polars.LazyFrame.show_graph#
- LazyFrame.show_graph(*, optimized: bool = True, show: bool = True, output_path: str | None = None, raw_output: bool = False, figsize: tuple[float, float] = (16.0, 12.0), type_coercion: bool = True, predicate_pushdown: bool = True, projection_pushdown: bool = True, simplify_expression: bool = True, slice_pushdown: bool = True, common_subplan_elimination: bool = True, streaming: bool = False) str | None [source]#
Show a plot of the query plan. Note that you should have graphviz installed.
- Parameters:
- optimized
Optimize the query plan.
- show
Show the figure.
- output_path
Write the figure to disk.
- raw_output
Return dot syntax. This cannot be combined with show and/or output_path.
- figsize
Passed to matplotlib if show == True.
- type_coercion
Do type coercion optimization.
- predicate_pushdown
Do predicate pushdown optimization.
- projection_pushdown
Do projection pushdown optimization.
- simplify_expression
Run simplify expressions optimization.
- 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)
Examples
>>> lf = pl.LazyFrame( ... { ... "a": ["a", "b", "a", "b", "b", "c"], ... "b": [1, 2, 3, 4, 5, 6], ... "c": [6, 5, 4, 3, 2, 1], ... } ... ) >>> lf.groupby("a", maintain_order=True).agg(pl.all().sum()).sort( ... "a" ... ).show_graph()