import datetime
from pathlib import Path
import io
import base64


import pandas as pd
from flask import Flask, render_template, request
from flask_caching import Cache

from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas
import matplotlib.pyplot as plt
import matplotlib.ticker as mtick

from download_digital import construct_dataframe, get_bez_data

config = {
    "CACHE_TYPE": "FileSystemCache",
    "CACHE_DEFAULT_TIMEOUT": 300,
    "CACHE_THRESHOLD": 1000,
    "CACHE_DIR": "cache",
}

app = Flask(__name__)
app.config.from_mapping(config)
cache = Cache(app)


def get_tables(url: str) -> tuple[pd.DataFrame, pd.DataFrame]:
    bez_data = get_bez_data(["bez_data_0", "bez_data_2"], url)

    df = construct_dataframe(
        bez_data=bez_data[0],
        grouped=False,
        special_tag="stud",
    )

    df_state = construct_dataframe(
        bez_data=bez_data[1], grouped=False, no_processing=True
    )

    return df, df_state


def plot(current_df: pd.DataFrame | None = None, data_folder: str = "data", sheet_name: str = "digital", total_target: int = 1500, plot_all: bool = False) -> str:
    data_dict = {}
    for f in sorted(Path(data_folder).iterdir()):
        with f.open("rb") as ff:
            df = pd.read_excel(ff, sheet_name=sheet_name)
        df = df.astype({"Digitale Befragung": "Int32"})
        sum_val = df[["Digitale Befragung"]].sum().iloc[0]
        key = f.name[:10]
        if plot_all or not (int(key[-2:]) - 15) % 7:
            data_dict[key] = sum_val

    data_dict["2023-08-15"] = 275
    if not plot_all and current_df is not None:
        current_df = current_df.astype({"Digitale Befragung": "Int32"})
        sum_val = current_df[["Digitale Befragung"]].sum().iloc[0]
        data_dict["jetzt"] = sum_val

    if plot_all:
        for day in range(16, 19):
            data_dict[f"2023-08-{day}"] = 0
        for day in range(25, 27):
            data_dict[f"2023-08-{day}"] = 0

    sorted_data_dict = {
        k: v
        for k, v in sorted(data_dict.items(), key=lambda x: x[0])
    }

    plt.figure(figsize=(6, 5), dpi=300)

    plt.bar(sorted_data_dict.keys(), sorted_data_dict.values(), color="#e4004e")
    plt.title("Entwicklung Digitale Beschäftigtenbefragung")

    plt.ylabel("# Teilnahmen")

    def val_to_perc(val):
        return 100 * val / total_target

    def perc_to_val(perc):
        return perc * total_target / 100

    sec_ax = plt.gca().secondary_yaxis("right", functions=(val_to_perc, perc_to_val))
    sec_ax.set_ylabel("# Teilnahmen [% Erfolg]")
    sec_ax.yaxis.set_major_formatter(mtick.PercentFormatter())

    plt.axhline(y=total_target, color="#48a9be", linestyle="--")
    # plt.axhline(y=federal_target_sheets[1], color="#48a9be", linestyle="--")
    # plt.axhline(y=federal_target_sheets[2], color="#48a9be", linestyle="--")

    # tikzplotlib.save("plot.tikz", axis_width="\\linewidth")
    plt.tight_layout()

    # Convert plot to PNG image
    pngImage = io.BytesIO()
    FigureCanvas(plt.gcf()).print_png(pngImage)

    # Encode PNG image to base64 string
    pngImageB64String = "data:image/png;base64,"
    pngImageB64String += base64.b64encode(pngImage.getvalue()).decode('utf8')

    return pngImageB64String


@app.route("/")
@cache.cached(timeout=50)
def tables(
    url: str = "https://beschaeftigtenbefragung.verdi.de/",
):
    df, df_state = get_tables(url)

    df = df.sort_values(
        ["Digitale Befragung", "Bundesland", "Bezirk"], ascending=[False, True, True]
    )

    df_state = df_state.sort_values("Landesbezirk")

    output_str = []

    def _print_as_html(df: pd.DataFrame):
        df = df.astype({"Digitale Befragung": "Int32"})
        with pd.option_context("display.max_rows", None):
            table = df.to_html(
                index_names=False,
                justify="left",
                index=False,
                classes="sortable dataframe",
            )

            tfoot = [
                "  <tfoot>",
                "      <td>Gesamt</td>",
            ]
            for i in range(len(df.columns) - 2):
                tfoot.append("      <td/>")
            tfoot.extend(
                [
                    f"      <td>{df['Digitale Befragung'].sum()}</td>",
                    "    </tr>",
                    "  </tfoot>",
                ]
            )
            tfoot = "\n".join(tfoot)
            idx = table.index("</table>")
            output_str.append(table[: idx - 1])
            output_str.append(tfoot)
            output_str.append(table[idx:])

    _print_as_html(df_state)
    _print_as_html(df)


    image = plot(df_state)


    return render_template(
        "base.html",
        tables="\n".join(output_str),
        timestamp=datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
        image=image,
    )


if __name__ == "__main__":
    app.run()