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import logging

import pandas as pd
from sqlalchemy import BigInteger, Float, inspect, Text

import superset.utils.database as database_utils
from superset import db
from superset.sql_parse import Table
from superset.utils import json

from .helpers import get_example_url, get_table_connector_registry

logger = logging.getLogger(__name__)


def load_sf_population_polygons(
    only_metadata: bool = False, force: bool = False
) -> None:
    tbl_name = "sf_population_polygons"
    database = database_utils.get_example_database()
    with database.get_sqla_engine() as engine:
        schema = inspect(engine).default_schema_name
        table_exists = database.has_table(Table(tbl_name, schema))

        if not only_metadata and (not table_exists or force):
            url = get_example_url("sf_population.json.gz")
            df = pd.read_json(url, compression="gzip")
            df["contour"] = df.contour.map(json.dumps)

            df.to_sql(
                tbl_name,
                engine,
                schema=schema,
                if_exists="replace",
                chunksize=500,
                dtype={
                    "zipcode": BigInteger,
                    "population": BigInteger,
                    "contour": Text,
                    "area": Float,
                },
                index=False,
            )

    logger.debug(f"Creating table {tbl_name} reference")
    table = get_table_connector_registry()
    tbl = db.session.query(table).filter_by(table_name=tbl_name).first()
    if not tbl:
        tbl = table(table_name=tbl_name, schema=schema)
        db.session.add(tbl)
    tbl.description = "Population density of San Francisco"
    tbl.database = database
    tbl.filter_select_enabled = True
    tbl.fetch_metadata()