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B �5�g� � @ s� d Z ddlZddlmZ ddlZddlmZmZmZ ddl m Z ddl m Z ddlmZ ddlmZ e ejd d �d ejdfeeeeed �d d��Ze ejd d �deeed�dd��ZdS )z pickle compat � N)�Any)�CompressionOptions�FilePathOrBuffer�StorageOptions)� pickle_compat)�doc)�generic)� get_handle�storage_options)r �infer)�obj�filepath_or_buffer� compression�protocolr c C sp |dk rt j}t|d|d|d��F}|jd dkrP|dkrP|j�t j| |d�� nt j| |j|d� W d Q R X d S ) a& Pickle (serialize) object to file. Parameters ---------- obj : any object Any python object. filepath_or_buffer : str, path object or file-like object File path, URL, or buffer where the pickled object will be stored. .. versionchanged:: 1.0.0 Accept URL. URL has to be of S3 or GCS. compression : {{'infer', 'gzip', 'bz2', 'zip', 'xz', None}}, default 'infer' If 'infer' and 'path_or_url' is path-like, then detect compression from the following extensions: '.gz', '.bz2', '.zip', or '.xz' (otherwise no compression) If 'infer' and 'path_or_url' is not path-like, then use None (= no decompression). 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)}}) >>> original_df foo bar 0 0 5 1 1 6 2 2 7 3 3 8 4 4 9 >>> pd.to_pickle(original_df, "./dummy.pkl") >>> unpickled_df = pd.read_pickle("./dummy.pkl") >>> unpickled_df foo bar 0 0 5 1 1 6 2 2 7 3 3 8 4 4 9 >>> import os >>> os.remove("./dummy.pkl") r �wbF)r �is_textr �method)�bz2�xz� )r N)�pickle�HIGHEST_PROTOCOLr r �handle�write�dumps�dump)r r r r r �handles� r �F/home/digitalm-up/venv/lib/python3.7/site-packages/pandas/io/pickle.py� to_pickle s Hr )r r r c C s� t tttf}t| d|d|d��~}yVy0tjdd�� t�dt� t � |j �S Q R X W n |k rr t j |j dd�S X W n t k r� t j |j d d�S X W dQ R X dS ) ax 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 File path, URL, or buffer where the pickled object will be loaded from. .. versionchanged:: 1.0.0 Accept URL. URL is not limited to S3 and GCS. compression : {{'infer', 'gzip', 'bz2', 'zip', 'xz', None}}, default 'infer' If 'infer' and 'path_or_url' is path-like, then detect compression from the following extensions: '.gz', '.bz2', '.zip', or '.xz' (otherwise no compression) If 'infer' and 'path_or_url' is not path-like, then use None (= no decompression). {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)}}) >>> original_df foo bar 0 0 5 1 1 6 2 2 7 3 3 8 4 4 9 >>> pd.to_pickle(original_df, "./dummy.pkl") >>> unpickled_df = pd.read_pickle("./dummy.pkl") >>> unpickled_df foo bar 0 0 5 1 1 6 2 2 7 3 3 8 4 4 9 >>> import os >>> os.remove("./dummy.pkl") �rbF)r r r T)�record�ignoreN)�encodingzlatin-1)�AttributeError� ImportError�ModuleNotFoundError� TypeErrorr �warnings�catch_warnings� simplefilter�Warningr �loadr �pc�UnicodeDecodeError)r r r Z excs_to_catchr r r r � read_pickle{ s" H r/ )r N)�__doc__r �typingr r( Zpandas._typingr r r Z pandas.compatr r- Zpandas.util._decoratorsr Z pandas.corer Zpandas.io.commonr Z _shared_docsr �intr r/ r r r r �<module> s b
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