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https://github.com/wassname/catalyst.git
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Thomas WieckiandEddie Hebert
b69590a2f7
This is a step towards the goal of uniting Quantopian scripts and zipline. To make the syntax of zipline identical to Quantopian we break out the API methods (like order) and turn them into functions. To access the algo object we add a thread local reference to the current algorithm that is accessed in the API functions. TradingAlgorithm now takes either a string or two functions (initialize and handle_data) that it executes. Use api method decorator for methods available in algoscript. Ported appropriate algorithm tests from internal code.
49 lines
1.6 KiB
Python
Executable File
49 lines
1.6 KiB
Python
Executable File
#!/usr/bin/env python
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#
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# Copyright 2012 Quantopian, Inc.
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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
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#
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# 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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import matplotlib.pyplot as plt
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from datetime import datetime
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import pytz
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from zipline.algorithm import TradingAlgorithm
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from zipline.utils.factory import load_from_yahoo
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class BuyApple(TradingAlgorithm): # inherit from TradingAlgorithm
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"""This is the simplest possible algorithm that does nothing but
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buy 1 apple share on each event.
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"""
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def initialize(self):
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pass
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def handle_data(self, data): # overload handle_data() method
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self.order('AAPL', 1) # order SID (=0) and amount (=1 shares)
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if __name__ == '__main__':
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start = datetime(2008, 1, 1, 0, 0, 0, 0, pytz.utc)
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end = datetime(2010, 1, 1, 0, 0, 0, 0, pytz.utc)
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data = load_from_yahoo(stocks=['AAPL'], indexes={}, start=start,
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end=end)
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simple_algo = BuyApple()
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results = simple_algo.run(data)
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ax1 = plt.subplot(211)
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results.portfolio_value.plot(ax=ax1)
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ax2 = plt.subplot(212, sharex=ax1)
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data.AAPL.plot(ax=ax2)
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plt.gcf().set_size_inches(18, 8)
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