import json
from datetime import datetime
from pathlib import Path

import fire
import pandas as pd
import requests
from bs4 import BeautifulSoup

bundesland_dict = {
    "110": "Schleswig-Holstein",
    "112": "Schleswig-Holstein",
    "103": "Schleswig-Holstein",
    "111": "Schleswig-Holstein",
    "109": "Mecklenburg-Vorpommern",
    "105": "Mecklenburg-Vorpommern",
    "108": "Mecklenburg-Vorpommern",
    "213": "Niedersachsen",
    "214": "Bremen",
    "217": "Niedersachsen",
    "215": "Niedersachsen",
    "305": "Berlin",
    "306": "Brandenburg",
    "307": "Brandenburg",
    "308": "Brandenburg",
    "432": "NRW",
    "433": "NRW",
    "435": "NRW",
    "437": "NRW",
    "442": "NRW",
    "443": "NRW",
    "444": "NRW",
    "445": "NRW",
    "446": "NRW",
    "447": "NRW",
    "448": "NRW",
    "506": "Rheinland-Pfalz",
    "507": "Rheinland-Pfalz",
    "508": "Rheinland-Pfalz",
    "601": "Hessen",
    "603": "Hessen",
    "604": "Hessen",
    "608": "Hessen",
    "609": "Hessen",
    "610": "Hessen",
    "701": "Sachsen",
    "706": "Sachsen-Anhalt",
    "707": "Sachsen-Anhalt",
    "712": "Thüringen",
    "713": "Sachsen",
    "801": "Bayern",
    "802": "Bayern",
    "803": "Bayern",
    "804": "Bayern",
    "806": "Bayern",
    "808": "Bayern",
    "809": "Bayern",
    "810": "Bayern",
    "811": "Bayern",
    "812": "Bayern",
    "813": "Bayern",
    "814": "Bayern",
    "904": "Baden-Württemberg",
    "905": "Baden-Württemberg",
    "912": "Baden-Württemberg",
    "914": "Baden-Württemberg",
    "915": "Baden-Württemberg",
    "916": "Baden-Württemberg",
    "917": "Baden-Württemberg",
    "1001": "Hamburg",
}


landesbezirk_dict = {
    "100": "Nord",
    "200": "Niedersachsen-Bremen",
    "300": "Berlin-Brandenburg",
    "400": "Nordrhein-Westfalen",
    "500": "Rheinland-Pfalz-Saarland",
    "600": "Hessen",
    "700": "Sachsen, Sachsen-Anhalt, Thüringen",
    "800": "Bayern",
    "900": "Baden-Württemberg",
    "1000": "Hamburg",
}


def get_landesbezirk(id: str):
    return landesbezirk_dict[str((int(id) // 100) * 100)]


def get_bez_data(
    tags: list[str], url: str = "https://beschaeftigtenbefragung.verdi.de/"
) -> list[dict]:
    r = requests.get(url)
    soup = BeautifulSoup(r.text, "html.parser")
    bez_data = []
    for tag in tags:
        for a in soup.find_all("script"):
            script_contents = a.decode_contents()
            if script_contents.find(tag) >= 0:
                break

        substring = script_contents[script_contents.find(tag) + len(tag) + 3 :]
        bez_data.append(json.loads(substring[: substring.find("\n") - 1]))
    return bez_data


def construct_dataframe(
    bez_data: dict[str, dict],
    special_tag: str | None = None,
):
    data = {}

    first_key = next(iter(bez_data.keys()))
    if first_key in landesbezirk_dict:
        data["Landesbezirk"] = pd.Series(
            [v["name"] for v in bez_data.values()], index=list(bez_data.keys())
        )
    else:
        data["Bundesland"] = pd.Series(
            [bundesland_dict[k] for k in bez_data], index=list(bez_data.keys())
        )
        data["Bezirk"] = pd.Series(
            [v["name"] for v in bez_data.values()], index=list(bez_data.keys())
        )

    tot_col_data = []
    tot_col_index = []
    if special_tag:
        for k, v in bez_data.items():
            if "sp" in v and special_tag in v["sp"]:
                tot_col_data.append(v["sp"][special_tag])
                tot_col_index.append(k)
    else:
        for k, v in bez_data.items():
            if "tot" in v:
                tot_col_data.append(v["tot"])
                tot_col_index.append(k)

    data["Digitale Befragung"] = pd.Series(tot_col_data, index=tot_col_index)
    return pd.DataFrame(data=data).astype({"Digitale Befragung": "Int32"})


def main(
    url: str = "https://beschaeftigtenbefragung.verdi.de/",
    tag: str = "bez_data_2",
    dry_run: bool = False,
    grouped: bool = False,
    special_tag: str | None = None,
    folder: str = "data",
    name: str = "data",
    sheet_name: str = "digital",
) -> None:
    bez_data = get_bez_data([tag], url)[0]
    df = construct_dataframe(
        bez_data=bez_data,
        special_tag=special_tag,
    )

    if grouped:
        df = df.groupby("Bundesland", as_index=False)[["Digitale Befragung"]].sum()

    if dry_run:
        print(df)
    else:
        filename = f"{folder}/{datetime.today().strftime('%Y-%m-%d')}_{name}.ods"
        if Path(filename).exists():
            print("File already exists!")
        else:
            df.to_excel(filename, sheet_name=sheet_name)


if __name__ == "__main__":
    fire.Fire(main)