polars.collect_all#
- polars.collect_all(lazy_frames: Sequence[LazyFrame], type_coercion: bool = True, predicate_pushdown: bool = True, projection_pushdown: bool = True, simplify_expression: bool = True, no_optimization: bool = False, slice_pushdown: bool = True, common_subplan_elimination: bool = True, streaming: bool = False) list[DataFrame][source]#
Collect multiple LazyFrames at the same time.
This runs all the computation graphs in parallel on Polars threadpool.
- Parameters:
- lazy_frames
A list of LazyFrames to collect.
- 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 optimizations.
- slice_pushdown
Slice pushdown optimization.
- common_subplan_elimination
Will try to cache branching subplans that occur on self-joins or unions.
- streaming
Run parts of the query in a streaming fashion (this is in an alpha state)
- Returns:
- List[DataFrame]