o _~#g[@sdZddlmZddlmZmZddlmZddlm Z ddl m Z ddl m Z ddlmZdd lZdd lmZdd lmZdd lmZdd lmZerbddlmZmZddlmZmZm Z m!Z!m"Z"e edd d'd(ddZ#e eddd dd e j$fd)d%d&Z%d S)*z feather-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)rdfr pathFilePath | WriteBuffer[bytes]StorageOptions | NonekwargsrreturnNonecKsrtdddlm}t|tstdt|d|dd}|j||jfi|WddS1s2wYdS) a  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)rrrrrhandlesr(}/var/www/static.ux5.de/https/Moving-Object-Detection-with-OpenCV/env/lib/python3.10/site-packages/pandas/io/feather_format.py to_feather&s  "r*TFilePath | ReadBuffer[bytes]columnsSequence[Hashable] | None use_threadsbool dtype_backendDtypeBackend | lib.NoDefaultc Cstdddlm}ddl}t|t|d|ddd}|tjur5ts5|j |j |t |dWdS|j |j |t |d}|d krYdd l m} |j| jd WdS|dkrk|jtjd WdStr||jtd WdSt1swYdS) 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!)r,r.numpy_nullable)_arrow_dtype_mapping) types_mapper)rrr(pandas.core.arrays.arrow.extension_typesr r r no_defaultr read_featherr&r/ read_tablepandas.io._utilr4 to_pandasgetpd ArrowDtyper NotImplementedError) rr,r.rr0rpandasr'pa_tabler4r(r(r)r8Es8+      r8)N) rr rrrrrrrr) rr+r,r-r.r/rrr0r1rr )&__doc__ __future__rtypingrrpandas._configr pandas._libsrpandas.compat._optionalrpandas.util._decoratorsrpandas.util._validatorsr r@r=pandas.core.apir pandas.core.shared_docsr r:r pandas.io.commonr collections.abcrrpandas._typingrrrrrr*r7r8r(r(r(r)s2