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# to you under the Apache License, Version 2.0 (the
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#
#   http://www.apache.org/licenses/LICENSE-2.0
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import datetime
import random

import geohash
import pandas as pd
from sqlalchemy import DateTime, Float, String

from superset import db
from superset.models.slice import Slice
from superset.utils import core as utils

from .helpers import (
    get_example_data,
    get_slice_json,
    get_table_connector_registry,
    merge_slice,
    misc_dash_slices,
)


def load_long_lat_data(only_metadata: bool = False, force: bool = False) -> None:
    """Loading lat/long data from a csv file in the repo"""
    tbl_name = "long_lat"
    database = utils.get_example_database()
    table_exists = database.has_table_by_name(tbl_name)

    if not only_metadata and (not table_exists or force):
        data = get_example_data("san_francisco.csv.gz", make_bytes=True)
        pdf = pd.read_csv(data, encoding="utf-8")
        start = datetime.datetime.now().replace(
            hour=0, minute=0, second=0, microsecond=0
        )
        pdf["datetime"] = [
            start + datetime.timedelta(hours=i * 24 / (len(pdf) - 1))
            for i in range(len(pdf))
        ]
        pdf["occupancy"] = [random.randint(1, 6) for _ in range(len(pdf))]
        pdf["radius_miles"] = [random.uniform(1, 3) for _ in range(len(pdf))]
        pdf["geohash"] = pdf[["LAT", "LON"]].apply(lambda x: geohash.encode(*x), axis=1)
        pdf["delimited"] = pdf["LAT"].map(str).str.cat(pdf["LON"].map(str), sep=",")
        pdf.to_sql(
            tbl_name,
            database.get_sqla_engine(),
            if_exists="replace",
            chunksize=500,
            dtype={
                "longitude": Float(),
                "latitude": Float(),
                "number": Float(),
                "street": String(100),
                "unit": String(10),
                "city": String(50),
                "district": String(50),
                "region": String(50),
                "postcode": Float(),
                "id": String(100),
                "datetime": DateTime(),
                "occupancy": Float(),
                "radius_miles": Float(),
                "geohash": String(12),
                "delimited": String(60),
            },
            index=False,
        )
        print("Done loading table!")
        print("-" * 80)

    print("Creating table reference")
    table = get_table_connector_registry()
    obj = db.session.query(table).filter_by(table_name=tbl_name).first()
    if not obj:
        obj = table(table_name=tbl_name)
    obj.main_dttm_col = "datetime"
    obj.database = database
    obj.filter_select_enabled = True
    db.session.merge(obj)
    db.session.commit()
    obj.fetch_metadata()
    tbl = obj

    slice_data = {
        "granularity_sqla": "day",
        "since": "2014-01-01",
        "until": "now",
        "viz_type": "mapbox",
        "all_columns_x": "LON",
        "all_columns_y": "LAT",
        "mapbox_style": "mapbox://styles/mapbox/light-v9",
        "all_columns": ["occupancy"],
        "row_limit": 500000,
    }

    print("Creating a slice")
    slc = Slice(
        slice_name="Mapbox Long/Lat",
        viz_type="mapbox",
        datasource_type="table",
        datasource_id=tbl.id,
        params=get_slice_json(slice_data),
    )
    misc_dash_slices.add(slc.slice_name)
    merge_slice(slc)