144 lines
4.3 KiB
Python
144 lines
4.3 KiB
Python
""" feather-format compat """
|
|
from __future__ import annotations
|
|
|
|
from typing import (
|
|
TYPE_CHECKING,
|
|
Any,
|
|
)
|
|
|
|
from pandas._config import using_pyarrow_string_dtype
|
|
|
|
from pandas._libs import lib
|
|
from pandas.compat._optional import import_optional_dependency
|
|
from pandas.util._decorators import doc
|
|
from pandas.util._validators import check_dtype_backend
|
|
|
|
import pandas as pd
|
|
from pandas.core.api import DataFrame
|
|
from pandas.core.shared_docs import _shared_docs
|
|
|
|
from pandas.io._util import arrow_string_types_mapper
|
|
from pandas.io.common import get_handle
|
|
|
|
if TYPE_CHECKING:
|
|
from collections.abc import (
|
|
Hashable,
|
|
Sequence,
|
|
)
|
|
|
|
from pandas._typing import (
|
|
DtypeBackend,
|
|
FilePath,
|
|
ReadBuffer,
|
|
StorageOptions,
|
|
WriteBuffer,
|
|
)
|
|
|
|
|
|
@doc(storage_options=_shared_docs["storage_options"])
|
|
def to_feather(
|
|
df: DataFrame,
|
|
path: FilePath | WriteBuffer[bytes],
|
|
storage_options: StorageOptions | None = None,
|
|
**kwargs: Any,
|
|
) -> None:
|
|
"""
|
|
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`.
|
|
|
|
"""
|
|
import_optional_dependency("pyarrow")
|
|
from pyarrow import feather
|
|
|
|
if not isinstance(df, DataFrame):
|
|
raise ValueError("feather only support IO with DataFrames")
|
|
|
|
with get_handle(
|
|
path, "wb", storage_options=storage_options, is_text=False
|
|
) as handles:
|
|
feather.write_feather(df, handles.handle, **kwargs)
|
|
|
|
|
|
@doc(storage_options=_shared_docs["storage_options"])
|
|
def read_feather(
|
|
path: FilePath | ReadBuffer[bytes],
|
|
columns: Sequence[Hashable] | None = None,
|
|
use_threads: bool = True,
|
|
storage_options: StorageOptions | None = None,
|
|
dtype_backend: DtypeBackend | lib.NoDefault = lib.no_default,
|
|
) -> DataFrame:
|
|
"""
|
|
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
|
|
"""
|
|
import_optional_dependency("pyarrow")
|
|
from pyarrow import feather
|
|
|
|
# import utils to register the pyarrow extension types
|
|
import pandas.core.arrays.arrow.extension_types # pyright: ignore[reportUnusedImport] # noqa: F401
|
|
|
|
check_dtype_backend(dtype_backend)
|
|
|
|
with get_handle(
|
|
path, "rb", storage_options=storage_options, is_text=False
|
|
) as handles:
|
|
if dtype_backend is lib.no_default and not using_pyarrow_string_dtype():
|
|
return feather.read_feather(
|
|
handles.handle, columns=columns, use_threads=bool(use_threads)
|
|
)
|
|
|
|
pa_table = feather.read_table(
|
|
handles.handle, columns=columns, use_threads=bool(use_threads)
|
|
)
|
|
|
|
if dtype_backend == "numpy_nullable":
|
|
from pandas.io._util import _arrow_dtype_mapping
|
|
|
|
return pa_table.to_pandas(types_mapper=_arrow_dtype_mapping().get)
|
|
|
|
elif dtype_backend == "pyarrow":
|
|
return pa_table.to_pandas(types_mapper=pd.ArrowDtype)
|
|
|
|
elif using_pyarrow_string_dtype():
|
|
return pa_table.to_pandas(types_mapper=arrow_string_types_mapper())
|
|
else:
|
|
raise NotImplementedError
|