import datetime as dt
import pandas as pd
import util as ut


class ManualStrategy:
    def __init__(self, verbose=False, impact=0.0, commission=0.0):
        self.verbose = verbose
        self.impact = impact
        self.commission = commission

    # this method should create a QLearner, and train it for trading
    def addEvidence(self, symbol="IBM",
                    sd=dt.datetime(2008, 1, 1),
                    ed=dt.datetime(2009, 1, 1),
                    sv=10000):

        # add your code to do learning here

        # example usage of the old backward compatible util function
        syms = [symbol]
        dates = pd.date_range(sd, ed)
        prices_all = ut.get_data(syms, dates)  # automatically adds SPY
        prices = prices_all[syms]  # only portfolio symbols
        # prices_SPY = prices_all['SPY']  # only SPY, for comparison later
        if self.verbose:
            print(prices)

        # example use with new colname
        # automatically adds SPY
        volume_all = ut.get_data(syms, dates, colname="Volume")
        volume = volume_all[syms]  # only portfolio symbols
        # volume_SPY = volume_all['SPY']  # only SPY, for comparison later
        if self.verbose:
            print(volume)

    # this method should use the existing policy and test it against new data
    def testPolicy(self, symbol="IBM",
                   sd=dt.datetime(2009, 1, 1),
                   ed=dt.datetime(2010, 1, 1),
                   sv=10000):
        dates = pd.date_range(sd, ed)
        prices = ut.get_data([symbol], dates)  # automatically adds SPY
        orders = pd.DataFrame(index=prices.index)
        orders["Symbol"] = symbol
        orders["Order"] = ""
        orders["Shares"] = 0

        # here we build a fake set of trades
        orders.iloc[0] = [symbol, "BUY", 1000]
        orders.iloc[40] = [symbol, "SELL", 1000]
        orders.iloc[41] = [symbol, "BUY", 1000]
        orders.iloc[60] = [symbol, "SELL", 2000]
        orders.iloc[61] = [symbol, "BUY", 2000]
        orders.iloc[-1] = [symbol, "SELL", 1000]
        orders = orders[orders["Shares"] != 0]
        return orders