# 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 AlgorithmImports import * ### ### 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 "Bitcoin" data. ### ### ### ### class CustomDataBitcoinAlgorithm(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(Bitcoin, "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. # It's only OK to use SetHoldings with crypto when using custom data. When trading with built-in crypto data, # use the cashbook. Reference https://github.com/QuantConnect/Lean/blob/master/Algorithm.Python/BasicTemplateCryptoAlgorithm.py self.SetHoldings("BTC", 1) self.Debug("Buying BTC 'Shares': BTC: {0}".format(close)) self.Debug("Time: {0} {1}".format(datetime.now(), close)) class Bitcoin(PythonData): '''Custom Data Type: Bitcoin data from Quandl - http://www.quandl.com/help/api-for-bitcoin-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://www.quantconnect.com/api/v2/proxy/quandl/api/v3/datasets/BCHARTS/BITSTAMPUSD.csv?order=asc&api_key=WyAazVXnq7ATy_fefTqm", SubscriptionTransportMedium.RemoteFile) def Reader(self, config, line, date, isLiveMode): coin = Bitcoin() coin.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 = liveBTC["last"] if value == 0: return None coin.EndTime = datetime.utcnow().astimezone(timezone(str(config.ExchangeTimeZone))).replace(tzinfo=None) coin.Value = value coin["Open"] = float(liveBTC["open"]) coin["High"] = float(liveBTC["high"]) coin["Low"] = float(liveBTC["low"]) coin["Close"] = float(liveBTC["last"]) coin["Ask"] = float(liveBTC["ask"]) coin["Bid"] = float(liveBTC["bid"]) coin["VolumeBTC"] = float(liveBTC["volume"]) coin["WeightedPrice"] = float(liveBTC["vwap"]) return coin 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 = data[4] if value == 0: return None coin.Time = datetime.strptime(data[0], "%Y-%m-%d") coin.EndTime = coin.Time + timedelta(days=1) coin.Value = value coin["Open"] = float(data[1]) coin["High"] = float(data[2]) coin["Low"] = float(data[3]) coin["Close"] = float(data[4]) coin["VolumeBTC"] = float(data[5]) coin["VolumeUSD"] = float(data[6]) coin["WeightedPrice"] = float(data[7]) return coin except ValueError: # Do nothing, possible error in json decoding return None