def _get_check()

in sourcecode/scoring/pandas_utils.py [0:0]

• 27 lines of code
• 13 McCabe index (conditional complexity)

  def _get_check(self, lines: List[str], kwargs: Dict) -> Callable:
    """Return a function which will either assert a condition or append to a list of errors.

    Note that this function does not actually log to stderr, but rather appends to a list so
    that all
    """
    unsafeAllowed = set()
    if "unsafeAllowed" in kwargs:
      unsafeAllowedArg = kwargs["unsafeAllowed"]
      if isinstance(unsafeAllowedArg, str):
        unsafeAllowed = {unsafeAllowedArg}
      elif isinstance(unsafeAllowedArg, List):
        unsafeAllowed = set(unsafeAllowedArg)
      else:
        assert isinstance(unsafeAllowedArg, Set)
        unsafeAllowed = unsafeAllowedArg
      del kwargs["unsafeAllowed"]

    def _check(columns: Any, condition: bool, msg: str):
      if isinstance(columns, str):
        failDisabled = columns in unsafeAllowed
      elif isinstance(columns, List):
        failDisabled = all(col in unsafeAllowed for col in columns)
      else:
        # Note there are multiple circumstances where the type of Columns may not be a str
        # or List[str], including when we are concatenating a Series (column name will be
        # set to None), when there are mulit-level column names (column name will be a tuple)
        # or when Pandas has set column names to a RangeIndex.
        failDisabled = False
      if self._fail and not failDisabled:
        assert condition, msg
      elif not condition:
        if failDisabled:
          lines.append(f"{msg} (allowed)")
        else:
          lines.append(f"{msg} (UNALLOWED)")

    return _check