Jhonathan Abreu
07fbbe65bb
* Set default always open market hours entry for base security without subscription Also return proper matching subscription for custom data symbols wihtout subscription. * Minor changes * Minor change
158 lines
8.7 KiB
Python
158 lines
8.7 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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### <summary>
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### This algorithm demonstrates the various ways you can call the History function,
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### what it returns, and what you can do with the returned values.
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### </summary>
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### <meta name="tag" content="using data" />
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### <meta name="tag" content="history and warm up" />
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### <meta name="tag" content="history" />
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### <meta name="tag" content="warm up" />
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class HistoryAlgorithm(QCAlgorithm):
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def Initialize(self):
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self.SetStartDate(2013,10, 8) #Set Start Date
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self.SetEndDate(2013,10,11) #Set End Date
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self.SetCash(100000) #Set Strategy Cash
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# Find more symbols here: http://quantconnect.com/data
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self.AddEquity("SPY", Resolution.Daily)
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self.AddData(CustomDataEquity, "IBM", Resolution.Daily)
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# specifying the exchange will allow the history methods that accept a number of bars to return to work properly
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# we can get history in initialize to set up indicators and such
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self.dailySma = SimpleMovingAverage(14)
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# get the last calendar year's worth of SPY data at the configured resolution (daily)
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tradeBarHistory = self.History([self.Securities["SPY"].Symbol], timedelta(365))
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self.AssertHistoryCount("History<TradeBar>([\"SPY\"], timedelta(365))", tradeBarHistory, 250)
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# get the last calendar day's worth of SPY data at the specified resolution
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tradeBarHistory = self.History(["SPY"], timedelta(1), Resolution.Minute)
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self.AssertHistoryCount("History([\"SPY\"], timedelta(1), Resolution.Minute)", tradeBarHistory, 390)
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# get the last 14 bars of SPY at the configured resolution (daily)
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tradeBarHistory = self.History(["SPY"], 14)
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self.AssertHistoryCount("History([\"SPY\"], 14)", tradeBarHistory, 14)
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# get the last 14 minute bars of SPY
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tradeBarHistory = self.History(["SPY"], 14, Resolution.Minute)
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self.AssertHistoryCount("History([\"SPY\"], 14, Resolution.Minute)", tradeBarHistory, 14)
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# get the historical data from last current day to this current day in minute resolution
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# with Fill Forward and Extended Market options
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intervalBarHistory = self.History(["SPY"], self.Time - timedelta(1), self.Time, Resolution.Minute, True, True)
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self.AssertHistoryCount("History([\"SPY\"], self.Time - timedelta(1), self.Time, Resolution.Minute, True, True)", intervalBarHistory, 960)
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# get the historical data from last current day to this current day in minute resolution
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# with Extended Market option
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intervalBarHistory = self.History(["SPY"], self.Time - timedelta(1), self.Time, Resolution.Minute, False, True)
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self.AssertHistoryCount("History([\"SPY\"], self.Time - timedelta(1), self.Time, Resolution.Minute, False, True)", intervalBarHistory, 828)
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# get the historical data from last current day to this current day in minute resolution
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# with Fill Forward option
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intervalBarHistory = self.History(["SPY"], self.Time - timedelta(1), self.Time, Resolution.Minute, True, False)
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self.AssertHistoryCount("History([\"SPY\"], self.Time - timedelta(1), self.Time, Resolution.Minute, True, False)", intervalBarHistory, 390)
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# get the historical data from last current day to this current day in minute resolution
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intervalBarHistory = self.History(["SPY"], self.Time - timedelta(1), self.Time, Resolution.Minute, False, False)
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self.AssertHistoryCount("History([\"SPY\"], self.Time - timedelta(1), self.Time, Resolution.Minute, False, False)", intervalBarHistory, 390)
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# we can loop over the return value from these functions and we get TradeBars
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# we can use these TradeBars to initialize indicators or perform other math
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for index, tradeBar in tradeBarHistory.loc["SPY"].iterrows():
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self.dailySma.Update(index, tradeBar["close"])
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# get the last calendar year's worth of customData data at the configured resolution (daily)
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customDataHistory = self.History(CustomDataEquity, "IBM", timedelta(365))
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self.AssertHistoryCount("History(CustomDataEquity, \"IBM\", timedelta(365))", customDataHistory, 10)
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# get the last 10 bars of IBM at the configured resolution (daily)
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customDataHistory = self.History(CustomDataEquity, "IBM", 14)
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self.AssertHistoryCount("History(CustomDataEquity, \"IBM\", 14)", customDataHistory, 10)
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# we can loop over the return values from these functions and we'll get Custom data
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# this can be used in much the same way as the tradeBarHistory above
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self.dailySma.Reset()
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for index, customData in customDataHistory.loc["IBM"].iterrows():
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self.dailySma.Update(index, customData["value"])
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# get the last 10 bars worth of Custom data for the specified symbols at the configured resolution (daily)
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allCustomData = self.History(CustomDataEquity, self.Securities.Keys, 14)
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self.AssertHistoryCount("History(CustomDataEquity, self.Securities.Keys, 14)", allCustomData, 20)
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# NOTE: Using different resolutions require that they are properly implemented in your data type. If your
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# custom data source has different resolutions, it would need to be implemented in the GetSource and
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# Reader methods properly.
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#customDataHistory = self.History(CustomDataEquity, "IBM", timedelta(7), Resolution.Minute)
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#customDataHistory = self.History(CustomDataEquity, "IBM", 14, Resolution.Minute)
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#allCustomData = self.History(CustomDataEquity, timedelta(365), Resolution.Minute)
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#allCustomData = self.History(CustomDataEquity, self.Securities.Keys, 14, Resolution.Minute)
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#allCustomData = self.History(CustomDataEquity, self.Securities.Keys, timedelta(1), Resolution.Minute)
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#allCustomData = self.History(CustomDataEquity, self.Securities.Keys, 14, Resolution.Minute)
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# get the last calendar year's worth of all customData data
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allCustomData = self.History(CustomDataEquity, self.Securities.Keys, timedelta(365))
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self.AssertHistoryCount("History(CustomDataEquity, self.Securities.Keys, timedelta(365))", allCustomData, 20)
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# we can also access the return value from the multiple symbol functions to request a single
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# symbol and then loop over it
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singleSymbolCustom = allCustomData.loc["IBM"]
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self.AssertHistoryCount("allCustomData.loc[\"IBM\"]", singleSymbolCustom, 10)
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for customData in singleSymbolCustom:
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# do something with 'IBM.CustomDataEquity' customData data
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pass
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customDataSpyValues = allCustomData.loc["IBM"]["value"]
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self.AssertHistoryCount("allCustomData.loc[\"IBM\"][\"value\"]", customDataSpyValues, 10)
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for value in customDataSpyValues:
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# do something with 'IBM.CustomDataEquity' value data
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pass
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def OnData(self, data):
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'''OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
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Arguments:
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data: Slice object keyed by symbol containing the stock data
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'''
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if not self.Portfolio.Invested:
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self.SetHoldings("SPY", 1)
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def AssertHistoryCount(self, methodCall, tradeBarHistory, expected):
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count = len(tradeBarHistory.index)
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if count != expected:
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raise Exception("{} expected {}, but received {}".format(methodCall, expected, count))
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class CustomDataEquity(PythonData):
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def GetSource(self, config, date, isLive):
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source = "https://www.dl.dropboxusercontent.com/s/o6ili2svndzn556/custom_data.csv?dl=0"
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return SubscriptionDataSource(source, SubscriptionTransportMedium.RemoteFile)
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def Reader(self, config, line, date, isLive):
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if line == None:
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return None
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customData = CustomDataEquity()
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customData.Symbol = config.Symbol
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csv = line.split(",")
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customData.Time = datetime.strptime(csv[0], '%Y%m%d %H:%M')
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customData.EndTime = customData.Time + timedelta(days=1)
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customData.Value = float(csv[1])
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return customData
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