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]