from clr import AddReference
AddReference("System")
AddReference("QuantConnect.Algorithm")
AddReference("QuantConnect.Common")
AddReference("QuantConnect.Indicators") # technical indicators

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

from datetime import date, timedelta, datetime
from collections import deque
import numpy as np
import pandas as pd
import json
import requests

class CustomDataBitcoinAlgorithm(QCAlgorithm):
    
    # Initialize 
    def Initialize(self):
        self.SetStartDate(2019, 6, 22)
        self.SetCash(1000000)
        self.AddCrypto('BTCUSD', Resolution.Minute, Market.Bitfinex)
        consolidator = QuoteBarConsolidator(timedelta(minutes = 5))
        consolidator.DataConsolidated += self.OnDataConsolidated
        self.SubscriptionManager.AddConsolidator("BTCUSD", consolidator)
        self.rsi = RelativeStrengthIndex(10, MovingAverageType.Simple) # define Indicator

    def OnDataConsolidated(self, sender, bar):
        agg_data = self.get_Bitfinex_data()
        close = agg_data[3]
        self.rsi.Update(self.Time, agg_data[3])
        if self.rsi.IsReady:
            rsi_value = self.rsi.Current.Value
            self.Debug('rsi_value {}'.format(rsi_value))
            ## Insert trading logic using the RSI values, place orders, etc.
    def get_Bitfinex_data(self):
        # download data from Bitfinex API
        end_time = self.Time # past 5 minutes time
        start_time = end_time - timedelta(minutes=5) # convert current time to timestamp
        end_tstamp = round(datetime.timestamp(end_time)*1000,0) # convert past 5 minutes to timestamp
        start_tstamp = round(datetime.timestamp(start_time)*1000,0)
        
        getdata_time = datetime.now()
        url = 'https://api-pub.bitfinex.com/v2/trades/tBTCUSD/hist?limit=1&start={}&end={}&sort=-1'.format(start_tstamp, end_tstamp)
        #url = 'https://api-pub.bitfinex.com/v2/trades/tBTCUSD/hist?limit=1'
        response = self.Download(url, user = 'hieppham', )
        self.Debug('data downloading time: {}'.format(datetime.now()-getdata_time))
        
        data = json.loads(response)
        data_df = pd.DataFrame(data, columns = ['id','date','volume','price'])
        
        self.Debug('data size {} rows'.format(data_df.shape[0]))
        
        # aggregate the data
        volume = data_df.volume.abs().sum()
        volume_pos = data_df.volume.apply(lambda x: x if x >0 else 0).sum() # only take trade volume resulted from a taker buy order
        open_price = data_df.price.values[0]
        close_price = data_df.price.values[-1]
        high_price = data_df.price.max()
        low_price = data_df.price.min()
        agg_data = [open_price, high_price, low_price, close_price, volume, volume_pos]
        
        return agg_data