mirror of
https://github.com/wassname/catalyst.git
synced 2026-06-30 04:34:21 +08:00
Eddie Hebert
7904773d00
The latest flake8 release in now 1.5, which pulls in pep8: 1.3.4a0 The upgrade pep8 has changes to what it picks up as lint. Making code base compatible, so that new devs can install pep8 from PyPI and not have friction over the version difference. Currently using these ignores in the config file: ``` [pep8] ignore = E124,E125,E126 ``` Ignoring these since they are difficult to squash while maintaining an 80 char line length, and appear spurious. Should address later. Updates Travis config, README, and pip requirements to reflect change.
109 lines
2.8 KiB
Python
109 lines
2.8 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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from datetime import datetime
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import csv
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from StringIO import StringIO
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from functools import partial
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import requests
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from loader_utils import (
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date_conversion,
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source_to_records
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)
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from loader_utils import Mapping
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from zipline.finance.risk import DailyReturn
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_BENCHMARK_MAPPING = {
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# Need to add 'symbol' and GSPC as a constant
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'volume': (int, 'Volume'),
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'open': (float, 'Open'),
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'close': (float, 'Close'),
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'high': (float, 'High'),
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'low': (float, 'Low'),
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'adj_close': (float, 'Adj Close'),
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'date': (partial(date_conversion, date_pattern='%Y-%m-%d'), 'Date')
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}
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def benchmark_mappings():
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return {key: Mapping(*value)
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for key, value
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in _BENCHMARK_MAPPING.iteritems()}
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def get_raw_benchmark_data(start_date, end_date):
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# create benchmark files
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# ^GSPC 19500103
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params = {
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# the s&p 500
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's': '^GSPC',
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# end_date month, zero indexed
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'd': end_date.month - 1,
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# end_date day str(int(todate[6:8])) #day
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'e': end_date.day,
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# end_date year str(int(todate[0:4]))
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'f': end_date.year,
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# daily frequency
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'g': 'd',
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# start_date month, zero indexed
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'a': start_date.month - 1,
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# start_date day
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'b': start_date.day,
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# start_date year
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'c': start_date.year
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}
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res = requests.get('http://ichart.yahoo.com/table.csv',
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params=params)
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return csv.DictReader(StringIO(res.content))
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def get_benchmark_data():
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"""
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Benchmarks from Yahoo's GSPC source.
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"""
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start_date = datetime(year=1950, month=1, day=3)
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end_date = datetime.utcnow()
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raw_benchmark_data = get_raw_benchmark_data(start_date, end_date)
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# Reverse data so we can load it in reverse chron order.
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benchmarks_source = reversed(list(raw_benchmark_data))
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mappings = benchmark_mappings()
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return source_to_records(mappings, benchmarks_source)
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def get_benchmark_returns():
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benchmark_returns = []
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for data_point in get_benchmark_data():
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returns = (data_point['close'] - data_point['open']) / \
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data_point['open']
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daily_return = DailyReturn(date=data_point['date'], returns=returns)
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benchmark_returns.append(daily_return)
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return benchmark_returns
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