#!/usr/bin/env python

import logging

import apache_beam as beam

from apache_beam.options.pipeline_options import PipelineOptions

from helpers.data_io import ReadFromCsv, UpsertProductsToPg
from helpers.parse_row import parse_row


#     def __init__(self, hostname, port, username, password, database):


class SustainabilityScoreOptions(PipelineOptions):
    """Options for this pipeline"""

    @classmethod
    def _add_argparse_args(cls, parser):
        parser.add_argument("--input", help="Input CSV file to process", type=str)
        parser.add_argument("--pg_hostname", help="Postgres hostname", type=str)
        parser.add_argument("--pg_port", help="Postgres port", type=str)
        parser.add_argument("--pg_username", help="Postgres username", type=str)
        parser.add_argument("--pg_password", help="Postgres password", type=str)
        parser.add_argument("--pg_database", help="Postgres database name", type=str)
        parser.add_argument("--pg_table", help="Postgres table name", type=str)


def main():
    """Construct and run the pipeline"""

    beam_options = PipelineOptions()
    opts = beam_options.view_as(SustainabilityScoreOptions)

    with beam.Pipeline(options=beam_options) as pipeline:
        # fmt: off
        pipeline \
            | beam.Create([opts.input]) \
            | beam.ParDo(ReadFromCsv()) \
            | beam.Map(parse_row) \
            | beam.ParDo(UpsertProductsToPg(
                hostname=opts.pg_hostname,
                port=opts.pg_port,
                username=opts.pg_username,
                password=opts.pg_password,
                database=opts.pg_database,
                table=opts.pg_table,
                table_key="tcin",
            ))
        # fmt: on


if __name__ == "__main__":
    logging.getLogger().setLevel(logging.INFO)
    main()