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 ed d d�dddddœdd„ƒZdS )z pickle compat é    )ÚannotationsN)ÚAny)ÚCompressionOptionsÚFilePathÚReadPickleBufferÚStorageOptionsÚWriteBuffer)Úpickle_compat)Údoc)Ú_shared_docs)Ú
get_handleÚstorage_optionsÚcompression_optionsÚfilepath_or_buffer)r   r   Úinferr   zFilePath | WriteBuffer[bytes]r   Úintr   ÚNone)Úobjr   ÚcompressionÚprotocolr   Úreturnc                 C  s„   |dk rt j}t|d|d|d��P}|jd dv rP|dkrP|j t j| |d�¡ nt j| |j|d� W d	  ƒ n1 sv0    Y  d	S )
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    Pickle (serialize) object to file.

    Parameters
    ----------
    obj : any object
        Any python object.
    filepath_or_buffer : str, path object, or file-like object
        String, path object (implementing ``os.PathLike[str]``), or file-like
        object implementing a binary ``write()`` function.

        .. versionchanged:: 1.0.0
           Accept URL. URL has to be of S3 or GCS.
    {compression_options}

        .. versionchanged:: 1.4.0 Zstandard support.

    protocol : int
        Int which indicates which protocol should be used by the pickler,
        default HIGHEST_PROTOCOL (see [1], paragraph 12.1.2). The possible
        values for this parameter depend on the version of Python. For Python
        2.x, possible values are 0, 1, 2. For Python>=3.0, 3 is a valid value.
        For Python >= 3.4, 4 is a valid value. A negative value for the
        protocol parameter is equivalent to setting its value to
        HIGHEST_PROTOCOL.

    {storage_options}

        .. versionadded:: 1.2.0

        .. [1] https://docs.python.org/3/library/pickle.html

    See Also
    --------
    read_pickle : Load pickled pandas object (or any object) from file.
    DataFrame.to_hdf : Write DataFrame to an HDF5 file.
    DataFrame.to_sql : Write DataFrame to a SQL database.
    DataFrame.to_parquet : Write a DataFrame to the binary parquet format.

    Examples
    --------
    >>> original_df = pd.DataFrame({{"foo": range(5), "bar": range(5, 10)}})  # doctest: +SKIP
    >>> original_df  # doctest: +SKIP
       foo  bar
    0    0    5
    1    1    6
    2    2    7
    3    3    8
    4    4    9
    >>> pd.to_pickle(original_df, "./dummy.pkl")  # doctest: +SKIP

    >>> unpickled_df = pd.read_pickle("./dummy.pkl")  # doctest: +SKIP
    >>> unpickled_df  # doctest: +SKIP
       foo  bar
    0    0    5
    1    1    6
    2    2    7
    3    3    8
    4    4    9
    r   ÚwbF©r   Zis_textr   Úmethod)Úbz2Úxzé   )r   N)ÚpickleÚHIGHEST_PROTOCOLr   r   ÚhandleÚwriteÚdumpsÚdump)r   r   r   r   r   Úhandles© r$   úP/home/ja/django-apps/lartica_env/lib/python3.9/site-packages/pandas/io/pickle.pyÚ	to_pickle   s    Gûr&   Údecompression_options)r   r'   zFilePath | ReadPickleBuffer)r   r   r   c              	   C  s  t tttf}t| d|d|d��Ô}z’zZtjdd��: t dt¡ t	 
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|jdd� Y W W  d  ƒ S 0 W n0 tyâ   tj
|jd	d� Y W  d  ƒ S 0 W d  ƒ n1 � sú0    Y  dS )
aÍ  
    Load pickled pandas object (or any object) from file.

    .. warning::

       Loading pickled data received from untrusted sources can be
       unsafe. See `here <https://docs.python.org/3/library/pickle.html>`__.

    Parameters
    ----------
    filepath_or_buffer : str, path object, or file-like object
        String, path object (implementing ``os.PathLike[str]``), or file-like
        object implementing a binary ``readlines()`` function.

        .. versionchanged:: 1.0.0
           Accept URL. URL is not limited to S3 and GCS.

    {decompression_options}

        .. versionchanged:: 1.4.0 Zstandard support.

    {storage_options}

        .. versionadded:: 1.2.0

    Returns
    -------
    unpickled : same type as object stored in file

    See Also
    --------
    DataFrame.to_pickle : Pickle (serialize) DataFrame object to file.
    Series.to_pickle : Pickle (serialize) Series object to file.
    read_hdf : Read HDF5 file into a DataFrame.
    read_sql : Read SQL query or database table into a DataFrame.
    read_parquet : Load a parquet object, returning a DataFrame.

    Notes
    -----
    read_pickle is only guaranteed to be backwards compatible to pandas 0.20.3.

    Examples
    --------
    >>> original_df = pd.DataFrame({{"foo": range(5), "bar": range(5, 10)}})  # doctest: +SKIP
    >>> original_df  # doctest: +SKIP
       foo  bar
    0    0    5
    1    1    6
    2    2    7
    3    3    8
    4    4    9
    >>> pd.to_pickle(original_df, "./dummy.pkl")  # doctest: +SKIP

    >>> unpickled_df = pd.read_pickle("./dummy.pkl")  # doctest: +SKIP
    >>> unpickled_df  # doctest: +SKIP
       foo  bar
    0    0    5
    1    1    6
    2    2    7
    3    3    8
    4    4    9
    ÚrbFr   T)ÚrecordÚignoreN)Úencodingzlatin-1)ÚAttributeErrorÚImportErrorÚModuleNotFoundErrorÚ	TypeErrorr   ÚwarningsÚcatch_warningsÚsimplefilterÚWarningr   Úloadr   ÚpcÚUnicodeDecodeError)r   r   r   Zexcs_to_catchr#   r$   r$   r%   Úread_pickles   s$    Gû@*r7   )r   N)Ú__doc__Ú
__future__r   r   Útypingr   r0   Zpandas._typingr   r   r   r   r   Zpandas.compatr	   r5   Zpandas.util._decoratorsr
   Zpandas.core.shared_docsr   Zpandas.io.commonr   r   r&   r7   r$   r$   r$   r%   Ú<module>   s0   
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