class_docstr: Namespace for list related expressions.
class_docstr_tok: ["Namespace","for","list","related","expressions","."]
docstr: Run any polars expression against the lists' elements.
  
  Parameters
  ----------
  expr
      Expression to run. Note that you can select an element with `pl.first()`, or
      `pl.col()`
  parallel
      Run all expression parallel. Don't activate this blindly.
      Parallelism is worth it if there is enough work to do per thread.
  
      This likely should not be used in the group by context, because we already
      parallel execution per group
  
  Examples
  --------
  >>> df = pl.DataFrame({"a": [1, 8, 3], "b": [4, 5, 2]})
  >>> df.with_columns(
  ...     rank=pl.concat_list("a", "b").list.eval(pl.element().rank())
  ... )
  shape: (3, 3)
  ┌─────┬─────┬────────────┐
  │ a   ┆ b   ┆ rank       │
  │ --- ┆ --- ┆ ---        │
  │ i64 ┆ i64 ┆ list[f64]  │
  ╞═════╪═════╪════════════╡
  │ 1   ┆ 4   ┆ [1.0, 2.0] │
  │ 8   ┆ 5   ┆ [2.0, 1.0] │
  │ 3   ┆ 2   ┆ [2.0, 1.0] │
  └─────┴─────┴────────────┘
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code: def eval(self, expr: Expr, *, parallel: bool = False) -> Expr:
      """
      Run any polars expression against the lists' elements.
  
      Parameters
      ----------
      expr
          Expression to run. Note that you can select an element with `pl.first()`, or
          `pl.col()`
      parallel
          Run all expression parallel. Don't activate this blindly.
          Parallelism is worth it if there is enough work to do per thread.
  
          This likely should not be used in the group by context, because we already
          parallel execution per group
  
      Examples
      --------
      >>> df = pl.DataFrame({"a": [1, 8, 3], "b": [4, 5, 2]})
      >>> df.with_columns(
      ...     rank=pl.concat_list("a", "b").list.eval(pl.element().rank())
      ... )
      shape: (3, 3)
      ┌─────┬─────┬────────────┐
      │ a   ┆ b   ┆ rank       │
      │ --- ┆ --- ┆ ---        │
      │ i64 ┆ i64 ┆ list[f64]  │
      ╞═════╪═════╪════════════╡
      │ 1   ┆ 4   ┆ [1.0, 2.0] │
      │ 8   ┆ 5   ┆ [2.0, 1.0] │
      │ 3   ┆ 2   ┆ [2.0, 1.0] │
      └─────┴─────┴────────────┘
  
      """
      return wrap_expr(self._pyexpr.list_eval(expr._pyexpr, parallel))
  
imports: from __future__ import annotations
  import copy
  from typing import TYPE_CHECKING, Any, Callable, Sequence
  import polars._reexport
  from polars import functions
  from polars.utils._parse_expr_input import parse_as_expression
  from polars.utils._wrap import wrap_expr
  from polars.utils.deprecation import deprecate_renamed_function, deprecate_renamed_parameter
label_desc: Use image node_id 33 for calling the ExprListNameSpace obj's underlying member method code with example usage: obj.eval(expr) and returns: wrap_expr