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131 lines
3.9 KiB
Python
131 lines
3.9 KiB
Python
""" feather-format compat """
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from __future__ import annotations
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from typing import (
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TYPE_CHECKING,
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Any,
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)
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from pandas._config import using_string_dtype
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from pandas._libs import lib
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from pandas.compat._optional import import_optional_dependency
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from pandas.util._decorators import doc
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from pandas.util._validators import check_dtype_backend
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from pandas.core.api import DataFrame
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from pandas.core.shared_docs import _shared_docs
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from pandas.io._util import arrow_table_to_pandas
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from pandas.io.common import get_handle
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if TYPE_CHECKING:
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from collections.abc import (
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Hashable,
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Sequence,
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)
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from pandas._typing import (
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DtypeBackend,
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FilePath,
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ReadBuffer,
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StorageOptions,
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WriteBuffer,
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)
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@doc(storage_options=_shared_docs["storage_options"])
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def to_feather(
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df: DataFrame,
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path: FilePath | WriteBuffer[bytes],
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storage_options: StorageOptions | None = None,
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**kwargs: Any,
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) -> None:
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"""
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Write a DataFrame to the binary Feather format.
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Parameters
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----------
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df : DataFrame
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path : str, path object, or file-like object
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{storage_options}
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**kwargs :
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Additional keywords passed to `pyarrow.feather.write_feather`.
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"""
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import_optional_dependency("pyarrow")
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from pyarrow import feather
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if not isinstance(df, DataFrame):
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raise ValueError("feather only support IO with DataFrames")
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with get_handle(
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path, "wb", storage_options=storage_options, is_text=False
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) as handles:
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feather.write_feather(df, handles.handle, **kwargs)
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@doc(storage_options=_shared_docs["storage_options"])
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def read_feather(
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path: FilePath | ReadBuffer[bytes],
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columns: Sequence[Hashable] | None = None,
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use_threads: bool = True,
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storage_options: StorageOptions | None = None,
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dtype_backend: DtypeBackend | lib.NoDefault = lib.no_default,
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) -> DataFrame:
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"""
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Load a feather-format object from the file path.
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Parameters
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----------
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path : str, path object, or file-like object
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String, path object (implementing ``os.PathLike[str]``), or file-like
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object implementing a binary ``read()`` function. The string could be a URL.
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Valid URL schemes include http, ftp, s3, and file. For file URLs, a host is
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expected. A local file could be: ``file://localhost/path/to/table.feather``.
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columns : sequence, default None
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If not provided, all columns are read.
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use_threads : bool, default True
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Whether to parallelize reading using multiple threads.
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{storage_options}
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dtype_backend : {{'numpy_nullable', 'pyarrow'}}, default 'numpy_nullable'
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Back-end data type applied to the resultant :class:`DataFrame`
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(still experimental). Behaviour is as follows:
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* ``"numpy_nullable"``: returns nullable-dtype-backed :class:`DataFrame`
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(default).
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* ``"pyarrow"``: returns pyarrow-backed nullable :class:`ArrowDtype`
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DataFrame.
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.. versionadded:: 2.0
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Returns
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-------
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type of object stored in file
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Examples
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--------
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>>> df = pd.read_feather("path/to/file.feather") # doctest: +SKIP
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"""
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import_optional_dependency("pyarrow")
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from pyarrow import feather
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# import utils to register the pyarrow extension types
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import pandas.core.arrays.arrow.extension_types # pyright: ignore[reportUnusedImport] # noqa: F401
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check_dtype_backend(dtype_backend)
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with get_handle(
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path, "rb", storage_options=storage_options, is_text=False
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) as handles:
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if dtype_backend is lib.no_default and not using_string_dtype():
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return feather.read_feather(
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handles.handle, columns=columns, use_threads=bool(use_threads)
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)
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pa_table = feather.read_table(
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handles.handle, columns=columns, use_threads=bool(use_threads)
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)
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return arrow_table_to_pandas(pa_table, dtype_backend=dtype_backend)
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