class_docstr: Check if there are columns which have only a single unique value in all rows.
  
  Parameters
  ----------
  columns : Union[Hashable, List[Hashable]] , default: None
      Columns to check, if none are given checks all
      columns except ignored ones.
  ignore_columns : Union[Hashable, List[Hashable]] , default: None
      Columns to ignore, if none given checks based
      on columns variable.
  ignore_nan : bool, default True
      Whether to ignore NaN values in a column when counting the number of unique values.
  n_samples : int , default: 10_000_000
      number of samples to use for this check.
  random_state : int, default: 42
      random seed for all check internals.
code: def __init__(
      self,
      columns: Union[Hashable, List[Hashable], None] = None,
      ignore_columns: Union[Hashable, List[Hashable], None] = None,
      ignore_nan: bool = True,
      n_samples: int = 10_000_000,
      random_state: int = 42,
      **kwargs,
  ):
      super().__init__(**kwargs)
      self.columns = columns
      self.ignore_columns = ignore_columns
      self.ignore_nan = ignore_nan
      self.n_samples = n_samples
      self.random_state = random_state
  
file_path: deepchecks/deepchecks/tabular/checks/data_integrity/is_single_value.py
imports: from typing import List, Union
  import pandas
  from deepchecks.core import CheckResult, ConditionCategory, ConditionResult
  from deepchecks.tabular import Context, SingleDatasetCheck
  from deepchecks.tabular.utils.messages import get_condition_passed_message
  from deepchecks.utils.dataframes import select_from_dataframe
  from deepchecks.utils.typing import Hashable
label_desc: Use image node_id 1 to create a new IsSingleValue object from inherited base classes: SingleDatasetCheck with example: obj = IsSingleValue(columns, ignore_columns, ignore_nan, n_samples, random_state)