polars.LazyFrame.collect_async#

LazyFrame.collect_async( *, gevent: bool = False, type_coercion: bool = True, predicate_pushdown: bool = True, projection_pushdown: bool = True, simplify_expression: bool = True, no_optimization: bool = False, slice_pushdown: bool = True, comm_subplan_elim: bool = True, comm_subexpr_elim: bool = True, streaming: bool = False, ) → Awaitable[DataFrame] | _GeventDataFrameResult[DataFrame][source]#

Collect DataFrame asynchronously in thread pool.

Warning

This functionality is considered unstable. It may be changed at any point without it being considered a breaking change.

Collects into a DataFrame (like collect()) but, instead of returning a DataFrame directly, it is scheduled to be collected inside a thread pool, while this method returns almost instantly.

This can be useful if you use gevent or asyncio and want to release control to other greenlets/tasks while LazyFrames are being collected.

Parameters:

gevent: Return wrapper to gevent.event.AsyncResult instead of Awaitable
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.
comm_subplan_elim: Will try to cache branching subplans that occur on self-joins or unions.
comm_subexpr_elim: Common subexpressions will be cached and reused.
streaming: Process the query in batches to handle larger-than-memory data. If set to False (default), the entire query is processed in a single batch.

Warning

Streaming mode is considered unstable. It may be changed at any point without it being considered a breaking change.

Note

Use explain() to see if Polars can process the query in streaming mode.

Returns:

If gevent=False (default) then returns an awaitable.
If gevent=True then returns wrapper that has a
.get(block=True, timeout=None) method.

See also

polars.collect_all: Collect multiple LazyFrames at the same time.
polars.collect_all_async: Collect multiple LazyFrames at the same time lazily.

Notes

In case of error set_exception is used on asyncio.Future/gevent.event.AsyncResult and will be reraised by them.

Examples

>>> import asyncio
>>> lf = pl.LazyFrame(
...     {
...         "a": ["a", "b", "a", "b", "b", "c"],
...         "b": [1, 2, 3, 4, 5, 6],
...         "c": [6, 5, 4, 3, 2, 1],
...     }
... )
>>> async def main():
...     return await (
...         lf.group_by("a", maintain_order=True)
...         .agg(pl.all().sum())
...         .collect_async()
...     )
>>> asyncio.run(main())
shape: (3, 3)
┌─────┬─────┬─────┐
│ a   ┆ b   ┆ c   │
│ --- ┆ --- ┆ --- │
│ str ┆ i64 ┆ i64 │
╞═════╪═════╪═════╡
│ a   ┆ 4   ┆ 10  │
│ b   ┆ 11  ┆ 10  │
│ c   ┆ 6   ┆ 1   │
└─────┴─────┴─────┘