# flake8: noqa
import humanize
from typing import Any
import os

import dlt
from dlt.common import pendulum
from dlt.sources.credentials import ConnectionStringCredentials

from dlt.sources.sql_database import sql_database, sql_table, Table

from sqlalchemy.sql.sqltypes import TypeEngine
import sqlalchemy as sa


def load_select_tables_from_database() -> None:
    """Use the sql_database source to reflect an entire database schema and load select tables from it.

    This example sources data from the public Rfam MySQL database.
    """
    # Create a pipeline
    pipeline = dlt.pipeline(
        pipeline_name="mysql_test",
        destination='bigquery',
        dataset_name="raw_mysql_data",)

    credentials = ConnectionStringCredentials(
        "mysql+pymysql://pchubapp:7CRJbnVis_Ls@34.150.22.222:3306/pchub_app"
    )

    # Configure the source to load a few select tables incrementally
    source_1 = sql_database().with_resources("cloud_resource")

    # Run the pipeline. The merge write disposition merges existing rows in the destination by primary key
    info = pipeline.run(source_1)
    print(info)


if __name__ == "__main__":
    # Load selected tables with different settings
    load_select_tables_from_database()