How to use the datacompy.sparkcompare.MatchType.MATCH function in datacompy

format_pattern = (" " * padding).join(
            [
                ("{:" + (">" if h[3] else "") + str(h[2]) + "}")
                for h in headers_columns_unequal_valid
            ]
        )
        print(format_pattern.format(*[h[0] for h in headers_columns_unequal_valid]), file=myfile)
        print(
            format_pattern.format(*["-" * len(h[0]) for h in headers_columns_unequal_valid]),
            file=myfile,
        )

        for column_name, column_values in sorted(
            self.columns_match_dict.items(), key=lambda i: i[0]
        ):
            num_matches = column_values[MatchType.MATCH.value]
            num_known_diffs = (
                None
                if self._known_differences is None
                else column_values[MatchType.KNOWN_DIFFERENCE.value]
            )
            num_mismatches = column_values[MatchType.MISMATCH.value]
            compare_column = self._base_to_compare_name(column_name)

            if num_mismatches or num_known_diffs or self.show_all_columns:
                output_row = [
                    column_name,
                    compare_column,
                    base_types.get(column_name),
                    compare_types.get(column_name),
                    str(num_matches),
                    str(num_mismatches),