PidZddlmZddlmZmZddlZddlmZddl m Z ddl m Z ddl mZdd lmZdd lmZdd lmZdd lmZdd lmZerddlmZmZddlmZmZmZm Z m!Z! d%d&dZ"edddde j#fd'd$Z$dS)(zfeather-format compat) annotations) TYPE_CHECKINGAnyN)using_string_dtype)lib)import_optional_dependency)Pandas4Warning) set_module)check_dtype_backend) DataFrame)arrow_table_to_pandas) get_handle)HashableSequence) DtypeBackendFilePath ReadBufferStorageOptions WriteBufferdfr pathFilePath | WriteBuffer[bytes]storage_optionsStorageOptions | NonekwargsrreturnNonec tdddlm}t|tst dt |d|d5}|j||jfi|ddddS#1swxYwYdS) at Write a DataFrame to the binary Feather format. Parameters ---------- df : DataFrame path : str, path object, or file-like object storage_options : dict, optional Extra options that make sense for a particular storage connection, e.g. host, port, username, password, etc. For HTTP(S) URLs the key-value pairs are forwarded to ``urllib.request.Request`` as header options. For other URLs (e.g. starting with "s3://", and "gcs://") the key-value pairs are forwarded to ``fsspec.open``. Please see ``fsspec`` and ``urllib`` for more details, and for more examples on storage options refer `here `_. **kwargs : Additional keywords passed to `pyarrow.feather.write_feather`. pyarrowrfeatherz'feather only support IO with DataFrameswbFris_textN) rrr! isinstancer ValueErrorr write_featherhandle)rrrrr!handless l/home/jaya/work/projects/VOICE-AGENT/VIET/agent-env/lib/python3.11/site-packages/pandas/io/feather_format.py to_featherr+'s4y))) b) $ $DBCCC  dOU   < b'.;;F;;;<<<<<<<<<<<<<<<<<`_. dtype_backend : {{'numpy_nullable', 'pyarrow'}} Back-end data type applied to the resultant :class:`DataFrame` (still experimental). If not specified, the default behavior is to not use nullable data types. If specified, the behavior is as follows: * ``"numpy_nullable"``: returns nullable-dtype-backed :class:`DataFrame`. * ``"pyarrow"``: returns pyarrow-backed nullable :class:`ArrowDtype` :class:`DataFrame` .. versionadded:: 2.0 Returns ------- type of object stored in file DataFrame object stored in the file. See Also -------- read_csv : Read a comma-separated values (csv) file into a pandas DataFrame. read_excel : Read an Excel file into a pandas DataFrame. read_spss : Read an SPSS file into a pandas DataFrame. read_orc : Load an ORC object into a pandas DataFrame. read_sas : Read SAS file into a pandas DataFrame. Examples -------- >>> df = pd.read_feather("path/to/file.feather") # doctest: +SKIP rrr NrbFr#ignorezmake_block is deprecated)r.r0)r2)rrr!(pandas.core.arrays.arrow.extension_typesr rr no_defaultrwarningscatch_warningsfilterwarningsr read_featherr(r1 read_tabler ) rr.r0rr2r!r,r)pa_tables r*r<r<Ms Jy)))4333 &&&  dOU   L  CN * *3E3G3G *(**  '." ++NGkARAR,        LLLLLLLL        %% NGk9J9J&  %X]KKK%LLLLLLLLLLLLLLLLLLs60D,AC 1 D C DC =DD #D )N) rr rrrrrrrr) rr-r.r/r0r1rrr2r3rr )%__doc__ __future__rtypingrrr9pandas._configr pandas._libsrpandas.compat._optionalr pandas.errorsr pandas.util._decoratorsr pandas.util._validatorsr pandas.core.apir pandas.io._utilr pandas.io.commonrcollections.abcrrpandas._typingrrrrrr+r8r<r*rOs""""""------>>>>>>((((((......777777%%%%%%111111''''''  .2#<#<#<#<#