wehub-resource-sync
119 lines
5.2 KiB
Python
119 lines
5.2 KiB
Python
# QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
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# Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from AlgorithmImports import *
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import pytz
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### <summary>
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### Demonstration of using an external custom datasource. LEAN Engine is incredibly flexible and allows you to define your own data source.
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### 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.
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### </summary>
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### <meta name="tag" content="using data" />
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### <meta name="tag" content="custom data" />
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### <meta name="tag" content="crypto" />
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class CustomDataBitcoinAlgorithm(QCAlgorithm):
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def initialize(self):
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self.set_start_date(2011, 9, 13)
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self.set_end_date(datetime.now().date() - timedelta(1))
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self.set_cash(100000)
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# Define the symbol and "type" of our generic data:
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self.add_data(Bitcoin, "BTC")
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def on_data(self, data):
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if not data.contains_key("BTC"): return
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close = data["BTC"].close
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# If we don't have any weather "SHARES" -- invest"
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if not self.portfolio.invested:
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# Weather used as a tradable asset, like stocks, futures etc.
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# It's only OK to use SetHoldings with crypto when using custom data. When trading with built-in crypto data,
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# use the cashbook. Reference https://github.com/QuantConnect/Lean/blob/master/Algorithm.python/BasicTemplateCryptoAlgorithm.py
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self.set_holdings("BTC", 1)
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self.debug("Buying BTC 'Shares': BTC: {0}".format(close))
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self.debug("Time: {0} {1}".format(datetime.now(), close))
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class Bitcoin(PythonData):
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'''Custom Data Type: Bitcoin data from Quandl - http://www.quandl.com/help/api-for-bitcoin-data'''
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def get_source(self, config, date, is_live_mode):
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if is_live_mode:
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return SubscriptionDataSource("https://www.bitstamp.net/api/ticker/", SubscriptionTransportMedium.REST)
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#return "http://my-ftp-server.com/futures-data-" + date.to_string("Ymd") + ".zip"
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# OR simply return a fixed small data file. Large files will slow down your backtest
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return SubscriptionDataSource("https://www.quantconnect.com/api/v2/proxy/quandl/api/v3/datasets/BCHARTS/BITSTAMPUSD.csv?order=asc&api_key=WyAazVXnq7ATy_fefTqm", SubscriptionTransportMedium.REMOTE_FILE)
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def reader(self, config, line, date, is_live_mode):
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coin = Bitcoin()
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coin.symbol = config.symbol
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if is_live_mode:
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# Example Line Format:
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# {"high": "441.00", "last": "421.86", "timestamp": "1411606877", "bid": "421.96", "vwap": "428.58", "volume": "14120.40683975", "low": "418.83", "ask": "421.99"}
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try:
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live_btc = json.loads(line)
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# If value is zero, return None
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value = live_btc["last"]
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if value == 0: return None
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coin.end_time = datetime.now(pytz.timezone(str(config.exchange_time_zone)))
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coin.value = value
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coin["Open"] = float(live_btc["open"])
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coin["High"] = float(live_btc["high"])
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coin["Low"] = float(live_btc["low"])
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coin["Close"] = float(live_btc["last"])
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coin["Ask"] = float(live_btc["ask"])
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coin["Bid"] = float(live_btc["bid"])
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coin["VolumeBTC"] = float(live_btc["volume"])
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coin["WeightedPrice"] = float(live_btc["vwap"])
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return coin
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except ValueError:
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# Do nothing, possible error in json decoding
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return None
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# Example Line Format:
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# Date Open High Low Close Volume (BTC) Volume (Currency) Weighted Price
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# 2011-09-13 5.8 6.0 5.65 5.97 58.37138238, 346.0973893944 5.929230648356
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if not (line.strip() and line[0].isdigit()): return None
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try:
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data = line.split(',')
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# If value is zero, return None
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value = data[4]
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if value == 0: return None
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coin.time = datetime.strptime(data[0], "%Y-%m-%d")
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coin.end_time = coin.time + timedelta(days=1)
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coin.value = value
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coin["Open"] = float(data[1])
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coin["High"] = float(data[2])
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coin["Low"] = float(data[3])
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coin["Close"] = float(data[4])
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coin["VolumeBTC"] = float(data[5])
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coin["VolumeUSD"] = float(data[6])
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coin["WeightedPrice"] = float(data[7])
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return coin
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except ValueError:
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# Do nothing, possible error in json decoding
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return None
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