polars.LazyFrame.sink_ipc#

LazyFrame.sink_ipc(
path: str | Path,
*,
compression: str | None = 'zstd',
maintain_order: bool = True,
type_coercion: bool = True,
predicate_pushdown: bool = True,
projection_pushdown: bool = True,
simplify_expression: bool = True,
no_optimization: bool = False,
slice_pushdown: bool = True,
) DataFrame[source]#

Persists a LazyFrame at the provided path.

This allows streaming results that are larger than RAM to be written to disk.

Parameters:
path

File path to which the file should be written.

compression{‘lz4’, ‘zstd’}

Choose “zstd” for good compression performance. Choose “lz4” for fast compression/decompression.

maintain_order

Maintain the order in which data is processed. Setting this to False will be slightly faster.

type_coercion

Do type coercion optimization.

predicate_pushdown

Do predicate pushdown optimization.

projection_pushdown

Do projection pushdown optimization.

simplify_expression

Run simplify expressions optimization.

no_optimization

Turn off (certain) optimizations.

slice_pushdown

Slice pushdown optimization.

Returns:
DataFrame

Examples

>>> lf = pl.scan_csv("/path/to/my_larger_than_ram_file.csv")  
>>> lf.sink_ipc("out.arrow")