U mdF @sdZddlmZddlZddlmZddlZddlmZm Z m Z m Z m Z ddl mZddlmZddlmZdd lmZeed ed d d dejdfdddddddddZeed edd ddddddddZdS)z pickle compat ) annotationsN)Any)CompressionOptionsFilePathReadPickleBufferStorageOptions WriteBuffer) pickle_compat)doc) _shared_docs) get_handlestorage_optionscompression_optionsfilepath_or_buffer)r rinferrzFilePath | WriteBuffer[bytes]rintrNone)objr compressionprotocolr returnc CsB|dkrtj}t|d|d|d}tj||j|dW5QRXdS)aZ 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} .. 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 rwbFrZis_textr )rN)pickleHIGHEST_PROTOCOLr dumphandle)rrrrr handlesrI/home/sam/Atlas/atlas_env/lib/python3.8/site-packages/pandas/io/pickle.py to_picklesEr decompression_options)r r!zFilePath | ReadPickleBuffer)rrr c Csttttf}t|d|d|d}zzLtjdd6tdtt |j W5QRWWW5QRSQRXWn2|k rt j |j ddYWW5QRSXWn0t k rt j |j d dYW5QRSXW5QRXdS) 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} .. versionadded:: 1.2.0 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 TypeErrorr warningscatch_warnings simplefilterWarningrloadrpcUnicodeDecodeError)rrr Z excs_to_catchrrrr read_picklejs$H  2(r1)rN)__doc__ __future__rrtypingrr*Zpandas._typingrrrrrZ pandas.compatr r/Zpandas.util._decoratorsr Zpandas.core.shared_docsr Zpandas.io.commonr rr r1rrrrs0       O