code: def all(*names: str, ignore_nulls: bool = True) -> Expr:
      """
      Either return an expression representing all columns, or evaluate a bitwise AND operation.
  
      If no arguments are passed, this function is syntactic sugar for `col("*")`.
      Otherwise, this function is syntactic sugar for `col(names).all()`.
  
      Parameters
      ----------
      *names
          Name(s) of the columns to use in the aggregation.
      ignore_nulls
          Ignore null values (default).
  
          If set to `False`, `Kleene logic`_ is used to deal with nulls:
          if the column contains any null values and no `True` values,
          the output is `None`.
  
          .. _Kleene logic: https://en.wikipedia.org/wiki/Three-valued_logic
  
      See Also
      --------
      all_horizontal
  
      Examples
      --------
      Selecting all columns.
  
      >>> df = pl.DataFrame(
      ...     {
      ...         "a": [True, False, True],
      ...         "b": [False, False, False],
      ...     }
      ... )
      >>> df.select(pl.all().sum())
      shape: (1, 2)
      ┌─────┬─────┐
      │ a   ┆ b   │
      │ --- ┆ --- │
      │ u32 ┆ u32 │
      ╞═════╪═════╡
      │ 2   ┆ 0   │
      └─────┴─────┘
  
      Evaluate bitwise AND for a column.
  
      >>> df.select(pl.all("a"))
      shape: (1, 1)
      ┌───────┐
      │ a     │
      │ ---   │
      │ bool  │
      ╞═══════╡
      │ false │
      └───────┘
  
      """  # noqa: W505
      if not names:
          return F.col("*")
  
      return F.col(*names).all(ignore_nulls=ignore_nulls)
  
file_path: polars/py-polars/polars/functions/aggregation/vertical.py
imports: from __future__ import annotations
  from typing import TYPE_CHECKING
  import polars.functions
  from polars.utils.deprecation import deprecate_renamed_function
label_desc: Use image node_id 1 for calling a global function with example usage: all() and returns: F, F