  # pragma: no cover
-                kwargs = {}
+                ...
             else:
-                kwargs = {"na_value": float("nan")}
-            return s.to_numpy(
-                dtype=dtype or PANDAS_TO_NUMPY_DTYPE_MISSING[str(s.dtype)],
-                copy=copy,
-                **kwargs,
-            )
+                kwargs.update({"na_value": float("nan")})
+            dtype = dtype or PANDAS_TO_NUMPY_DTYPE_MISSING[str(s.dtype)]
         if not has_missing and str(s.dtype) in PANDAS_TO_NUMPY_DTYPE_NO_MISSING:
-            return s.to_numpy(
-                dtype=dtype or PANDAS_TO_NUMPY_DTYPE_NO_MISSING[str(s.dtype)], copy=copy
-            )
-        return s.to_numpy(dtype=dtype, copy=copy)
+            dtype = dtype or PANDAS_TO_NUMPY_DTYPE_NO_MISSING[str(s.dtype)]
+        return s.to_numpy(dtype=dtype, **kwargs)
 
     def to_pandas(self) -> pd.Series[Any]:
         if self._implementation is Implementation.PANDAS:

narwhals/_pandas_like/series_dt.py

@@ -9,7 +9,6 @@
 from narwhals._pandas_like.utils import calculate_timestamp_datetime
 from narwhals._pandas_like.utils import int_dtype_mapper
 from narwhals._pandas_like.utils import is_pyarrow_dtype_backend
-from narwhals.utils import import_dtypes_module
 
 if TYPE_CHECKING:
     from narwhals._pandas_like.series import PandasLikeSeries
@@ -173,7 +172,7 @@ def timestamp(self, time_unit: TimeUnit) -> PandasLikeSeries:
         s = self.native
         dtype = self.compliant.dtype
         mask_na = s.isna()
-        dtypes = import_dtypes_module(self.version)
+        dtypes = self.version.dtypes
         if dtype == dtypes.Date:
             # Date is only supported in pandas dtypes if pyarrow-backed
             s_cast = s.astype("Int32[pyarrow]")

narwhals/_pandas_like/series_list.py

@@ -7,7 +7,6 @@
 from narwhals._pandas_like.utils import get_dtype_backend
 from narwhals._pandas_like.utils import narwhals_to_native_dtype
 from narwhals._pandas_like.utils import set_index
-from narwhals.utils import import_dtypes_module
 
 if TYPE_CHECKING:
     from narwhals._pandas_like.series import PandasLikeSeries
@@ -28,7 +27,7 @@ def len(self) -> PandasLikeSeries:
                 backend_version=backend_version,
             )
         dtype = narwhals_to_native_dtype(
-            import_dtypes_module(self.version).UInt32(),
+            self.version.dtypes.UInt32(),
             get_dtype_backend(result.dtype, implementation),
             implementation,
             backend_version,