class_docstr: A representation of a column as a boolean mask.
  
  This augments the column with information that it is valid as a
  boolean mask for columns with a given number of rows
  
  Parameters
  ----------
  column
      The data to turn into a column to then verify
  nrows
      the number of rows to verify against
  
  Returns
  -------
  BooleanMask
      New object wrapping the column bearing witness to its
      suitability as a boolean mask for columns with matching
      row count.
  
  Raises
  ------
  TypeError
      If the column is of unsuitable dtype
  IndexError
      If the mask has the wrong number of rows
docstr: Construct a new BooleanMask from a column without checks.
  
  Parameters
  ----------
  column
     The column that will be used as a boolean mask
  
  Returns
  -------
  BooleanMask
  
  Notes
  -----
  This method asserts, by fiat, that the column is valid.
  Behaviour is undefined if it is not.
code: def from_column_unchecked(cls, column: "NumericalColumn") -> Self:
      """Construct a new BooleanMask from a column without checks.
  
      Parameters
      ----------
      column
         The column that will be used as a boolean mask
  
      Returns
      -------
      BooleanMask
  
      Notes
      -----
      This method asserts, by fiat, that the column is valid.
      Behaviour is undefined if it is not.
      """
      self = cls.__new__(cls)
      self.column = column
      return self
  
file_path: cudf/python/cudf/cudf/core/copy_types.py
imports: from dataclasses import dataclass
  from typing import TYPE_CHECKING, Any, cast
  from typing_extensions import Self
  import cudf
  import cudf._lib
  from cudf._lib.types import size_type_dtype
label_desc: Use image node_id 2 for calling the BooleanMask obj's underlying member method code with example usage: obj.from_column_unchecked(cls, column) and returns: self