(self, as_pandas=False)
return rules
Get a list of sigma objects.

        Args:
            as_pandas: Boolean indicating that the results will be returned
                as a Pandas DataFrame instead of a list of dicts.

        Returns:
            List of Sigme rule object instances or a pandas Dataframe with all
            rules if as_pandas is True.

        Raises:
            ValueError: If no rules are found.
Get a list of sigma objects.
Get a list of sigma objects .
def list_sigma_rules(self, as_pandas=False):
        """Get a list of sigma objects.

        Args:
            as_pandas: Boolean indicating that the results will be returned
                as a Pandas DataFrame instead of a list of dicts.

        Returns:
            List of Sigme rule object instances or a pandas Dataframe with all
            rules if as_pandas is True.

        Raises:
            ValueError: If no rules are found.
        """
        rules = []
        response = self.fetch_resource_data('sigma/')

        if not response:
            raise ValueError('No rules found.')

        if as_pandas:
            return pandas.DataFrame.from_records(response.get('objects'))

        for rule_dict in response['objects']:
            if not rule_dict:
                raise ValueError('No rules found.')

            index_obj = sigma.Sigma(api=self)
            for key, value in rule_dict.items():
                index_obj.set_value(key, value)
            rules.append(index_obj)
        return rules
def list_sigma_rules ( self , as_pandas = False ) : rules = [ ] response = self . fetch_resource_data ( 'sigma/' ) if not response : raise ValueError ( 'No rules found.' ) if as_pandas : return pandas . DataFrame . from_records ( response . get ( 'objects' ) ) for rule_dict in response [ 'objects' ] : if not rule_dict : raise ValueError ( 'No rules found.' ) index_obj = sigma . Sigma ( api = self ) for key , value in rule_dict . items ( ) : index_obj . set_value ( key , value ) rules . append ( index_obj ) return rules