def METHOD_NAME(file_handler):
    """Parser for _overall_mean_cov.csv files."""
    root = file_handler["root"]
    file = file_handler["fn"]
    # First check the general structure.
    file_match = GEN_FILE_RGX.search(file)
    if file_match:
        sample, phenotype = file_match.group(1), None
        file_match = COV_FILE_RGX.search(file)
        if file_match:
            sample, phenotype, suffix = file_match.groups()
            if suffix:
                # Only non-'tumor' strings are concatenated with the sample.
                if not re.search("tumor", suffix, re.IGNORECASE):
                    sample += suffix
    else:
        log_data["invalid_file_names"][root].append(file)
        return {"success": False}
    # There is still a possibility for failing(eg empty file, unknown metric).
    success = False
    source = None  # File name from "Average alignment coverage over file" metric.
    value = None
    # A loop is created in advance. Maybe new metrics will be added in the future.
    for line in file_handler["f"].splitlines():
        line_match = AVG_RGX.search(line)
        # If line is fine then extract the necessary fields.
        if line_match:
            success = True
            source, value = line_match.groups()
        # Otherwise check if line is empty. If not then report it and go to the next line.
        else:
            if not re.search("^\s*$", line):
                log_data["unknown_metrics"].append(line)
            continue
        # Try to convert the value. It shall be float.
        try:
            value = float(value)
        except ValueError:
            log_data["unusual_values"][root][file][line] = value
    return {
        "success": success,
        "sample": sample,
        "phenotype": phenotype,
        "data": {"source_file": source, "value": value},
    }