def main()

in courses/understanding_spanner/spanner-challenge-lab/import-products-to-spanner.py [0:0]

• 37 lines of code
• 1 McCabe index (conditional complexity)

def main(argv=None, save_main_session=True):
    """Main entry point."""
    projectid = os.environ.get('GOOGLE_CLOUD_PROJECT')
    parser = argparse.ArgumentParser()
    parser.add_argument(
        '--input',
        dest='input',
        default='products.csv',
        help='Input filename.')
    parser.add_argument(
        '--instance',
        dest='instance',
        default='challenge-lab-instance',
        help='Spanner instance ID.')
    parser.add_argument(
        '--database',
        dest='database',
        default = 'orders-db',      
        help='Spanner database.')
    parser.add_argument(
        '--table',
        dest='table',
        default = 'products',      
        help='Spanner table.')
    known_args, pipeline_args = parser.parse_known_args(argv)

    pipeline_options = PipelineOptions(pipeline_args)
    pipeline_options.view_as(SetupOptions).save_main_session = save_main_session

    with beam.Pipeline(options=pipeline_options) as p:
        products = p | 'Read CSV to dataframe' >> read_csv(known_args.input)

        products = ( convert.to_pcollection(products)
            | 'Convert to ProductRow class' >> beam.Map(lambda x : ProductRow(**(x._asdict())))
            | 'Reverse bits in prod_code' >> beam.Map(lambda x : ProductRow(reverse_bits(x.prod_code), x.prod_name, x.prod_desc, x.prod_price))
        )

        products | 'Write to Spanner' >> SpannerInsert(
                    project_id=projectid,
                    instance_id=known_args.instance,
                    database_id=known_args.database,
                    table=known_args.table)