pandas.read_feather

pandas.read_feather(path, columns=None, use_threads=True, storage_options=None, dtype_backend=_NoDefault.no_default)

Load a feather-format object from the file path.

Parameters

pathstr, 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.

columnssequence, default None

If not provided, all columns are read.

use_threadsbool, default True

Whether to parallelize reading using multiple threads.

storage_optionsdict, 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.

New in version 1.2.0.

dtype_backend{“numpy_nullable”, “pyarrow”}, defaults to NumPy backed DataFrames

Which dtype_backend to use, e.g. whether a DataFrame should have NumPy arrays, nullable dtypes are used for all dtypes that have a nullable implementation when “numpy_nullable” is set, pyarrow is used for all dtypes if “pyarrow” is set.

The dtype_backends are still experimential.

New in version 2.0.

Returns

type of object stored in file