"""Narwhals-level equivalent of `CompliantNamespace`.""" from __future__ import annotations from typing import ( TYPE_CHECKING, Any, Callable, Generic, Literal, Protocol, TypeVar, overload, ) from narwhals._compliant.typing import CompliantNamespaceAny, CompliantNamespaceT_co from narwhals._utils import Implementation, Version from narwhals.dependencies import ( get_cudf, get_modin, get_pandas, get_polars, get_pyarrow, is_dask_dataframe, is_duckdb_relation, is_ibis_table, is_pyspark_connect_dataframe, is_pyspark_dataframe, is_sqlframe_dataframe, ) if TYPE_CHECKING: from collections.abc import Collection, Sized from typing import ClassVar import duckdb import pandas as pd import polars as pl import pyarrow as pa import pyspark.sql as pyspark_sql from pyspark.sql.connect.dataframe import DataFrame as PySparkConnectDataFrame from typing_extensions import Self, TypeAlias, TypeIs from narwhals._arrow.namespace import ArrowNamespace from narwhals._dask.namespace import DaskNamespace from narwhals._duckdb.namespace import DuckDBNamespace from narwhals._ibis.namespace import IbisNamespace from narwhals._pandas_like.namespace import PandasLikeNamespace from narwhals._polars.namespace import PolarsNamespace from narwhals._spark_like.dataframe import SQLFrameDataFrame from narwhals._spark_like.namespace import SparkLikeNamespace from narwhals._typing import ( Arrow, Backend, Dask, DuckDB, EagerAllowed, Ibis, IntoBackend, PandasLike, Polars, SparkLike, ) from narwhals.typing import NativeDataFrame, NativeLazyFrame, NativeSeries T = TypeVar("T") _Guard: TypeAlias = "Callable[[Any], TypeIs[T]]" EagerAllowedNamespace: TypeAlias = "Namespace[PandasLikeNamespace] | Namespace[ArrowNamespace] | Namespace[PolarsNamespace]" class _BasePandasLike(Sized, Protocol): index: Any """`mypy` doesn't like the asymmetric `property` setter in `pandas`.""" def __getitem__(self, key: Any, /) -> Any: ... def __mul__(self, other: float | Collection[float] | Self) -> Self: ... def __floordiv__(self, other: float | Collection[float] | Self) -> Self: ... @property def loc(self) -> Any: ... @property def shape(self) -> tuple[int, ...]: ... def set_axis(self, labels: Any, *, axis: Any = ..., copy: bool = ...) -> Self: ... def copy(self, deep: bool = ...) -> Self: ... # noqa: FBT001 def rename(self, *args: Any, inplace: Literal[False], **kwds: Any) -> Self: """`inplace=False` is required to avoid (incorrect?) default overloads.""" ... class _BasePandasLikeFrame(NativeDataFrame, _BasePandasLike, Protocol): ... class _BasePandasLikeSeries(NativeSeries, _BasePandasLike, Protocol): def where(self, cond: Any, other: Any = ..., **kwds: Any) -> Any: ... class _NativeDask(Protocol): _partition_type: type[pd.DataFrame] class _CuDFDataFrame(_BasePandasLikeFrame, Protocol): def to_pylibcudf(self, *args: Any, **kwds: Any) -> Any: ... class _CuDFSeries(_BasePandasLikeSeries, Protocol): def to_pylibcudf(self, *args: Any, **kwds: Any) -> Any: ... class _NativeIbis(Protocol): def sql(self, *args: Any, **kwds: Any) -> Any: ... def __pyarrow_result__(self, *args: Any, **kwds: Any) -> Any: ... def __pandas_result__(self, *args: Any, **kwds: Any) -> Any: ... def __polars_result__(self, *args: Any, **kwds: Any) -> Any: ... class _ModinDataFrame(_BasePandasLikeFrame, Protocol): _pandas_class: type[pd.DataFrame] class _ModinSeries(_BasePandasLikeSeries, Protocol): _pandas_class: type[pd.Series[Any]] _NativePolars: TypeAlias = "pl.DataFrame | pl.LazyFrame | pl.Series" _NativeArrow: TypeAlias = "pa.Table | pa.ChunkedArray[Any]" _NativeDuckDB: TypeAlias = "duckdb.DuckDBPyRelation" _NativePandas: TypeAlias = "pd.DataFrame | pd.Series[Any]" _NativeModin: TypeAlias = "_ModinDataFrame | _ModinSeries" _NativeCuDF: TypeAlias = "_CuDFDataFrame | _CuDFSeries" _NativePandasLikeSeries: TypeAlias = "pd.Series[Any] | _CuDFSeries | _ModinSeries" _NativePandasLikeDataFrame: TypeAlias = ( "pd.DataFrame | _CuDFDataFrame | _ModinDataFrame" ) _NativePandasLike: TypeAlias = "_NativePandasLikeDataFrame |_NativePandasLikeSeries" _NativeSQLFrame: TypeAlias = "SQLFrameDataFrame" _NativePySpark: TypeAlias = "pyspark_sql.DataFrame" _NativePySparkConnect: TypeAlias = "PySparkConnectDataFrame" _NativeSparkLike: TypeAlias = ( "_NativeSQLFrame | _NativePySpark | _NativePySparkConnect" ) NativeKnown: TypeAlias = "_NativePolars | _NativeArrow | _NativePandasLike | _NativeSparkLike | _NativeDuckDB | _NativeDask | _NativeIbis" NativeUnknown: TypeAlias = "NativeDataFrame | NativeSeries | NativeLazyFrame" NativeAny: TypeAlias = "NativeKnown | NativeUnknown" __all__ = ["Namespace"] class Namespace(Generic[CompliantNamespaceT_co]): _compliant_namespace: CompliantNamespaceT_co _version: ClassVar[Version] = Version.MAIN def __init__(self, namespace: CompliantNamespaceT_co, /) -> None: self._compliant_namespace = namespace def __init_subclass__(cls, *args: Any, version: Version, **kwds: Any) -> None: super().__init_subclass__(*args, **kwds) if isinstance(version, Version): cls._version = version else: msg = f"Expected {Version} but got {type(version).__name__!r}" raise TypeError(msg) def __repr__(self) -> str: return f"Namespace[{type(self.compliant).__name__}]" @property def compliant(self) -> CompliantNamespaceT_co: return self._compliant_namespace @property def implementation(self) -> Implementation: return self.compliant._implementation @property def version(self) -> Version: return self._version @overload @classmethod def from_backend(cls, backend: PandasLike, /) -> Namespace[PandasLikeNamespace]: ... @overload @classmethod def from_backend(cls, backend: Polars, /) -> Namespace[PolarsNamespace]: ... @overload @classmethod def from_backend(cls, backend: Arrow, /) -> Namespace[ArrowNamespace]: ... @overload @classmethod def from_backend(cls, backend: SparkLike, /) -> Namespace[SparkLikeNamespace]: ... @overload @classmethod def from_backend(cls, backend: DuckDB, /) -> Namespace[DuckDBNamespace]: ... @overload @classmethod def from_backend(cls, backend: Dask, /) -> Namespace[DaskNamespace]: ... @overload @classmethod def from_backend(cls, backend: Ibis, /) -> Namespace[IbisNamespace]: ... @overload @classmethod def from_backend(cls, backend: EagerAllowed, /) -> EagerAllowedNamespace: ... @overload @classmethod def from_backend( cls, backend: IntoBackend[Backend], / ) -> Namespace[CompliantNamespaceAny]: ... @classmethod def from_backend( cls: type[Namespace[Any]], backend: IntoBackend[Backend], / ) -> Namespace[Any]: """Instantiate from native namespace module, string, or Implementation. Arguments: backend: native namespace module, string, or Implementation. Examples: >>> from narwhals._namespace import Namespace >>> Namespace.from_backend("polars") Namespace[PolarsNamespace] """ impl = Implementation.from_backend(backend) backend_version = impl._backend_version() # noqa: F841 version = cls._version ns: CompliantNamespaceAny if impl.is_pandas_like(): from narwhals._pandas_like.namespace import PandasLikeNamespace ns = PandasLikeNamespace(implementation=impl, version=version) elif impl.is_polars(): from narwhals._polars.namespace import PolarsNamespace ns = PolarsNamespace(version=version) elif impl.is_pyarrow(): from narwhals._arrow.namespace import ArrowNamespace ns = ArrowNamespace(version=version) elif impl.is_spark_like(): from narwhals._spark_like.namespace import SparkLikeNamespace ns = SparkLikeNamespace(implementation=impl, version=version) elif impl.is_duckdb(): from narwhals._duckdb.namespace import DuckDBNamespace ns = DuckDBNamespace(version=version) elif impl.is_dask(): from narwhals._dask.namespace import DaskNamespace ns = DaskNamespace(version=version) elif impl.is_ibis(): from narwhals._ibis.namespace import IbisNamespace ns = IbisNamespace(version=version) else: msg = "Not supported Implementation" # pragma: no cover raise AssertionError(msg) return cls(ns) @overload @classmethod def from_native_object( cls, native: _NativePolars, / ) -> Namespace[PolarsNamespace]: ... @overload @classmethod def from_native_object( cls, native: _NativePandas, / ) -> Namespace[PandasLikeNamespace[pd.DataFrame, pd.Series[Any]]]: ... @overload @classmethod def from_native_object(cls, native: _NativeArrow, /) -> Namespace[ArrowNamespace]: ... @overload @classmethod def from_native_object( cls, native: _NativeSparkLike, / ) -> Namespace[SparkLikeNamespace]: ... @overload @classmethod def from_native_object( cls, native: _NativeDuckDB, / ) -> Namespace[DuckDBNamespace]: ... @overload @classmethod def from_native_object(cls, native: _NativeDask, /) -> Namespace[DaskNamespace]: ... @overload @classmethod def from_native_object(cls, native: _NativeIbis, /) -> Namespace[IbisNamespace]: ... @overload @classmethod def from_native_object( cls, native: _NativeModin, / ) -> Namespace[PandasLikeNamespace[_ModinDataFrame, _ModinSeries]]: ... @overload @classmethod def from_native_object( cls, native: _NativeCuDF, / ) -> Namespace[PandasLikeNamespace[_CuDFDataFrame, _CuDFSeries]]: ... @overload @classmethod def from_native_object( cls, native: _NativePandasLike, / ) -> Namespace[PandasLikeNamespace[Any, Any]]: ... @overload @classmethod def from_native_object( cls, native: NativeUnknown, / ) -> Namespace[CompliantNamespaceAny]: ... @classmethod def from_native_object( cls: type[Namespace[Any]], native: NativeAny, / ) -> Namespace[Any]: impl: Backend if is_native_polars(native): impl = Implementation.POLARS elif is_native_pandas(native): impl = Implementation.PANDAS elif is_native_arrow(native): impl = Implementation.PYARROW elif is_native_spark_like(native): impl = ( Implementation.SQLFRAME if is_native_sqlframe(native) else Implementation.PYSPARK_CONNECT if is_native_pyspark_connect(native) else Implementation.PYSPARK ) elif is_native_dask(native): # pragma: no cover impl = Implementation.DASK elif is_native_duckdb(native): impl = Implementation.DUCKDB elif is_native_cudf(native): # pragma: no cover impl = Implementation.CUDF elif is_native_modin(native): # pragma: no cover impl = Implementation.MODIN elif is_native_ibis(native): impl = Implementation.IBIS else: msg = f"Unsupported type: {type(native).__qualname__!r}" raise TypeError(msg) return cls.from_backend(impl) def is_native_polars(obj: Any) -> TypeIs[_NativePolars]: return (pl := get_polars()) is not None and isinstance( obj, (pl.DataFrame, pl.Series, pl.LazyFrame) ) def is_native_arrow(obj: Any) -> TypeIs[_NativeArrow]: return (pa := get_pyarrow()) is not None and isinstance( obj, (pa.Table, pa.ChunkedArray) ) def is_native_dask(obj: Any) -> TypeIs[_NativeDask]: return is_dask_dataframe(obj) is_native_duckdb: _Guard[_NativeDuckDB] = is_duckdb_relation is_native_sqlframe: _Guard[_NativeSQLFrame] = is_sqlframe_dataframe is_native_pyspark: _Guard[_NativePySpark] = is_pyspark_dataframe is_native_pyspark_connect: _Guard[_NativePySparkConnect] = is_pyspark_connect_dataframe def is_native_pandas(obj: Any) -> TypeIs[_NativePandas]: return (pd := get_pandas()) is not None and isinstance(obj, (pd.DataFrame, pd.Series)) def is_native_modin(obj: Any) -> TypeIs[_NativeModin]: return (mpd := get_modin()) is not None and isinstance( obj, (mpd.DataFrame, mpd.Series) ) # pragma: no cover def is_native_cudf(obj: Any) -> TypeIs[_NativeCuDF]: return (cudf := get_cudf()) is not None and isinstance( obj, (cudf.DataFrame, cudf.Series) ) # pragma: no cover def is_native_pandas_like(obj: Any) -> TypeIs[_NativePandasLike]: return ( is_native_pandas(obj) or is_native_cudf(obj) or is_native_modin(obj) ) # pragma: no cover def is_native_spark_like(obj: Any) -> TypeIs[_NativeSparkLike]: return ( is_native_sqlframe(obj) or is_native_pyspark(obj) or is_native_pyspark_connect(obj) ) def is_native_ibis(obj: Any) -> TypeIs[_NativeIbis]: return is_ibis_table(obj)