Generic command support
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- Adding generic algorithm command support. Adding regression algorithms
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# 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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class VoidCommand():
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quantity = 0
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def run(self, algo: QCAlgorithm):
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algo.buy("BAC", self.get_quantity())
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def get_quantity(self):
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return self.quantity
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class BoolCommand(Command):
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result = False
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def run(self, algo: QCAlgorithm):
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trade_ibm = self.my_custom_method()
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if trade_ibm:
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algo.buy("IBM", 1)
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return trade_ibm
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def my_custom_method(self):
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return self.result
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### <summary>
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### Regression algorithm asserting the behavior of different callback commands call
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### </summary>
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class CallbackCommandRegressionAlgorithm(QCAlgorithm):
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def initialize(self):
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'''Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.'''
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self.set_start_date(2013, 10, 7)
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self.set_end_date(2013, 10, 11)
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self.add_equity("SPY")
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self.add_equity("IBM")
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self.add_equity("BAC")
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self.add_command(VoidCommand)
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self.add_command(BoolCommand)
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def on_command(self, data):
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self.buy(data.symbol, 1)
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return True # False, None
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