polars.read_ipc#
- polars.read_ipc(
- source: str | Path | IO[bytes] | 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, Any] | None = None,
- row_index_name: str | None = None,
- row_index_offset: int = 0,
- rechunk: bool = True,
Read into a DataFrame from Arrow IPC (Feather v2) file.
See “File or Random Access format” on https://arrow.apache.org/docs/python/ipc.html. Arrow IPC files are also known as Feather (v2) files.
- Parameters:
- source
Path to a file or a file-like object (by “file-like object” we refer to objects that have a
read()method, such as a file handler like the builtinopenfunction, or aBytesIOinstance). Iffsspecis 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 whenuse_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_index_name
Insert a row index column with the given name into the DataFrame as the first column. If set to
None(default), no row index column is created.- row_index_offset
Start the row index at this offset. Cannot be negative. Only used if
row_index_nameis set.- rechunk
Make sure that all data is contiguous.
- Returns:
- DataFrame
Warning
If
memory_mapis set, the bytes on disk are mapped 1:1 to memory. That means that you cannot write to the same filename. E.g.pl.read_ipc("my_file.arrow").write_ipc("my_file.arrow")will fail.