mirror of
https://github.com/wassname/catalyst.git
synced 2026-07-11 03:00:04 +08:00
Eddie Hebert
0ab136f1c8
Hopefully, this helps ease ramp up time for developing against market data, without us distributing the data. We do a check for the data when attempting to read the msgpack files, if they don't exist the loader makes a web request and retrieves and serializes the data for the user. Provides a loader for: - curves from data.treasury.gov - benchmarks from Yahoo! Finance Adds dependency of requests library in dev requirements.
72 lines
2.1 KiB
Python
72 lines
2.1 KiB
Python
#
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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 os
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if __name__ == "__main__":
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import sys
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sys.path.append(os.path.abspath('.'))
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print sys.path
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import msgpack
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from treasuries import get_treasury_data
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from benchmarks import get_benchmark_returns
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def dump_treasury_curves():
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"""
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Dumps data to be used with zipline.
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Puts source treasury and data into zipline.
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"""
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tr_data = []
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for curve in get_treasury_data():
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print curve
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date_as_tuple = curve['date'].timetuple()[0:6] + \
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(curve['date'].microsecond,)
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# Not ideal but massaging data into expected format
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del curve['date']
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tr = (date_as_tuple, curve)
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tr_data.append(tr)
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tr_path = os.path.join(os.path.dirname(__file__),
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"treasury_curves.msgpack")
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tr_fp = open(tr_path, "wb")
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tr_fp.write(msgpack.dumps(tr_data))
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def dump_benchmarks():
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"""
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Dumps data to be used with zipline.
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Puts source treasury and data into zipline.
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"""
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benchmark_path = os.path.join(os.path.dirname(__file__),
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"benchmark.msgpack")
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benchmark_fp = open(benchmark_path, "wb")
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benchmark_data = []
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for daily_return in get_benchmark_returns():
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print daily_return
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date_as_tuple = daily_return.date.timetuple()[0:6] + \
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(daily_return.date.microsecond,)
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# Not ideal but massaging data into expected format
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benchmark = (date_as_tuple, daily_return.returns)
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benchmark_data.append(benchmark)
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benchmark_fp.write(msgpack.dumps(benchmark_data))
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