示例#1
0
def main():
    parser = argparse.ArgumentParser(
        'Command line interface to the office TREC DD jig.',
        usage=usage,
        conflict_handler='resolve')
    parser.add_argument('command', help='must be "load", "init", "start", "step", or "stop"')
    parser.add_argument('args', help='input for given command',
                        nargs=argparse.REMAINDER)
    modules = [yakonfig, kvlayer, Harness]
    args = yakonfig.parse_args(parser, modules)

    logging.basicConfig(level=logging.DEBUG)

    if args.command not in set(['load', 'init', 'start', 'step', 'stop']):
        sys.exit('The only valid commands are "load", "init", "start", "step", and "stop".')

    kvl = kvlayer.client()
    label_store = LabelStore(kvl)
    config = yakonfig.get_global_config('harness')
    harness = Harness(config, kvl, label_store)

    if args.command == 'load':
        if not config.get('truth_data_path'):
            sys.exit('Must provide --truth-data-path as an argument')
        if not os.path.exists(config['truth_data_path']):
            sys.exit('%r does not exist' % config['truth_data_path'])
        parse_truth_data(label_store, config['truth_data_path'])
        logger.info('Done!  The truth data was loaded into this '
                     'kvlayer backend:\n%s',
                    json.dumps(yakonfig.get_global_config('kvlayer'),
                               indent=4, sort_keys=True))

    elif args.command == 'init':
        response = harness.init()
        print(json.dumps(response))

    elif args.command == 'start':
        response = harness.start()
        print(json.dumps(response))

    elif args.command == 'stop':
        response = harness.stop(args.args[0])
        print(json.dumps(response))

    elif args.command == 'step':
        parts = args.args
        topic_id = parts.pop(0)
        feedback = harness.step(topic_id, parts)
        print(json.dumps(feedback))
示例#2
0
def main():
    '''Run the random recommender system on a sequence of topics.
    '''
    description = (
        'A baseline recommender system that uses the truth data to'
        ' create output that has perfect recall and would also have'
        ' perfect precision if you ignore subtopic diversity/novelty.'
        ' This generates output directly from the truth data and'
        ' randomly shuffles the truth data per topic, so that'
        ' the ordering of passages does not attempt to optimize any'
        ' particular quality metric.')
    parser = argparse.ArgumentParser(description=description)
    parser.add_argument('--overwrite', action='store_true')
    args = yakonfig.parse_args(parser, [yakonfig])

    logging.basicConfig(level=logging.DEBUG)

    config = yakonfig.get_global_config('harness')
    batch_size = config.get('batch_size', 5)
    run_file_path = config['run_file_path']
    if os.path.exists(run_file_path):
        if args.overwrite:
            os.remove(run_file_path)
        else:
            sys.exit('%r already exists' % run_file_path)

    kvl_config = {
        'storage_type': 'local',
        'namespace': 'test',
        'app_name': 'test'
    }
    kvl = kvlayer.client(kvl_config)
    label_store = LabelStore(kvl)

    parse_truth_data(label_store, config['truth_data_path'])

    # Set up the system
    doc_store = make_doc_store(label_store)
    system = RandomSystem(doc_store)
    ambassador = HarnessAmbassadorCLI(system, args.config, batch_size)
    ambassador.run()