Jhonathan Abreu
2ddf40b8e9
* feat: support snake-case style Python QCAlgorithm implementations * feat: add unit tests and minor fixes * feat: implement new BasePythonWrapper class for python wrappers. Used to cache methods and contains invoke functionality * feat: make python wrappers implement the new base class for pep8 style support * feat: keep overriden methods in Algorithm Python Wrapper * feat: add unit tests for custom models algorithms with PEP8 style * Bump pythonnet version to 2.0.30 * fix bugs and address peer review * Address peer review * Minor revert * feat: StubsIgnoreAttribute for ignoring members or classes by the stubs generator * Minor fixes * Minor fix * Minor fix * Bump pythonnet version to 2.0.31 * Added Greeks.Lambda_ alias of Lambda for python compatibility. Remove unused method
50 lines
2.1 KiB
Python
50 lines
2.1 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 algorithm asserting the behavior of Universe.Selected collection
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### </summary>
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class UniverseSelectedRegressionAlgorithm(QCAlgorithm):
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def Initialize(self):
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self.SetStartDate(2014, 3, 25)
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self.SetEndDate(2014, 3, 27)
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self.UniverseSettings.Resolution = Resolution.Daily
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self._universe = self.AddUniverse(self.SelectionFunction)
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self.selectionCount = 0
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def SelectionFunction(self, fundamentals):
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sortedByDollarVolume = sorted(fundamentals, key=lambda x: x.DollarVolume, reverse=True)
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sortedByDollarVolume = sortedByDollarVolume[self.selectionCount:]
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self.selectionCount = self.selectionCount + 1
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# return the symbol objects of the top entries from our sorted collection
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return [ x.Symbol for x in sortedByDollarVolume[:self.selectionCount] ]
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def OnData(self, data):
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if Symbol.Create("TSLA", SecurityType.Equity, Market.USA) in self._universe.Selected:
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raise ValueError(f"TSLA shouldn't of been selected")
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self.Buy(next(iter(self._universe.Selected)), 1)
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def OnEndOfAlgorithm(self):
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if self.selectionCount != 3:
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raise ValueError(f"Unexpected selection count {self.selectionCount}")
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if self._universe.Selected.Count != 3 or self._universe.Selected.Count == self._universe.Members.Count:
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raise ValueError(f"Unexpected universe selected count {self._universe.Selected.Count}")
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