Mh[dSrSSKJr SSKJrJr SSKJr SSKJ r SSK J r SSK J r SSKJr SS KrSS KJr SS KJr SS KJr SS KJr \(aSSKJrJr SSKJrJrJ r J!r!J"r" \ "\SS9SSSjj5r#\ "\SS9S SS \ RH4SSjj5r%g )zfeather-format compat ) annotations) TYPE_CHECKINGAny)using_pyarrow_string_dtype)lib)import_optional_dependency)doc)check_dtype_backendN) DataFrame) _shared_docs)arrow_string_types_mapper) get_handle)HashableSequence) DtypeBackendFilePath ReadBufferStorageOptions WriteBufferstorage_options)rc [S5 SSKJn [U[5(d [ S5e[ USUSS9nUR"XR40UD6 SSS5 g!,(df  g=f) z Write a DataFrame to the binary Feather format. Parameters ---------- df : DataFrame path : str, path object, or file-like object {storage_options} **kwargs : Additional keywords passed to `pyarrow.feather.write_feather`. pyarrowrfeatherz'feather only support IO with DataFrameswbFris_textN) rrr isinstancer ValueErrorr write_featherhandle)dfpathrkwargsrhandless J/var/www/html/env/lib/python3.13/site-packages/pandas/io/feather_format.py to_featherr'&sc&y) b) $ $BCC  dOU  b..;F;   s A%% A3Tc[S5 SSKJn SSKn[ U5 [ USUSS9nU[ RLa<[5(d-URURU[U5S9sSSS5 $URURU[U5S9nUS :Xa-SS K Jn URU "5R S 9sSSS5 $US:Xa&UR["R$S 9sSSS5 $[5(a UR['5S 9sSSS5 $[(e!,(df  g=f) a Load a feather-format object from the file path. Parameters ---------- path : str, path object, or file-like object String, path object (implementing ``os.PathLike[str]``), or file-like object implementing a binary ``read()`` function. The string could be a URL. Valid URL schemes include http, ftp, s3, and file. For file URLs, a host is expected. A local file could be: ``file://localhost/path/to/table.feather``. columns : sequence, default None If not provided, all columns are read. use_threads : bool, default True Whether to parallelize reading using multiple threads. {storage_options} dtype_backend : {{'numpy_nullable', 'pyarrow'}}, default 'numpy_nullable' Back-end data type applied to the resultant :class:`DataFrame` (still experimental). Behaviour is as follows: * ``"numpy_nullable"``: returns nullable-dtype-backed :class:`DataFrame` (default). * ``"pyarrow"``: returns pyarrow-backed nullable :class:`ArrowDtype` DataFrame. .. versionadded:: 2.0 Returns ------- type of object stored in file Examples -------- >>> df = pd.read_feather("path/to/file.feather") # doctest: +SKIP rrrNrbFr)columns use_threadsnumpy_nullable)_arrow_dtype_mapping) types_mapper)rrr(pandas.core.arrays.arrow.extension_typesr rr no_defaultr read_featherr!bool read_tablepandas.io._utilr- to_pandasgetpd ArrowDtyper NotImplementedError) r#r*r+r dtype_backendrpandasr%pa_tabler-s r&r1r1Es3Vy)4 &  dOU   CNN *3M3O3O''T+=N(   %% NNGk9J&  , , <%%3G3I3M3M%N  "i '%%2==%A%  (( ) )%%3L3N%O+  .& %/  s%AD5=A D5"D5%D5/D55 E)N) r"r r#zFilePath | WriteBuffer[bytes]rStorageOptions | Noner$rreturnNone) r#zFilePath | ReadBuffer[bytes]r*zSequence[Hashable] | Noner+r2rr=r:zDtypeBackend | lib.NoDefaultr>r )&__doc__ __future__rtypingrrpandas._configr pandas._libsrpandas.compat._optionalrpandas.util._decoratorsr pandas.util._validatorsr r;r7pandas.core.apir pandas.core.shared_docsr r4r pandas.io.commonrcollections.abcrrpandas._typingrrrrrr'r0r1r&rOs" 6>'7%05' \"345.2<< '<+< <  <6<<\"345*.-125.. I& &I& &I&I&+ I& 0 I&  I&6I&rN