Name	Size	Mode	Actions
api.cpython-36.pyc	1096	0644	editdlrm
clipboards.cpython-36.pyc	3392	0644	editdlrm
common.cpython-36.pyc	14064	0644	editdlrm
date_converters.cpython-36.pyc	1947	0644	editdlrm
feather_format.cpython-36.pyc	2936	0644	editdlrm
gbq.cpython-36.pyc	7459	0644	editdlrm
html.cpython-36.pyc	31977	0644	editdlrm
orc.cpython-36.pyc	1802	0644	editdlrm
parquet.cpython-36.pyc	9500	0644	editdlrm
parsers.cpython-36.pyc	88200	0644	editdlrm
pickle.cpython-36.pyc	5679	0644	editdlrm
pytables.cpython-36.pyc	130805	0644	editdlrm
spss.cpython-36.pyc	1328	0644	editdlrm
sql.cpython-36.pyc	52283	0644	editdlrm
stata.cpython-36.pyc	97563	0644	editdlrm
__init__.cpython-36.pyc	145	0644	editdlrm

3 :%Eg��@s�dZd
dl
Z
d
dlmZmZ
d
dlZd
dlmZ
d
dlm Z
d
dlmZm Z
de
jfeeeeed�d d �Zdeeed�dd �ZdS)z pickle compat �N)�Any�Optional)
�FilePathOrBuffer)
� pickle_compat)�get_filepath_or_buffer� get_handle�infer)�obj�filepath_or_buffer�compression�protocolc Cs�t|
|d
d�\}}}}t
|t�r.|dkr.d}t|d
|dd�\}}|dkrPtj}z|jtj||d��

Wd|j�
x|D]} | j�
qxW|r�y|j�
Wnt k r�


YnXXdS) 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. .. [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") �wb)r�moderNF)r�is_textr
)
r) r� isinstance�strr�pickle�HIGHEST_PROTOCOL�write�dumps�close� ValueError) r r rr� fp_or_buf�
_�should_close�
f�fh�_f�r�`__. 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). 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") )
rrN�rbF)rrT)
�record�ignore)
�encodingzlatin-1)rrrr�AttributeError�ImportError�ModuleNotFoundError� TypeError�warnings�catch_warnings�simplefilter�Warningr�load�pc�UnicodeDecodeErrorrr) r rrrrrrZ excs_to_catchrrrr�read_picklecs.A














r0)
r)�__doc__r�typingrrr)Zpandas._typingrZ pandas.compatrr.Zpandas.io.commonrrrr�intr r0rrrr�
s




T