#!/usr/bin/env python3

import argparse
import logging
import os
import sqlite3
from datetime import datetime
from datetime import timedelta
from pathlib import Path

import pandas as pd
import plotly.express as px

log = logging.getLogger(__name__)

HERE = Path(os.path.dirname(os.path.realpath(__file__)))

TABLE_NAME = "dc_stats"
INTERVALS = [1]  # on cron interval is 10min


def parse_args():
    parser = argparse.ArgumentParser(description="Extract docker stats in a sqlite db")

    parser.add_argument(
        "sqlite",
        nargs="?",
        type=Path,
        help="Path to sqlite file",
        default=HERE / "stats.sqlite",
    )
    parser.add_argument(
        "html",
        nargs="?",
        type=Path,
        help="Path to html output report",
        default=HERE / "stats.html",
    )
    parser.add_argument("--debug", "-d", action="store_true", help="Run in debug mode")
    parser.add_argument("-n", "--n-days-histo", dest="n_days_histo",
                    type=int,
                    default=30,
                    help="Number of day to show")
    args = parser.parse_args()
    return args.sqlite, args.html, args.debug, args.n_days_histo


def generate_html_report(sqlite_fn: Path, html_fn: Path, n_days_histo):
    # Create your connection.
    log.info(f"Read sqlite {sqlite_fn}")
    cnx = sqlite3.connect(sqlite_fn)

    first_date = datetime.today() - timedelta(days = n_days_histo)
    log.debug(f"First date : {first_date}")

    df = pd.read_sql_query(f"SELECT * FROM {TABLE_NAME} WHERE date > '{first_date}'", cnx)
    df = df.set_index("date")
    log.info(f"Find {len(df)} items")

    # df["granu"] = 1

    dfs = pd.DataFrame()
    for i in INTERVALS:
        dfi = df[::i].copy()

        # dfi["granu"] = i
        dfs = dfs.append(dfi)

    #breakpoint()

    # Remove empty conlumn
    dfs = dfs.dropna(axis=1, how='all')
    #breakpoint()

    log.info(f"Get {len(dfs)} items after sub-sampling")
    fig = px.area(dfs)
    fig.for_each_trace(lambda trace: trace.update(fillcolor=trace.line.color))
    fig["layout"].pop("updatemenus")  # optional, drop animation buttons
    fig.update_layout(transition={"duration": 1e12})
    now = datetime.now()
    fig.update_layout(
        title="Utilisation de RAM pour les docker-compose de l'eunuque (pour voir une stat, mettre la sourie sur "
        f"le haut des courbes, vers les points), généré le {now.strftime('%d/%m/%Y %H:%M:%S')}",
        xaxis_title="Temps",
        yaxis_title="RAM (MiB)",
        legend={"traceorder":"reversed"}
    )
    fig.write_html(html_fn, include_plotlyjs="cdn")
    log.info(f"Report generate in {html_fn}")


def main():
    sqlite_fn, html_fn, debug, n_days_histo = parse_args()
    if debug:
        logging.basicConfig(level=logging.DEBUG)
    else:
        logging.basicConfig(level=logging.INFO)
    generate_html_report(sqlite_fn, html_fn, n_days_histo)


if __name__ == "__main__":
    main()