B Y0d@sdZddlZddlmZddlZddlmZmZmZddl m Z ddl m Z ddlmZddlmZe ejd d d ejdfeeeeed d dZe ejd d deeedddZdS)z pickle compat N)Any)CompressionOptionsFilePathOrBufferStorageOptions) pickle_compat)doc)generic) get_handlestorage_options)r infer)objfilepath_or_buffer compressionprotocolr c Csp|dkrtj}t|d|d|dF}|jddkrP|dkrP|jtj||dntj||j|dWd QRXd 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") rwbF)ris_textr method)bz2xz)rN)pickleHIGHEST_PROTOCOLr rhandlewritedumpsdump)r r rrr handlesrB/var/www/html/venv/lib/python3.7/site-packages/pandas/io/pickle.py to_pickles Hr)r rr c Csttttf}t|d|d|d~}yVy0tjddtdtt |j SQRXWn |k rrt j |j ddSXWn t k rt j |j d dSXWdQRXdS) ax 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 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)rrr T)recordignoreN)encodingzlatin-1)AttributeError ImportErrorModuleNotFoundError TypeErrorr warningscatch_warnings simplefilterWarningrloadrpcUnicodeDecodeError)r rr Z excs_to_catchrrrr read_pickle{s"H  r/)r N)__doc__rtypingrr(Zpandas._typingrrrZ pandas.compatrr-Zpandas.util._decoratorsrZ pandas.corerZpandas.io.commonr Z _shared_docsrintrr/rrrrs     b