polars.LazyFrame.fetch

LazyFrame.fetch(

n_rows: int = 500,

*,

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,

) → DataFrame

Collect a small number of rows for debugging purposes.

Parameters:

n_rows

Collect n_rows from the data sources.

type_coercion

Run type coercion optimization.

predicate_pushdown

Run predicate pushdown optimization.

projection_pushdown

Run projection pushdown optimization.

simplify_expression

Run simplify expressions optimization.

no_optimization

Turn off 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

Run parts of the query in a streaming fashion (this is in an alpha state)

Returns:

DataFrame

Warning

This is strictly a utility function that can help to debug queries using a smaller number of rows, and should not be used in production code.

Notes

This is similar to a collect() operation, but it overwrites the number of rows read by every scan operation. Be aware that fetch does not guarantee the final number of rows in the DataFrame. Filters, join operations and fewer rows being available in the scanned data will all influence the final number of rows (joins are especially susceptible to this, and may return no data at all if n_rows is too small as the join keys may not be present).

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.group_by("a", maintain_order=True).agg(pl.all().sum()).fetch(2)
shape: (2, 3)
┌─────┬─────┬─────┐
│ a   ┆ b   ┆ c   │
│ --- ┆ --- ┆ --- │
│ str ┆ i64 ┆ i64 │
╞═════╪═════╪═════╡
│ a   ┆ 1   ┆ 6   │
│ b   ┆ 2   ┆ 5   │
└─────┴─────┴─────┘