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? ? ? ? ? ?   55 "i((( 5s  %%TypeIs[SQLFrameDataFrame]cNtddlm}t||SdS)zFCheck whether `df` is a SQLFrame DataFrame without importing SQLFrame.Nr) BaseDataFrameF)rQsqlframe.base.dataframerrW)rRrs r!is_sqlframe_dataframers3~~!999999"m,,, 5r arrAny | _NDArray[_ShapeT]TypeIs[_NDArray[_ShapeT]]cPtx}duot||jS)z=Check whether `arr` is a NumPy Array without importing NumPy.N)r7rWrrnps r!is_numpy_arrayr s'++ Bd * Jz#rz/J/JJr TypeIs[_1DArray]c6t|o |jdkS)z@Check whether `arr` is a 1D NumPy Array without importing NumPy.rrndimrs r!is_numpy_array_1dr #   038q=0r TypeIs[_1DArrayInt]ctx}o.t|o||j|jSrV)r7r issubdtypedtypeintegerrs r!is_numpy_array_1d_intrs={{  1 c " " 1 MM#)RZ 0 0r TypeIs[_2DArray]c6t|o |jdkS)z@Check whether `arr` is a 2D NumPy Array without importing NumPy.rrs r!is_numpy_array_2drrr scalarTypeGuard[_NumpyScalar]cPtx}duot||jS)zACheck whether `scalar` is a NumPy Scalar without importing NumPy.N)r7rWgeneric)rrs r!is_numpy_scalarr$s) ++ Bd * Mz&"*/M/MMr c\t|pt|pt|S)zCheck whether `df` is a pandas-like DataFrame without doing any imports. By "pandas-like", we mean: pandas, Modin, cuDF. )r_rnrw)rRs r!is_pandas_like_dataframer,s/ r " " U&8&<&< U@QRT@U@UUr c\t|pt|pt|S)zCheck whether `ser` is a pandas-like Series without doing any imports. By "pandas-like", we mean: pandas, Modin, cuDF. )rdrqrzr`s r!is_pandas_like_seriesr4s, C OOC$8$8 ON3>> import pandas as pd >>> import polars as pl >>> import numpy as np >>> import narwhals as nw >>> s_pd = pd.Series([1, 2, 3]) >>> s_pl = pl.Series([1, 2, 3]) >>> np_arr = np.array([1, 2, 3]) >>> nw.dependencies.is_into_series(s_pd) True >>> nw.dependencies.is_into_series(s_pl) True >>> nw.dependencies.is_into_series(np_arr) False rr __narwhals_series__)narwhals.seriesr rWrErrr)rr s r!is_into_seriesrFsq4'&&&&& =&)) 0 ="7 8 8 0 M * * 0 $M 2 2 0 ! / / r native_dataframeAny | IntoDataFrameTTypeIs[IntoDataFrameT]cddlm}t||p>> import pandas as pd >>> import polars as pl >>> import numpy as np >>> from narwhals.dependencies import is_into_dataframe >>> df_pd = pd.DataFrame({"a": [1, 2, 3], "b": [4, 5, 6]}) >>> df_pl = pl.DataFrame({"a": [1, 2, 3], "b": [4, 5, 6]}) >>> np_arr = np.array([[1, 4], [2, 5], [3, 6]]) >>> is_into_dataframe(df_pd) True >>> is_into_dataframe(df_pl) True >>> is_into_dataframe(np_arr) False rr__narwhals_dataframe__)narwhals.dataframerrWrErrr)rrs r!is_into_dataframerksv4-,,,,, #Y// 6 #%= > > 6 / 0 0 6 , - - 6 $$4 5 5 r DataFrame[IntoDataFrameT] | Any!TypeIs[DataFrame[IntoDataFrameT]]c.ddlm}t||S)zCheck whether `df` is a Narwhals DataFrame. This is useful if you expect a user to pass in a Narwhals DataFrame directly, and you want to catch both `narwhals.DataFrame` and `narwhals.stable.v1.DataFrame`. rr)rrrWrs r!is_narwhals_dataframers&-,,,,, b) $ $$r lfAny | LazyFrame[FrameT]TypeIs[LazyFrame[FrameT]]c.ddlm}t||S)zCheck whether `lf` is a Narwhals LazyFrame. This is useful if you expect a user to pass in a Narwhals LazyFrame directly, and you want to catch both `narwhals.LazyFrame` and `narwhals.stable.v1.LazyFrame`. r)r )rr rW)rr s r!is_narwhals_lazyframers&-,,,,, b) $ $$r Any | Series[IntoSeriesT]TypeIs[Series[IntoSeriesT]]c.ddlm}t||S)zCheck whether `ser` is a Narwhals Series. This is useful if you expect a user to pass in a Narwhals Series directly, and you want to catch both `narwhals.Series` and `narwhals.stable.v1.Series`. rr )rr rW)r`r s r!is_narwhals_seriesrs&'&&&&& c6 " ""r cRt|o|jSrV)rr is_integerrs r!is_narwhals_series_intrs# c " " =sy';';'='==r )r,rBr)r7r&r"r3rwrzrrrrrnrqrrrrr_rjrrrdrrrrr)rr)rRrrrS)r`rrra)rerrrf)rRrrrk)r`rrro)rerrrr)rRrrru)r`rrrx)rerrr{)r~rrr)rRrrr)rRrrr)rRrrr)rRrrr)rRrrr)r`rrr)r`rrr)rRrrr)r~rrr)rRrrr)rRrrr)rRrrr)rrrr)rrrr)rrrr)rrrr)rrrr)rRrrr)r`rrr)rerrr)rrrr)rrrr)rRrrr)rrrr)r`rrr)d __future__rrtypingrrr+dask.dataframe dataframerFr>rA modin.pandasr%rmr^rrr2r pyspark.sqlsqlrrrPySparkConnectDataFrametyping_extensionsrr narwhals._spark_like.dataframer rr rr narwhals.typingrrrrrrrrr frozensetr]r"r&r)r,r0r3r7r:r<r?rBrGrJrLrNrQr_rdrjrnrqrtrwrzr}rrrrrrrrrrrrrrrrrrrrrrrrrrr__all__rr r!rs #""""" %%%%%%%%KKKMMMKKK%%%%%%RRRRRR33333333@@@@@@77777777&&&&&&                       y+'' ++++ ++++ )))) )))) ,,,, **** )))) 3333 ++++ )))) ....,,,, 0000 8888 ---- NNNN LLLL MMMM OOOO MMMM UUUU VVVV MMMM MMMM KKKK RRRR JJJJ LLLLKKKK 1111 1111 NNNNVVVVPPPP""""J""""J % % % % % % % % # # # #>>>>   r