polars.read_ipc#

polars.read_ipc(file: str | BinaryIO | _io.BytesIO | pathlib.Path | bytes, columns: list[int] | list[str] | None = None, n_rows: int | None = None, use_pyarrow: bool = False, memory_map: bool = True, storage_options: dict[str, object] | None = None, row_count_name: str | None = None, row_count_offset: int = 0, rechunk: bool = True) DataFrame[source]#

Read into a DataFrame from Arrow IPC (Feather v2) file.

Parameters:
file

Path to a file or a file-like object. If fsspec is installed, it will be used to open remote files.

columns

Columns to select. Accepts a list of column indices (starting at zero) or a list of column names.

n_rows

Stop reading from IPC file after reading n_rows. Only valid when use_pyarrow=False.

use_pyarrow

Use pyarrow or the native rust reader.

memory_map

Try to memory map the file. This can greatly improve performance on repeated queries as the OS may cache pages. Only uncompressed IPC files can be memory mapped.

storage_options

Extra options that make sense for fsspec.open() or a particular storage connection, e.g. host, port, username, password, etc.

row_count_name

If not None, this will insert a row count column with give name into the DataFrame

row_count_offset

Offset to start the row_count column (only use if the name is set)

rechunk

Make sure that all data is contiguous.

Returns:
DataFrame