fdc866fda0
We didn't experience the expected performance improvements. Locally under unit test there was aboout an order of magnitude throughput increase, but when run against the history benchmark, this new approach was 60% slower. We're reverting this for now to perform further analysis and better understand the performance profiling of the python history stack.
51 lines
2.2 KiB
Python
51 lines
2.2 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 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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import numpy as np
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### <summary>
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### Basic template algorithm simply initializes the date range and cash. This is a skeleton
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### framework you can use for designing an algorithm.
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### </summary>
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### <meta name="tag" content="using data" />
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### <meta name="tag" content="using quantconnect" />
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### <meta name="tag" content="trading and orders" />
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class BasicTemplateAlgorithm(QCAlgorithm):
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'''Basic template algorithm simply initializes the date range and cash'''
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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.SetStartDate(2013,10, 7) #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.Second)
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self.Debug("numpy test >>> print numpy.pi: " + str(np.pi))
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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) |