#
#   QuantConnect Basic Template:
#    Fundamentals to using a QuantConnect algorithm.
#
#    You can view the QCAlgorithm base class on Github: 
#    https://github.com/QuantConnect/Lean/tree/master/Algorithm
#

import numpy as np
import csv
import pandas as pd
from datetime import datetime, timezone
from dateutil import parser
import pytz
# from data_service import DataService

class BasicTemplateAldgorithm(QCAlgorithm):

    def Initialize(self):
        # Set the cash we'd like to use for our backtest
        # This is ignored in live trading 
        self.SetCash(100000)
        self.SetTimeZone(TimeZones.Utc)
        
        # Set Brokerage model to load OANDA fee structure.
        self.SetBrokerageModel(BrokerageName.OandaBrokerage)
        
        alg = 'a1'
        symbol = 'GBPUSD'
        granularity = 'M5'
        
        # Add assets you'd like to see
        self.pair = self.AddForex(symbol, Resolution.Minute).Symbol
        
        file = self.Download('https://twitter-copy-pip.herokuapp.com/signal_data/{0}/{1}/{2}'.format(alg, symbol, granularity))
        # self.Debug(str(file))
        sig_data = pd.read_json(file, orient='split')
        sig_data = sig_data.sort_values(by=['time'])
        first_date = datetime.utcfromtimestamp(sig_data.iloc[0]['time']/1000)
        self.Debug('first_date'+str(first_date))
        last_date = datetime.utcfromtimestamp(sig_data.iloc[len(sig_data)-1]['time']/1000)
        self.Debug('last_date'+str(last_date))
        
        # Start and end dates for the backtest.
        # These are ignored in live trading.
        self.SetStartDate(first_date.year, first_date.month, first_date.day)
        self.SetEndDate(last_date.year, last_date.month, last_date.day)
        
        if alg == 'a1':
            action_key = 'action'
        else:
            action_key = '{0}_action'.format(alg)
        
        # self.Debug(str(sig_data))
        for i, row in sig_data.iterrows():
            dt = datetime.utcfromtimestamp(row['time']/1000)
            if row[action_key] == 'BUY':
                self.Debug('creating buy order '+ str(dt))
                self.Schedule.On(
                    self.DateRules.On(dt.year, dt.month, dt.day),
                    self.TimeRules.At(dt.hour, dt.minute),
                    Action(self.ScheduledBuy))
            if row[action_key] == 'SELL':
                self.Debug('creating sell order '+ str(dt))
                self.Schedule.On(
                    self.DateRules.On(dt.year, dt.month, dt.day),
                    self.TimeRules.At(dt.hour, dt.minute),
                    Action(self.ScheduledSell))
            if row[action_key] == 'HOLD':
                self.Debug('CLOSING order '+ str(dt))
                self.Schedule.On(
                    self.DateRules.On(dt.year, dt.month, dt.day),
                    self.TimeRules.At(dt.hour, dt.minute),
                    Action(self.ScheduledHold))
    
    def ScheduledBuy(self):
        # if self.Portfolio.Invested:
            # self.Liquidate(self.pair)
        # self.MarketOrder(self.pair, 1000000)
        self.SetHoldings(self.pair, 50.0, liquidateExistingHoldings=True)
    
    
    def ScheduledSell(self):
        # if self.Portfolio.Invested:
        #     self.Liquidate(self.pair)
        # self.MarketOrder(self.pair, -1000000)
        self.SetHoldings(self.pair, -50.0, liquidateExistingHoldings=True)
    
    def ScheduledHold(self):
        if self.Portfolio.Invested:
            self.Liquidate(self.pair)

    def OnData(self, slice):
        pass

# QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
# Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

from clr import AddReference
AddReference("System")
AddReference("QuantConnect.Algorithm")
AddReference("QuantConnect.Common")

from System import *
from QuantConnect import *
from QuantConnect.Algorithm import *
from QuantConnect.Data import SubscriptionDataSource
from QuantConnect.Python import PythonData

from datetime import date, timedelta, datetime
import decimal
import numpy as np
import json

### <summary>
### Demonstration of using an external custom datasource. LEAN Engine is incredibly flexible and allows you to define your own data source.
### This includes any data source which has a TIME and VALUE. These are the *only* requirements. To demonstrate this we're loading in "Bitsig_data" data.
### </summary>
### <meta name="tag" content="using data" />
### <meta name="tag" content="custom data" />
### <meta name="tag" content="crypto" />
# class CustomDataBitsig_dataAlgorithm(QCAlgorithm):

#     def Initialize(self):
#         self.SetStartDate(2011, 9, 13)
#         self.SetEndDate(datetime.now().date() - timedelta(1))
#         self.SetCash(100000)

#         # Define the symbol and "type" of our generic data:
#         self.AddData(Bitsig_data, "BTC")


#     def OnData(self, data):
#         if not data.ContainsKey("BTC"): return

#         close = data["BTC"].Close

#         # If we don't have any weather "SHARES" -- invest"
#         if not self.Portfolio.Invested:
#             # Weather used as a tradable asset, like stocks, futures etc.
#             self.SetHoldings("BTC", 1)
#             self.Debug("Buying BTC 'Shares': BTC: {0}".format(close))

#         self.Debug("Time: {0} {1}".format(datetime.now(), close))


class SignalData(PythonData):
    '''Custom Data Type: Bitsig_data data from Quandl - http://www.quandl.com/help/api-for-bitsig_data-data'''

    def GetSource(self, config, date, isLiveMode):
        # if isLiveMode:
        #     return SubscriptionDataSource("https://www.bitstamp.net/api/ticker/", SubscriptionTransportMedium.Rest);

        #return "http://my-ftp-server.com/futures-data-" + date.ToString("Ymd") + ".zip";
        # OR simply return a fixed small data file. Large files will slow down your backtest
        return SubscriptionDataSource("https://twitter-copy-pip.herokuapp.com/a1_signal_data/EURUSD_H1.csv?order=asc", SubscriptionTransportMedium.RemoteFile);


    def Reader(self, config, line, date, isLiveMode):
        sig_data = Bitsig_data()
        sig_data.Symbol = config.Symbol

        if isLiveMode:
            # Example Line Format:
            # {"high": "441.00", "last": "421.86", "timestamp": "1411606877", "bid": "421.96", "vwap": "428.58", "volume": "14120.40683975", "low": "418.83", "ask": "421.99"}
            try:
                liveBTC = json.loads(line)

                # If value is zero, return None
                value = decimal.Decimal(liveBTC["last"])
                if value == 0: return None

                sig_data.Time = datetime.now()
                sig_data.Value = value
                sig_data["Open"] = float(liveBTC["open"])
                sig_data["High"] = float(liveBTC["high"])
                sig_data["Low"] = float(liveBTC["low"])
                sig_data["Close"] = float(liveBTC["last"])
                sig_data["Ask"] = float(liveBTC["ask"])
                sig_data["Bid"] = float(liveBTC["bid"])
                sig_data["VolumeBTC"] = float(liveBTC["volume"])
                sig_data["WeightedPrice"] = float(liveBTC["vwap"])
                return sig_data
            except ValueError:
                # Do nothing, possible error in json decoding
                return None

        # Example Line Format:
        # Date      Open   High    Low     Close   Volume (BTC)    Volume (Currency)   Weighted Price
        # 2011-09-13 5.8    6.0     5.65    5.97    58.37138238,    346.0973893944      5.929230648356
        if not (line.strip() and line[0].isdigit()): return None

        try:
            data = line.split(',')

            # If value is zero, return None
            value = decimal.Decimal(data[4])
            if value == 0: return None

            sig_data.Time = datetime.strptime(data[0], "%Y-%m-%d")
            sig_data.Value = value
            sig_data["Open"] = float(data[1])
            sig_data["High"] = float(data[2])
            sig_data["Low"] = float(data[3])
            sig_data["Close"] = float(data[4])
            sig_data["VolumeBTC"] = float(data[5])
            sig_data["VolumeUSD"] = float(data[6])
            sig_data["WeightedPrice"] = float(data[7])
            return sig_data;

        except ValueError:
            # Do nothing, possible error in json decoding
            return None