o ۭj@sdZddlmZddlZddlmZmZddlZddlm Z ddl m Z ddl mZddlmZerHdd lmZmZmZmZmZdd lmZmZe ed ed d ddejdfd"ddZe ed edd d  d#d$d d!ZdS)%z pickle compat ) annotationsN) TYPE_CHECKINGAny) pickle_compat)doc) _shared_docs) get_handle)CompressionOptionsFilePathReadPickleBufferStorageOptions WriteBuffer) DataFrameSeriesstorage_optionscompression_optionsfilepath_or_buffer)rrinferobjrFilePath | WriteBuffer[bytes] compressionr protocolintStorageOptions | NonereturnNonecCsX|dkrtj}t|d|d|d}tj||j|dWddS1s%wYdS)a9 Pickle (serialize) object to file. Parameters ---------- obj : any object Any python object. filepath_or_buffer : str, path object, or file-like object String, path object (implementing ``os.PathLike[str]``), or file-like object implementing a binary ``write()`` function. Also accepts URL. URL has to be of S3 or GCS. {compression_options} .. versionchanged:: 1.4.0 Zstandard support. protocol : int Int which indicates which protocol should be used by the pickler, default HIGHEST_PROTOCOL (see [1], paragraph 12.1.2). The possible values for this parameter depend on the version of Python. For Python 2.x, possible values are 0, 1, 2. For Python>=3.0, 3 is a valid value. For Python >= 3.4, 4 is a valid value. A negative value for the protocol parameter is equivalent to setting its value to HIGHEST_PROTOCOL. {storage_options} .. [1] https://docs.python.org/3/library/pickle.html See Also -------- read_pickle : Load pickled pandas object (or any object) from file. DataFrame.to_hdf : Write DataFrame to an HDF5 file. DataFrame.to_sql : Write DataFrame to a SQL database. DataFrame.to_parquet : Write a DataFrame to the binary parquet format. Examples -------- >>> original_df = pd.DataFrame({{"foo": range(5), "bar": range(5, 10)}}) # doctest: +SKIP >>> original_df # doctest: +SKIP foo bar 0 0 5 1 1 6 2 2 7 3 3 8 4 4 9 >>> pd.to_pickle(original_df, "./dummy.pkl") # doctest: +SKIP >>> unpickled_df = pd.read_pickle("./dummy.pkl") # doctest: +SKIP >>> unpickled_df # doctest: +SKIP foo bar 0 0 5 1 1 6 2 2 7 3 3 8 4 4 9 rwbFris_textr)rN)pickleHIGHEST_PROTOCOLrdumphandle)rrrrrhandlesr$M/var/www/html/CropPilot/venv/lib/python3.10/site-packages/pandas/io/pickle.py to_pickle!sC"r&decompression_options)rr'FilePath | ReadPickleBufferDataFrame | Seriesc Csttttf}t|d|d|dk}zIz-tjddtdtt |j WdWWWdS1s8wYWn|yWt j |j ddYWWdSwWnt yqt j |j d dYWdSwWddS1s}wYdS) a Load pickled pandas object (or any object) from file. .. warning:: Loading pickled data received from untrusted sources can be unsafe. See `here `__. 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. Also accepts URL. URL is not limited to S3 and GCS. {decompression_options} .. versionchanged:: 1.4.0 Zstandard support. {storage_options} Returns ------- 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 provided the object was serialized with to_pickle. 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 rbFrT)recordignoreN)encodingzlatin-1)AttributeError ImportErrorModuleNotFoundError TypeErrorrwarningscatch_warnings simplefilterWarningrloadr"pcUnicodeDecodeError)rrr excs_to_catchr#r$r$r% read_picklers8 F    "r:) rrrrrr rrrrrr)rN)rr(rr rrrr))__doc__ __future__rrtypingrrr2 pandas.compatrr7pandas.util._decoratorsrpandas.core.shared_docsrpandas.io.commonrpandas._typingr r r r r pandasrrr r&r:r$r$r$r%s6      M