Ë
    ðmxi  ã                  óX   — d dl mZ d dlmZmZ d dlmZ erd dlmZ  G d„ dee   «      Zy)é    )Úannotations)ÚTYPE_CHECKINGÚGeneric)ÚSeriesT)ÚNonNestedLiteralc                  ól   — e Zd Zdd„Zdd„Zdd„Zdd„Zdd„Zdd„Zdd„Z	dd„Z
dd	„Zdd
„Zdddœdd„Zy)ÚSeriesListNamespacec                ó   — || _         y )N)Ú_narwhals_series)ÚselfÚseriess     úK/home/htdocs/ttos/venv/lib/python3.12/site-packages/narwhals/series_list.pyÚ__init__zSeriesListNamespace.__init__   s
   € Ø &ˆÕó    c                ó�   — | j                   j                  | j                   j                  j                  j	                  «       «      S )aM  Return the number of elements in each list.

        Null values count towards the total.

        Examples:
            >>> import pyarrow as pa
            >>> import narwhals as nw
            >>> s_native = pa.chunked_array([[[1, 2], [3, 4, None], None, []]])
            >>> s = nw.from_native(s_native, series_only=True)
            >>> s.list.len().to_native()  # doctest: +ELLIPSIS
            <pyarrow.lib.ChunkedArray object at ...>
            [
              [
                2,
                3,
                null,
                0
              ]
            ]
        )r   Ú_with_compliantÚ_compliant_seriesÚlistÚlen©r   s    r   r   zSeriesListNamespace.len   s;   € ð* ×$Ñ$×4Ñ4Ø×!Ñ!×3Ñ3×8Ñ8×<Ñ<Ó>ó
ð 	
r   c                ó�   — | j                   j                  | j                   j                  j                  j	                  «       «      S )as  Get the unique/distinct values in the list.

        Null values are included in the result. The order of unique values is not guaranteed.

        Examples:
            >>> import polars as pl
            >>> import narwhals as nw
            >>> s_native = pl.Series([[1, 1, 2], [3, 3, None], None, []])
            >>> s = nw.from_native(s_native, series_only=True)
            >>> s.list.unique().to_native()  # doctest: +NORMALIZE_WHITESPACE
            shape: (4,)
            Series: '' [list[i64]]
            [
               [1, 2]
               [null, 3]
               null
               []
            ]
        )r   r   r   r   Úuniquer   s    r   r   zSeriesListNamespace.unique(   s;   € ð( ×$Ñ$×4Ñ4Ø×!Ñ!×3Ñ3×8Ñ8×?Ñ?ÓAó
ð 	
r   c                ó’   — | j                   j                  | j                   j                  j                  j	                  |«      «      S )aF  Check if sublists contain the given item.

        Arguments:
            item: Item that will be checked for membership.

        Examples:
            >>> import polars as pl
            >>> import narwhals as nw
            >>> s_native = pl.Series([[1, 2], None, []])
            >>> s = nw.from_native(s_native, series_only=True)
            >>> s.list.contains(1).to_native()  # doctest: +NORMALIZE_WHITESPACE
            shape: (3,)
            Series: '' [bool]
            [
                    true
                    null
                    false
            ]
        )r   r   r   r   Úcontains)r   Úitems     r   r   zSeriesListNamespace.contains@   s=   € ð( ×$Ñ$×4Ñ4Ø×!Ñ!×3Ñ3×8Ñ8×AÑAÀ$ÓGó
ð 	
r   c                ó&  — t        |t        «      s$dt        |«      j                  › d�}t	        |«      ‚|dk  rd|› d�}t        |«      ‚| j                  j                  | j                  j                  j                  j                  |«      «      S )a  Return the value by index in each list.

        Negative indices are not accepted.

        Examples:
            >>> import polars as pl
            >>> import narwhals as nw
            >>> s_native = pl.Series([[1, 2], [3, 4, None], [None, 5]])
            >>> s = nw.from_native(s_native, series_only=True)
            >>> s.list.get(1).to_native()  # doctest: +NORMALIZE_WHITESPACE
            shape: (3,)
            Series: '' [i64]
            [
                    2
                    4
                    5
            ]
        z'Index must be of type 'int'. Got type 'z
' instead.r   zIndex z8 is out of bounds: should be greater than or equal to 0.)Ú
isinstanceÚintÚtypeÚ__name__Ú	TypeErrorÚ
ValueErrorr   r   r   r   Úget)r   ÚindexÚmsgs      r   r#   zSeriesListNamespace.getX   s�   € ô& ˜%¤Ô%à9¼$¸u»+×:NÑ:NÐ9OÈzÐZð ô ˜C“.Ð à�1Š9Ø˜5˜'Ð!YÐZˆCÜ˜S“/Ð!à×$Ñ$×4Ñ4Ø×!Ñ!×3Ñ3×8Ñ8×<Ñ<¸UÓCó
ð 	
r   c                ó�   — | j                   j                  | j                   j                  j                  j	                  «       «      S )a×  Compute the min value of the lists in the array.

        Examples:
            >>> import polars as pl
            >>> import narwhals as nw
            >>> s_native = pl.Series([[1], [3, 4, None]])
            >>> s = nw.from_native(s_native, series_only=True)
            >>> s.list.min().to_native()  # doctest: +NORMALIZE_WHITESPACE
            shape: (2,)
            Series: '' [i64]
            [
                    1
                    3
            ]
        )r   r   r   r   Úminr   s    r   r'   zSeriesListNamespace.miny   ó;   € ð  ×$Ñ$×4Ñ4Ø×!Ñ!×3Ñ3×8Ñ8×<Ñ<Ó>ó
ð 	
r   c                ó�   — | j                   j                  | j                   j                  j                  j	                  «       «      S )aî  Compute the max value of the lists in the array.

        Examples:
            >>> import pyarrow as pa
            >>> import narwhals as nw
            >>> s_native = pa.chunked_array([[[1], [3, 4, None]]])
            >>> s = nw.from_native(s_native, series_only=True)
            >>> s.list.max().to_native()  # doctest: +ELLIPSIS
            <pyarrow.lib.ChunkedArray object at ...>
            [
              [
                1,
                4
              ]
            ]
        )r   r   r   r   Úmaxr   s    r   r*   zSeriesListNamespace.max�   s;   € ð" ×$Ñ$×4Ñ4Ø×!Ñ!×3Ñ3×8Ñ8×<Ñ<Ó>ó
ð 	
r   c                ó�   — | j                   j                  | j                   j                  j                  j	                  «       «      S )aÝ  Compute the mean value of the lists in the array.

        Examples:
            >>> import polars as pl
            >>> import narwhals as nw
            >>> s_native = pl.Series([[1], [3, 4, None]])
            >>> s = nw.from_native(s_native, series_only=True)
            >>> s.list.mean().to_native()  # doctest: +NORMALIZE_WHITESPACE
            shape: (2,)
            Series: '' [f64]
            [
                    1.0
                    3.5
            ]
        )r   r   r   r   Úmeanr   s    r   r,   zSeriesListNamespace.mean¢   s;   € ð  ×$Ñ$×4Ñ4Ø×!Ñ!×3Ñ3×8Ñ8×=Ñ=Ó?ó
ð 	
r   c                ó�   — | j                   j                  | j                   j                  j                  j	                  «       «      S )aô  Compute the median value of the lists in the array.

        Examples:
            >>> import pyarrow as pa
            >>> import narwhals as nw
            >>> s_native = pa.chunked_array([[[1], [3, 4, None]]])
            >>> s = nw.from_native(s_native, series_only=True)
            >>> s.list.median().to_native()  # doctest: +ELLIPSIS
            <pyarrow.lib.ChunkedArray object at ...>
            [
              [
                1,
                3
              ]
            ]
        )r   r   r   r   Úmedianr   s    r   r.   zSeriesListNamespace.median¶   s;   € ð" ×$Ñ$×4Ñ4Ø×!Ñ!×3Ñ3×8Ñ8×?Ñ?ÓAó
ð 	
r   c                ó�   — | j                   j                  | j                   j                  j                  j	                  «       «      S )a×  Compute the sum value of the lists in the array.

        Examples:
            >>> import polars as pl
            >>> import narwhals as nw
            >>> s_native = pl.Series([[1], [3, 4, None]])
            >>> s = nw.from_native(s_native, series_only=True)
            >>> s.list.sum().to_native()  # doctest: +NORMALIZE_WHITESPACE
            shape: (2,)
            Series: '' [i64]
            [
                    1
                    7
            ]
        )r   r   r   r   Úsumr   s    r   r0   zSeriesListNamespace.sumË   r(   r   F©Ú
descendingÚ
nulls_lastc               ó–   — | j                   j                  | j                   j                  j                  j	                  ||¬«      «      S )a^  Sort the lists of the series.

        Arguments:
            descending: Sort in descending order.
            nulls_last: Place null values last.

        Examples:
            >>> import polars as pl
            >>> import narwhals as nw
            >>> s_native = pl.Series([[2, -1, 1], [3, -4, None]])
            >>> s = nw.from_native(s_native, series_only=True)
            >>> s.list.sort().to_native()  # doctest: +NORMALIZE_WHITESPACE
            shape: (2,)
            Series: '' [list[i64]]
            [
                    [-1, 1, 2]
                    [null, -4, 3]
            ]
        r1   )r   r   r   r   Úsort)r   r2   r3   s      r   r5   zSeriesListNamespace.sortß   sG   € ð( ×$Ñ$×4Ñ4Ø×!Ñ!×3Ñ3×8Ñ8×=Ñ=Ø%°*ð >ó ó
ð 	
r   N)r   r   ÚreturnÚNone)r6   r   )r   r   r6   r   )r$   r   r6   r   )r2   Úboolr3   r8   r6   r   )r    Ú
__module__Ú__qualname__r   r   r   r   r#   r'   r*   r,   r.   r0   r5   © r   r   r	   r	      sA   „ ó'ó
ó2
ó0
ó0
óB
ó(
ó*
ó(
ó*
ð( */À5ö 
r   r	   N)	Ú
__future__r   Útypingr   r   Únarwhals.typingr   r   r	   r;   r   r   ú<module>r?      s'   ðÝ "ç )å #áÝ0ôl
˜' 'Ñ*õ l
r   