# 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. import json from AlgorithmImports import * ### ### Regression test to demonstrate importing and trading on custom data. ### ### ### ### ### ### class CustomDataRegressionAlgorithm(QCAlgorithm): def initialize(self) -> None: self.set_start_date(2020,1,5) # Set Start Date self.set_end_date(2020,1,10) # Set End Date self.set_cash(100000) # Set Strategy Cash resolution = Resolution.SECOND if self.live_mode else Resolution.DAILY self.add_data(Bitcoin, "BTC", resolution) seeder = FuncSecuritySeeder(self.get_last_known_prices) self.set_security_initializer(lambda x: seeder.seed_security(x)) self._warmed_up_checked = False def on_data(self, data: Slice) -> None: if not self.portfolio.invested: if data['BTC'].close != 0 : self.order('BTC', self.portfolio.margin_remaining/abs(data['BTC'].close + 1)) def on_securities_changed(self, changes: SecurityChanges) -> None: changes.filter_custom_securities = False for added_security in changes.added_securities: if added_security.symbol.value == "BTC": self._warmed_up_checked = True if not added_security.has_data: raise ValueError(f"Security {added_security.symbol} was not warmed up!") def on_end_of_algorithm(self) -> None: if not self._warmed_up_checked: raise ValueError("Security was not warmed up!") class Bitcoin(PythonData): '''Custom Data Type: Bitcoin data from Quandl - https://data.nasdaq.com/databases/BCHAIN''' def get_source(self, config: SubscriptionDataConfig, date: datetime, is_live_mode: bool) -> SubscriptionDataSource: if is_live_mode: return SubscriptionDataSource("https://www.bitstamp.net/api/ticker/", SubscriptionTransportMedium.REST) #return "http://my-ftp-server.com/futures-data-" + date.to_string("Ymd") + ".zip" # OR simply return a fixed small data file. Large files will slow down your backtest subscription = SubscriptionDataSource("https://www.quantconnect.com/api/v2/proxy/nasdaq/api/v3/datatables/QDL/BITFINEX.csv?code=BTCUSD&api_key=WyAazVXnq7ATy_fefTqm") subscription.sort = True return subscription def reader(self, config: SubscriptionDataConfig, line: str, date: datetime, is_live_mode: bool) -> DynamicData: coin = Bitcoin() coin.symbol = config.symbol if is_live_mode: # 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: live_btc = json.loads(line) # If value is zero, return coin value = live_btc["last"] if value == 0: return coin coin.time = datetime.now() coin.value = value coin["Open"] = float(live_btc["open"]) coin["High"] = float(live_btc["high"]) coin["Low"] = float(live_btc["low"]) coin["Close"] = float(live_btc["last"]) coin["Ask"] = float(live_btc["ask"]) coin["Bid"] = float(live_btc["bid"]) coin["VolumeBTC"] = float(live_btc["volume"]) coin["WeightedPrice"] = float(live_btc["vwap"]) return coin except ValueError: # Do nothing, possible error in json decoding return coin # Example Line Format: # code date high low mid last bid ask volume # BTCUSD 2024-10-08 63248.0 61940.0 62246.5 62245.0 62246.0 62247.0 477.91102114 if not (line.strip() and line[7].isdigit()): return coin try: data = line.split(',') coin.time = datetime.strptime(data[1], "%Y-%m-%d") coin.end_time = coin.time + timedelta(days=1) coin.value = float(data[5]) coin["High"] = float(data[2]) coin["Low"] = float(data[3]) coin["Mid"] = float(data[4]) coin["Close"] = float(data[5]) coin["Bid"] = float(data[6]) coin["Ask"] = float(data[7]) coin["VolumeBTC"] = float(data[8]) return coin except ValueError: # Do nothing, possible error in json decoding return coin