polars.collect_all

polars.collect_all(lazy_frames: List[polars.internals.lazy_frame.LazyFrame], type_coercion: bool = True, predicate_pushdown: bool = True, projection_pushdown: bool = True, simplify_expression: bool = True, string_cache: bool = False, no_optimization: bool = False, slice_pushdown: bool = False) List[polars.internals.frame.DataFrame]

Collect multiple LazyFrames at the same time. This runs all the computation graphs in parallel on Polars threadpool.

Parameters
type_coercion

Do type coercion optimization.

predicate_pushdown

Do predicate pushdown optimization.

projection_pushdown

Do projection pushdown optimization.

simplify_expression

Run simplify expressions optimization.

string_cache

Use a global string cache in this query. This is needed if you want to join on categorical columns.

Caution!

If you already have set a global string cache, set this to False as this will reset the global cache when the query is finished.

no_optimization

Turn off optimizations.

slice_pushdown

Slice pushdown optimization.

Returns
List[DataFrame]