h8<SSKJr SSKrSSKJr SSKJr \(aSSKrSSKJr SSK r SSK r SSK J r SSK rSSKrSSKrSSKJr SSKJr SSKJr SSKJr SSKJr SS KJr SS KJ r SS K!J"r" SS K#J$r$ SS K#J%r% SSK#J&r& SSK#J'r' SSK#J(r( SSK#J)r) SSK#J*r* SSK#J+r+ \,"S/5r-SDSjr.SDSjr/SDSjr0SDSjr1SDSjr2SDSjr3SDSjr4SDSjr5SDSjr6SDSjr7SDSjr8SDS jr9SDS!jr:SDS"jr;SDS#jrSGS&jr?SHS'jr@SIS(jrASJS)jrBSKS*jrCSLS+jrDSMS,jrESNS-jrFSOS.jrGSPS/jrHSQS0jrISRS1jrJSSS2jrKSTS3jrLSUS4jrMSVS5jrNSWS6jrOSXS7jrPSYS8jrQSZS9jrRS[S:jrSS\S;jrTS]S<jrUS^S=jrVS_S>jrWS`S?jrXSaS@jrYSbSAjrZScSBjr[/SCQr\g)d) annotationsN) TYPE_CHECKING)Any) TypeGuard)TypeIs)ArrowChunkedArray)SQLFrameDataFrame DataFrame LazyFrameSeries)FrameT)IntoDataFrameT) IntoSeriesT)_1DArray)_2DArray)_NDArray) _NumpyScalar)_ShapeT fireduckscB[RRSS5$)z;Get Polars module (if already imported - else return None).polarsNsysmodulesgetG/var/www/html/env/lib/python3.13/site-packages/narwhals/dependencies.py get_polarsr"+ ;;??8T **r cB[RRSS5$)z;Get pandas module (if already imported - else return None).pandasNrrr r! get_pandasr&0r#r cb[RRSS5=nb UR$g)zAGet modin.pandas module (if already imported - else return None).modinN)rrrr%)r(s r! get_modinr)5s)$//<|| r cB[RRSS5$)z9Get cudf module (if already imported - else return None).cudfNrrr r!get_cudfr,< ;;??64 ((r cB[RRSS5$)z9Get cupy module (if already imported - else return None).cupyNrrr r!get_cupyr0Ar-r cB[RRSS5$)zGet dask_expr module (if already imported - else return None). dask_exprNrrr r! get_dask_exprrEds ;;??; --r cB[RRSS5$)z# UHPn[RRUS5=mSL=(a [TTRR 5v MR g7fN)rrr isinstancer%r ).0 module_namedfmods r! &is_pandas_dataframe..zsRV(K  T2 24? 1 r3::// 0 1'AA)r&rQr any IMPORT_HOOKS)rTpdrUs` @r!is_pandas_dataframer\xsF< R , MB 1M RUV(VSr c^^[5=nSL=(a [TUR5=(d [UU4Sj[55$)z@Check whether `ser` is a pandas Series without importing pandas.Nc3># UHPn[RRUS5=mSL=(a [TTRR 5v MR g7frP)rrrrQr%r)rRrSrUsers r!rV#is_pandas_series..sRT(K  T2 24? / sCJJ-- . /'rX)r&rQrrYrZ)r_r[rUs` @r!is_pandas_seriesrasF< R , KC1K PST(TQr c^^[5=nSL=(a [TUR5=(d [UU4Sj[55$)zACheck whether `index` is a pandas Index without importing pandas.Nc3># UHPn[RRUS5=mSL=(a [TTRR 5v MR g7frP)rrrrQr%Index)rRrSindexrUs r!rV"is_pandas_index..sRU(K  T2 24? 0 ucjj.. / 0'rX)r&rQrdrYrZ)rer[rUs` @r!is_pandas_indexrgsF< R , LE2881L QTU(URr cV[5=nSL=(a [XR5$)z@Check whether `df` is a modin DataFrame without importing modin.N)r)rQr )rTmpds r!is_modin_dataframerjs"; Ct + M 2}}0MMr cV[5=nSL=(a [XR5$)z>Check whether `ser` is a modin Series without importing modin.N)r)rQr)r_ris r!is_modin_seriesrls"; Ct + K 3 0KKr cV[5=nSL=(a [XR5$)z?Check whether `index` is a modin Index without importing modin.N)r)rQrd)reris r!is_modin_indexrns); Ct +   yy1r cV[5=nSL=(a [XR5$)z>Check whether `df` is a cudf DataFrame without importing cudf.N)r,rQr )rTr+s r!is_cudf_dataframerps"J Dt + N 2~~0NNr cV[5=nSL=(a [XR5$)zCheck whether `df` is a Dask DataFrame without importing Dask.N)r<rQr )rTdds r!is_dask_dataframerws#$& &Bt 3 T 2||8TTr cV[5=nSL=(a [XR5$)zACheck whether `df` is a DuckDB Relation without importing DuckDB.N)r?rQDuckDBPyRelation)rTr>s r!is_duckdb_relationrzs+ l "F4 / J # #5r c~[5=nSL=(a) [XRRR5$)z:Check whether `df` is a Ibis Table without importing Ibis.N)rBrQexprtypesTable)rTrAs r! is_ibis_tablers,J Dt + U 2yy?T?T0UUr cV[5=nSL=(a [XR5$)zBCheck whether `df` is a Polars DataFrame without importing Polars.N)r"rQr rTpls r!is_polars_dataframer", Bt + L 2||0LLr cV[5=nSL=(a [XR5$)zBCheck whether `df` is a Polars LazyFrame without importing Polars.N)r"rQr rs r!is_polars_lazyframerrr cV[5=nSL=(a [XR5$)z@Check whether `ser` is a Polars Series without importing Polars.N)r"rQr)r_rs r!is_polars_seriesrs", Bt + J 3 0JJr cV[5=nSL=(a [XR5$)zHCheck whether `ser` is a PyArrow ChunkedArray without importing PyArrow.N)r3rQ ChunkedArray)r_pas r!is_pyarrow_chunked_arrayrs$- B , QC1QQr cV[5=nSL=(a [XR5$)z@Check whether `df` is a PyArrow Table without importing PyArrow.N)r3rQr~)rTrs r!is_pyarrow_tablers"- B , IB1IIr ch[[5=nSL=(a [XR55$)zDCheck whether `df` is a PySpark DataFrame without importing PySpark.N)boolrJrQr )rT pyspark_sqls r!is_pyspark_dataframers2 ') )$6 2 r00 1 r c<[5bSSKJn [X5$g)zFCheck whether `df` is a SQLFrame DataFrame without importing SQLFrame.r) BaseDataFrameF)rMsqlframe.base.dataframerrQ)rTrs r!is_sqlframe_dataframers~!9",, r cV[5=nSL=(a [XR5$)z=Check whether `arr` is a NumPy Array without importing NumPy.N)r7rQndarray)arrnps r!is_numpy_arrayrs"+ Bd * Jz#zz/JJr cD[U5=(a URS:H$)z@Check whether `arr` is a 1D NumPy Array without importing NumPy.rndimrs r!is_numpy_array_1dr #  0388q=0r cD[U5=(a URS:H$)z@Check whether `arr` is a 2D NumPy Array without importing NumPy.rrs r!is_numpy_array_2drrr cV[5=nSL=(a [XR5$)zACheck whether `scalar` is a NumPy Scalar without importing NumPy.N)r7rQgeneric)scalarrs r!is_numpy_scalarrs$ + Bd * Mz&**/MMr c`[U5=(d [U5=(d [U5$)zzCheck whether `df` is a pandas-like DataFrame without doing any imports. By "pandas-like", we mean: pandas, Modin, cuDF. )r\rjrp)rTs r!is_pandas_like_dataframer s& r " U&8&< U@QRT@UUr c`[U5=(d [U5=(d [U5$)zxCheck whether `ser` is a pandas-like Series without doing any imports. By "pandas-like", we mean: pandas, Modin, cuDF. )rarlrr)r_s r!is_pandas_like_seriesrs# C OOC$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.seriesrrQhasattrrrr) native_seriesrs r!is_into_seriesr#sQ4' =) 0 ="7 8 0 M * 0 $M 2 0 ! / r cSSKJn [X5=(dB [US5=(d/ [ U5=(d [ U5=(d [ U5$)aCheck whether `native_dataframe` can be converted to a Narwhals DataFrame. Arguments: native_dataframe: The object to check. Returns: `True` if `native_dataframe` can be converted to a Narwhals DataFrame, `False` otherwise. Examples: >>> 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.dataframer rQrrrr)native_dataframer s r!is_into_dataframerHsV4- #/ 6 #%= > 6 / 0 6 , - 6 $$4 5 r c$SSKJn [X5$)zCheck whether `df` is a Narwhals DataFrame. This is useful if you expect a user to pass in a Narwhals DataFrame directly, and you want to catch both ``narwhals.DataFrame`` and ``narwhals.stable.v1.DataFrame`. rr )rr rQ)rTr s r!is_narwhals_dataframerms- b $$r c$SSKJn [X5$)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`. rr )rr rQ)lfr s r!is_narwhals_lazyframer{s- b $$r c$SSKJn [X5$)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)rrrQ)r_rs r!is_narwhals_seriesrs' c ""r )r,rBr)r7r&r"r3rprrrwrrrrjrlrrrrr\rgrrrarrrrr)returnr)rTrrzTypeIs[pd.DataFrame])r_rrzTypeIs[pd.Series[Any]])rerrzTypeIs[pd.Index[Any]])rTrrzTypeIs[mpd.DataFrame])r_rrzTypeIs[mpd.Series])rerrzTypeIs[mpd.Index])rTrrzTypeIs[cudf.DataFrame])r_rrzTypeIs[cudf.Series[Any]])rerrzTypeIs[cudf.Index])rTrrzTypeIs[dd.DataFrame])rTrrzTypeIs[duckdb.DuckDBPyRelation])rTrrzTypeIs[ibis.Table])rTrrzTypeIs[pl.DataFrame])rTrrzTypeIs[pl.LazyFrame])r_rrzTypeIs[pl.Series])r_zAny | ArrowChunkedArrayrzTypeIs[ArrowChunkedArray])rTrrzTypeIs[pa.Table])rTrrzTypeIs[pyspark_sql.DataFrame])rTrrzTypeIs[SQLFrameDataFrame])rzAny | _NDArray[_ShapeT]rzTypeIs[_NDArray[_ShapeT]])rrrzTypeIs[_1DArray])rrrzTypeIs[_2DArray])rrrzTypeGuard[_NumpyScalar])rTrrr)r_rrr)rerrr)rzAny | IntoSeriesTrzTypeIs[IntoSeriesT])rzAny | IntoDataFrameTrzTypeIs[IntoDataFrameT])rTzDataFrame[IntoDataFrameT] | Anyrz!TypeIs[DataFrame[IntoDataFrameT]])rzAny | LazyFrame[FrameT]rzTypeIs[LazyFrame[FrameT]])r_zAny | Series[IntoSeriesT]rzTypeIs[Series[IntoSeriesT]])] __future__rrtypingrrr+dask.dataframe dataframervr>rA modin.pandasr%rir[rrr2r pyspark.sqlsqlrtyping_extensionsrrnarwhals._arrow.typingrnarwhals._spark_like.dataframer rr r rrnarwhals.typingrrrrrrrr frozensetrZr"r&r)r,r0r3r7r:r<r?rBrErHrJrMr\rargrjrlrnrprrrtrwrzrrrrrrrrrrrrrrrrrrrr__all__rr r!rs# %+(8@,,&&.+(((,' +' + + ) ) , * ) 3 + ) . , 0 - N L O M U V M M K R RRJ K 1 1 NVP"J"J %' %& % % # r