Michael Handschuh
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.
62 lines
2.8 KiB
Python
62 lines
2.8 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 QuantConnect.Python import PythonQuandl
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from datetime import datetime, timedelta
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### <summary>
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### Futures demonstration algorithm.
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### QuantConnect allows importing generic data sources! This example demonstrates importing a futures
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### data from the popular open data source Quandl. QuantConnect has a special deal with Quandl giving you access
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### to Stevens Continuous Futurs (SCF) for free. If you'd like to download SCF for local backtesting, you can download it through Quandl.com.
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### </summary>
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### <meta name="tag" content="using data" />
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### <meta name="tag" content="quandl" />
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### <meta name="tag" content="custom data" />
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### <meta name="tag" content="futures" />
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class QuandlFuturesDataAlgorithm(QCAlgorithm):
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def Initialize(self):
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''' Initialize the data and resolution you require for your strategy '''
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self.SetStartDate(2000, 1, 1)
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self.SetEndDate(datetime.now().date() - timedelta(1))
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self.SetCash(25000)
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# Symbol corresponding to the quandl code
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self.crude = "SCF/CME_CL1_ON"
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self.AddData(QuandlFuture, self.crude, Resolution.Daily)
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def OnData(self, data):
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'''Data Event Handler: New data arrives here. "TradeBars" type is a dictionary of strings so you can access it by symbol.'''
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if self.Portfolio.HoldStock: return
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self.SetHoldings(self.crude, 1)
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self.Debug(str(self.Time) + str(" Purchased Crude Oil: ") + self.crude)
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class QuandlFuture(PythonQuandl):
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'''Custom quandl data type for setting customized value column name. Value column is used for the primary trading calculations and charting.'''
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def __init__(self):
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# Define ValueColumnName: cannot be None, Empty or non-existant column name
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# If ValueColumnName is "Close", do not use PythonQuandl, use Quandl:
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# self.AddData[QuandlFuture](self.crude, Resolution.Daily)
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self.ValueColumnName = "Settle" |