import datetime
import math
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from pandas_datareader import data as pdr
import backtrader as bt

import strategies as st

# import data
def get_data(stocks, start, end):
    stockData = pdr.get_data_yahoo(stocks, start, end)
    return stockData


def run(strategy, data, fund_mode=False):
    if fund_mode:
        cerebro = bt.Cerebro()
        cerebro.addobserver(bt.observers.FundShares)
    else:
        cerebro = bt.Cerebro(stdstats=False)
        cerebro.addobserver(bt.observers.Broker)
        cerebro.addobserver(bt.observers.BuySell)

    cerebro.adddata(data)
    cerebro.addstrategy(strategy)

    # Broker Information
    broker_args = dict(coc=True)
    cerebro.broker = bt.brokers.BackBroker(**broker_args)
    comminfo = st.PercentageCommisionScheme()
    cerebro.broker.addcommissioninfo(comminfo)

    if fund_mode:
        cerebro.broker.set_fundmode(True)

    cerebro.broker.set_cash(st.month_sum)
    cerebro.addanalyzer(bt.analyzers.DrawDown, _name="drawdown")
    cerebro.addanalyzer(bt.analyzers.VWR, _name="returns")
    cerebro.addanalyzer(
        bt.analyzers.TimeReturn, timeframe=bt.TimeFrame.NoTimeFrame, _name="tr"
    )
    thestrats = cerebro.run()
    thestrat = thestrats[0]
    # cerebro.plot(iplot=False, style="candlestick")
    return thestrat


if __name__ == "__main__":
    df = pd.DataFrame(
        columns=[
            "froi",
            "cost",
            "total_value",
            "times",
            "units",
            "comms",
            "annual%",
            "max_dd_len",
            "max_dd",
            "max_md",
            "twr",
            "tr",
        ]
    )

    stockList = ["^GSPC"]
    # startDate = datetime.datetime.fromisoformat("2000-01-01")
    # endDate = datetime.datetime.fromisoformat("2022-01-01")
    print(stockList[0])
    for period_years in (1, 2, 5):
        endDate = datetime.datetime.now()
        startDate = endDate - datetime.timedelta(days=period_years * 365)
        stockData = get_data(stockList[0], startDate, endDate)
        actualStart: datetime.datetime = stockData.index[0]
        data = bt.feeds.PandasData(dataname=stockData)

        for i, strategy in enumerate(
            (st.SmaCross, st.DCA, st.QDCA, st.VA, st.QVA, st.SmaVA)
        ):
            therun = run(strategy, data)
            dd = therun.analyzers.drawdown
            ret = therun.analyzers.returns
            tr = therun.analyzers.tr
            # print(next(reversed(tr.get_analysis())))
            params = therun.calc_params()
            annual = 100 * (
                (1 + params[0] / 100) ** (365 / (endDate - actualStart).days) - 1
            )
            df.loc[strategy.__name__] = therun.calc_params() + (
                annual,
                dd.get_analysis().max.len,
                dd.get_analysis().max.drawdown,
                dd.get_analysis().max.moneydown,
                ret.get_analysis()["vwr"],
                list(tr.get_analysis().items())[0][1],
            )
        print("Starting from:", actualStart)
        print("Time in Market: {:.1f} years".format((endDate - actualStart).days / 365))
        # print(df[["annual%", "froi", "cost", "total_value", "max_dd", "max_md"]])
        print(df)