def METHOD_NAME(self, f):
    """Go through log file looking for conpair concordance or contamination output
    One parser to rule them all."""
    conpair_regexes = {
        "concordance_concordance": [r"Concordance: ([\d\.]+)%\nBased.*", r"(\d\.\d+)\nBased.*"],
        "concordance_used_markers": [r"Based on (\d+)/\d+ markers"],
        "concordance_total_markers": [r"Based on \d+/(\d+) markers"],
        "concordance_marker_threshold": [r"\(coverage per marker threshold : (\d+) reads\)"],
        "concordance_min_mapping_quality": [r"Minimum mappinq quality: (\d+)"],
        "concordance_min_base_quality": [r"Minimum base quality: (\d+)"],
        "contamination_normal": [r"Normal sample contamination level: ([\d\.]+)%"],
        "contamination_tumor": [r"Tumor sample contamination level: ([\d\.]+)%"],
    }
    parsed_data = {}
    for k, r_arr in conpair_regexes.items():
        for r in r_arr:
            match = re.search(r, f["f"])
            if match:
                parsed_data[k] = float(match.group(1))
                if k == "concordance_concordance" and not "Concordance" in r:
                    parsed_data[k] = 100.0 * float(parsed_data[k])
                break
    def _cp_type(data):
        if "concordance_concordance" in parsed_data:
            return "concordance"
        elif "contamination_normal" in parsed_data:
            return "contamination"
    if len(parsed_data) > 0:
        if f["s_name"] in self.conpair_data:
            if _cp_type(self.conpair_data[f["s_name"]]) == _cp_type(parsed_data):
                log.debug("Duplicate sample name found! Overwriting: {}".format(f["s_name"]))
        else:
            self.conpair_data[f["s_name"]] = dict()
        self.add_data_source(f, section=_cp_type(parsed_data))
        self.conpair_data[f["s_name"]].update(parsed_data)