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So that the zipline library can be used when installed to a write-protected location, e.g. the global site-packages, moving the download files to a directory in the user's path, which should be writeable. For now, choosing a ~/.zipline/data location.
82 lines
2.2 KiB
Python
82 lines
2.2 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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from os.path import expanduser
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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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# TODO: Make this path customizable.
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DATA_PATH = os.path.join(
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expanduser("~"),
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'.zipline',
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'data'
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)
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def get_datafile(name, mode='r'):
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"""
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Returns a handle to data file.
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Creates containing directory, if needed.
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"""
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if not os.path.exists(DATA_PATH):
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os.makedirs(DATA_PATH)
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return open(os.path.join(DATA_PATH, name), mode)
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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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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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with get_datafile('treasury_curves.msgpack', mode='wb') as tr_fp:
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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_data = []
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for daily_return in get_benchmark_returns():
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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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with get_datafile('benchmark.msgpack', mode='wb') as bmark_fp:
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bmark_fp.write(msgpack.dumps(benchmark_data))
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