rtsm_test_raw_parser.py

from datetime import datetime

def split_raw_rtsm_test(content):
    """
    Split the raw rtsm test in row and filters out comments and empty lines
    :param content: content of rtsm output file
    """
    results = filter(lambda x: not x.startswith('#'),
                     filter(lambda x: len(x) > 0,
                            map(lambda x: x.strip(),
                                content.split('\n')
                                )
                            ))
    return results


def preparse_rtsm_test_file(content):
    results = []
    result = dict()
    observation = dict()
    for line in content:
        key, value = line.split('=')
        if 'INFO' in key and 'OBS' not in key:
            if 'rcu' in result:
                results.append(result)
                result = dict()

            rcu, mode, observation_id, error_type, start_frequency, stop_frequency, time = value.split(',')
            result.update(rcu=int(rcu),
                          mode=int(mode),
                          error_type=error_type,
                          start_frequency=float(start_frequency),
                          stop_frequency=float(stop_frequency),
                          time=datetime.utcfromtimestamp(float(time)))
        elif 'INFO' in key:
            observation_id, start_time, stop_time, samples = value.split(',')
            observation.update(observation_id=observation_id,
                                             start_time=datetime.utcfromtimestamp(float(start_time)),
                                             end_time=datetime.utcfromtimestamp(float(stop_time)),
                                             samples=int(samples))
        elif 'BAD' in key:
            values = [float(item) for item in value.lstrip('[').rstrip(']').strip().split(' ')]
            result.update(bad_spectrum=values)
        elif 'MEAN' in key:
            values = [float(item) for item in value.lstrip('[').rstrip(']').strip().split(' ')]
            result.update(average_spectrum=values)
    results.append(result)
    observation.update(errors=results)
    return observation


def parse_rtsm_test(content):
    """
    Expects a string content with the rtsm test output
    and output a list of Django Models
    :param content: string content with the station test output
    :return: a list of Django models
    """
    return [preparse_rtsm_test_file(split_raw_rtsm_test(content))]