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