Fixed stylistic problems suggested by Bharath

class OneHotFeaturizer(MolecularFeaturizer):

  """Encodes SMILES or any arbitrary string as a one-hot array.

  This featurizer encodes a string or any arbitrary string as a one-hot array.

  This featurizer encodes either a SMILES string or any arbitrary string as a one-hot array.

  Note

  ----

  This class requires RDKit to be installed to work with RDKit molecules.

  This class needs RDKit to be installed in order to work with RDKit molecules.

  """

  def __init__(self, charset: List[str] = ZINC_CHARSET, max_length: int = 100):

    Parameters

    ----------

    datapoints: A list of either strings or RDKit molecules.

    datapoints: list

      A list of either strings or RDKit molecules.

    log_every_n: int, optional (default 1000)

      How many elements are featurized every time a featurization is logged.

    """

    datapoints = list(datapoints)

    if (len(datapoints) < 1):

      print(

          "No datapoints are present in the parameter Iterable, so we return an empty array."

      )

      return np.array([])

    # Featurize str data

    if (type(datapoints[0]) == str):

      # Calls featurize() in grandparent class, which takes Iterable[Any].

    # Featurize data using featurize() in grandparent class

    return Featurizer.featurize(self, datapoints, log_every_n)

    # Featurize mol data

    else:

      # Calls featurize() in parent class, which takes molecules.

      return MolecularFeaturizer.featurize(self, datapoints, log_every_n)

  def _featurize(self, datapoint: Any):

    # Featurize str data

    if (type(datapoint) == str):

      return self._featurizeString(datapoint)

      return self._featurize_string(datapoint)

    # Featurize mol data

    else:

      return self._featurizeMol(datapoint)

      return self._featurize_mol(datapoint)

  def _featurizeString(self, string: str) -> np.ndarray:

  def _featurize_string(self, string: str) -> np.ndarray:

    """Compute one-hot featurization of string.

    Parameters

    ----------

    str: An arbitrary string to be featurized.

    string: str

      An arbitrary string to be featurized.

    Returns

    -------

        for val in string

    ])

  def _featurizeMol(self, mol: RDKitMol) -> np.ndarray:

  def _featurize_mol(self, mol: RDKitMol) -> np.ndarray:

    """Compute one-hot featurization of this molecule.

    Parameters

    except ModuleNotFoundError:

      raise ImportError("This class requires RDKit to be installed.")

    smiles = Chem.MolToSmiles(mol)  # Convert mol to SMILES string.

    return self._featurizeString(smiles)  # Use string featurization.

    return self._featurize_string(smiles)  # Use string featurization.

  def pad_smile(self, smiles: str) -> str:

    """Pad smile string to `self.pad_length`