How to use the snps.utils.clean_str function in snps

if self._snps.empty:
            self._source.extend(source)
            self._snps = snps
        else:
            common_snps = self._snps.join(snps, how="inner", rsuffix="_added")

            discrepant_positions = common_snps.loc[
                (common_snps["chrom"] != common_snps["chrom_added"])
                | (common_snps["pos"] != common_snps["pos_added"])
            ]

            if not self._name:
                prefix = ""
            else:
                prefix = "{}_".format(clean_str(self._name))

            if 0 < len(discrepant_positions) < discrepant_snp_positions_threshold:
                logger.warning(
                    "{} SNP positions were discrepant; keeping original positions".format(
                        str(len(discrepant_positions))
                    )
                )

                if save_output:
                    self._discrepant_positions_file_count += 1
                    save_df_as_csv(
                        discrepant_positions,
                        self._output_dir,
                        "{}discrepant_positions_{}{}".format(
                            prefix, str(self._discrepant_positions_file_count), ".csv"
                        ),

def _save_discrepant_snps_file(self, df, discrepant_snps_type, filename):
        if not filename:
            if not self._name:
                filename = "{}.csv".format(discrepant_snps_type)
            else:
                filename = "{}_{}.csv".format(
                    clean_str(self._name), discrepant_snps_type
                )

        return save_df_as_csv(
            df,
            self._output_dir,
            filename,
            comment="# Source(s): {}\n".format(self.source),
        )

if self._snps.empty:
            self._source.extend(source)
            self._snps = snps
        else:
            common_snps = self._snps.join(snps, how="inner", rsuffix="_added")

            discrepant_positions = common_snps.loc[
                (common_snps["chrom"] != common_snps["chrom_added"])
                | (common_snps["pos"] != common_snps["pos_added"])
            ]

            if not self._name:
                prefix = ""
            else:
                prefix = "{}_".format(clean_str(self._name))

            if 0 < len(discrepant_positions) < discrepant_snp_positions_threshold:
                print(
                    "{} SNP positions were discrepant; keeping original positions".format(
                        str(len(discrepant_positions))
                    )
                )

                if save_output:
                    self._discrepant_positions_file_count += 1
                    save_df_as_csv(
                        discrepant_positions,
                        self._output_dir,
                        "{}discrepant_positions_{}{}".format(
                            prefix, str(self._discrepant_positions_file_count), ".csv"
                        ),

if self._snps.empty:
            self._source.extend(source)
            self._snps = snps
        else:
            common_snps = self._snps.join(snps, how="inner", rsuffix="_added")

            discrepant_positions = common_snps.loc[
                (common_snps["chrom"] != common_snps["chrom_added"])
                | (common_snps["pos"] != common_snps["pos_added"])
            ]

            if not self._name:
                prefix = ""
            else:
                prefix = "{}_".format(clean_str(self._name))

            if 0 < len(discrepant_positions) < discrepant_snp_positions_threshold:
                logger.warning(
                    "{} SNP positions were discrepant; keeping original positions".format(
                        str(len(discrepant_positions))
                    )
                )

                if save_output:
                    self._discrepant_positions_file_count += 1
                    save_df_as_csv(
                        discrepant_positions,
                        self._output_dir,
                        "{}discrepant_positions_{}{}".format(
                            prefix, str(self._discrepant_positions_file_count), ".csv"
                        ),

def _save_discrepant_snps_file(self, df, discrepant_snps_type, filename):
        if not filename:
            if not self._name:
                filename = "{}.csv".format(discrepant_snps_type)
            else:
                filename = "{}_{}.csv".format(
                    clean_str(self._name), discrepant_snps_type
                )

        return save_df_as_csv(
            df,
            self._output_dir,
            filename,
            comment="# Source(s): {}\n".format(self.source),
        )

def _save_discrepant_snps_file(self, df, discrepant_snps_type, filename):
        if not filename:
            if not self._name:
                filename = "{}.csv".format(discrepant_snps_type)
            else:
                filename = "{}_{}.csv".format(
                    clean_str(self._name), discrepant_snps_type
                )

        return save_df_as_csv(
            df,
            self._output_dir,
            filename,
            comment="# Source(s): {}\n".format(self.source),
        )

vcf : bool
            flag to save file as VCF
        atomic : bool
            atomically write output to a file on local filesystem
        **kwargs
            additional parameters to `pandas.DataFrame.to_csv`

        Returns
        -------
        str
            path to file in output directory if SNPs were saved, else empty str
        """
        if not self._name:
            prefix = ""
        else:
            prefix = "{}_".format(clean_str(self._name))

        if not filename:
            if vcf:
                ext = ".vcf"
            else:
                ext = ".csv"

            filename = "{}{}{}".format(prefix, self.assembly, ext)
        return super().save_snps(filename=filename, vcf=vcf, atomic=atomic, **kwargs)