c37b450a2e
- Adds PyObject overload to `ScheduleManager.TrainingNow` and `ScheduleManager.Training` - Adds `QCAlgorithm.Train` helper method - Adds Python algorithm showing how to use the helper method.
52 lines
1.9 KiB
Python
52 lines
1.9 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 clr import AddReference
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AddReference("System")
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AddReference("QuantConnect.Algorithm")
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AddReference("QuantConnect.Common")
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from System import *
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from QuantConnect import *
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from QuantConnect.Algorithm import *
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from time import sleep
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### <summary>
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### Example algorithm showing how to use QCAlgorithm.Train method
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### </summary>
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### <meta name="tag" content="using quantconnect" />
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### <meta name="tag" content="training" />
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class TrainingExampleAlgorithm(QCAlgorithm):
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'''Example algorithm showing how to use QCAlgorithm.Train method'''
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def Initialize(self):
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self.SetStartDate(2013, 10, 7)
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self.SetEndDate(2013, 10, 14)
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self.AddEquity("SPY", Resolution.Daily)
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# Set TrainingMethod to be executed immediately
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self.Train(self.TrainingMethod)
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# Set TrainingMethod to be executed at 8:00 am every Sunday
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self.Train(self.DateRules.Every(DayOfWeek.Sunday), self.TimeRules.At(8 , 0), self.TrainingMethod)
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def TrainingMethod(self):
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self.Log(f'Start training at {self.Time}')
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# Use the historical data to train the machine learning model
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history = self.History(["SPY"], 200, Resolution.Daily)
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# ML code:
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pass |