Jhonathan Abreu
5758b65099
Build & Test Lean / build (push) Has been cancelled
Regression Tests / build (push) Has been cancelled
Research Regression Tests / build (push) Has been cancelled
* Add new Python QCAlgorithm.History() method with all parameters and type * Add regression algorithms * Using all parameters in History() * Use private methods to reuse History() code * Use private methods to reuse History() code * Add unit tests for QCAlgorithm.Python.History() * Add unit tests for QCAlgorithm.Python.History() * Add unit tests for QCAlgorithm.Python.History() * Add unit tests for QCAlgorithm.Python.History() * Add unit tests for QCAlgorithm.Python.History() * Add unit tests for QCAlgorithm.Python.History() * Asserting history count
67 lines
3.2 KiB
Python
67 lines
3.2 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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### <summary>
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### Regression test illustrating how history from custom data sources can be requested. The <see cref="QCAlgorithm.History"/> method used in this
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### example also allows to specify other parameters than just the resolution, such as the data normalization mode, the data mapping mode, etc.
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### </summary>
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class HistoryWithCustomDataSourceRegressionAlgorithm(QCAlgorithm):
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def Initialize(self):
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self.SetStartDate(2014, 6, 5)
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self.SetEndDate(2014, 6, 6)
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self.aapl = self.AddData(CustomData, "AAPL", Resolution.Minute).Symbol
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self.spy = self.AddData(CustomData, "SPY", Resolution.Minute).Symbol
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def OnEndOfAlgorithm(self):
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aaplHistory = self.History(CustomData, self.aapl, self.StartDate, self.EndDate, Resolution.Minute,
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fillForward=False, extendedMarket=False, dataNormalizationMode=DataNormalizationMode.Raw).droplevel(0, axis=0)
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spyHistory = self.History(CustomData, self.spy, self.StartDate, self.EndDate, Resolution.Minute,
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fillForward=False, extendedMarket=False, dataNormalizationMode=DataNormalizationMode.Raw).droplevel(0, axis=0)
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if aaplHistory.size == 0 or spyHistory.size == 0:
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raise Exception("At least one of the history results is empty")
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# Check that both resutls contain the same data, since CustomData fetches APPL data regardless of the symbol
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if not aaplHistory.equals(spyHistory):
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raise Exception("Histories are not equal")
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class CustomData(PythonData):
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'''Custom data source for the regression test algorithm, which returns AAPL equity data regardless of the symbol requested.'''
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def GetSource(self, config, date, isLiveMode):
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return TradeBar().GetSource(
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SubscriptionDataConfig(
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config,
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CustomData,
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# Create a new symbol as equity so we find the existing data files
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# Symbol.Create(config.MappedSymbol, SecurityType.Equity, config.Market)),
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Symbol.Create("AAPL", SecurityType.Equity, config.Market)),
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date,
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isLiveMode)
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def Reader(self, config, line, date, isLiveMode):
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tradeBar = TradeBar.ParseEquity(config, line, date)
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data = CustomData()
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data.Time = tradeBar.Time
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data.Value = tradeBar.Value
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data.Close = tradeBar.Close
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data.Open = tradeBar.Open
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data.High = tradeBar.High
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data.Low = tradeBar.Low
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data.Volume = tradeBar.Volume
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return data
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