mirror of
https://github.com/wassname/catalyst.git
synced 2026-07-06 01:05:37 +08:00
Eddie Hebert
ead9fc953f
Read tests.risk.answer_key module into an IPython notebook, to start a base to which answer key values and explanations can be added and display without access to Excel. For now, the notebook just provides the latest download link for the spreadsheet.
229 lines
7.6 KiB
Python
229 lines
7.6 KiB
Python
#
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# Copyright 2013 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 hashlib
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import os
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import numpy as np
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import xlrd
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import requests
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def col_letter_to_index(col_letter):
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# Only supports single letter,
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# but answer key doesn't need multi-letter, yet.
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index = 0
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for i, char in enumerate(reversed(col_letter)):
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index += ((ord(char) - 65) + 1) * pow(26, i)
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return index
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DIR = os.path.dirname(os.path.realpath(__file__))
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ANSWER_KEY_CHECKSUMS_PATH = os.path.join(DIR, 'risk-answer-key-checksums')
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ANSWER_KEY_CHECKSUMS = open(ANSWER_KEY_CHECKSUMS_PATH, 'r').read().splitlines()
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ANSWER_KEY_FILENAME = 'risk-answer-key.xlsx'
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ANSWER_KEY_PATH = os.path.join(DIR, ANSWER_KEY_FILENAME)
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ANSWER_KEY_BUCKET_NAME = 'zipline-test_data'
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ANSWER_KEY_DL_TEMPLATE = """
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https://s3.amazonaws.com/zipline-test-data/risk/{md5}/risk-answer-key.xlsx
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""".strip()
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LATEST_ANSWER_KEY_URL = ANSWER_KEY_DL_TEMPLATE.format(
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md5=ANSWER_KEY_CHECKSUMS[-1])
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def answer_key_signature():
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with open(ANSWER_KEY_PATH, 'r') as f:
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md5 = hashlib.md5()
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while True:
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buf = f.read(1024)
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if not buf:
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break
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md5.update(buf)
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return md5.hexdigest()
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def ensure_latest_answer_key():
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"""
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Get the latest answer key from a publically available location.
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Logic for determining what and when to download is as such:
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- If there is no local spreadsheet file, then get the lastest answer key,
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as defined by the last row in the checksum file.
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- If there is a local spreadsheet file:
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-- If the spreadsheet's checksum is in the checksum file:
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--- If the spreadsheet's checksum does not match the latest, then grab the
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the latest checksum and replace the local checksum file.
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--- If the spreadsheet's checksum matches the latest, then skip download,
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and use the local spreadsheet as a cached copy.
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-- If the spreadsheet's checksum is not in the checksum file, then leave
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the local file alone, assuming that the local xls's md5 is not in the list
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due to local modifications during development.
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It is possible that md5's could collide, if that is ever case, we should
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then find an alternative naming scheme.
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The spreadsheet answer sheet is not kept in SCM, as every edit would
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increase the repo size by the file size, since it is treated as a binary.
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"""
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answer_key_dl_checksum = None
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local_answer_key_exists = os.path.exists(ANSWER_KEY_PATH)
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if local_answer_key_exists:
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local_hash = answer_key_signature()
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if local_hash in ANSWER_KEY_CHECKSUMS:
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# Assume previously downloaded version.
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# Check for latest.
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if local_hash != ANSWER_KEY_CHECKSUMS[-1]:
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# More recent checksum, download
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answer_key_dl_checksum = ANSWER_KEY_CHECKSUMS[-1]
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else:
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# Assume local copy that is being developed on
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answer_key_dl_checksum = None
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else:
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answer_key_dl_checksum = ANSWER_KEY_CHECKSUMS[-1]
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if answer_key_dl_checksum:
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res = requests.get(
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ANSWER_KEY_DL_TEMPLATE.format(md5=answer_key_dl_checksum))
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with open(ANSWER_KEY_PATH, 'w') as f:
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f.write(res.content)
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# Get latest answer key on load.
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ensure_latest_answer_key()
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class DataIndex(object):
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"""
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Coordinates for the spreadsheet, using the values as seen in the notebook.
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The python-excel libraries use 0 index, while the spreadsheet in a GUI
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uses a 1 index.
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"""
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def __init__(self, sheet_name, col, row_start, row_end):
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self.sheet_name = sheet_name
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self.col = col
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self.row_start = row_start
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self.row_end = row_end
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@property
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def col_index(self):
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return col_letter_to_index(self.col) - 1
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@property
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def row_start_index(self):
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return self.row_start - 1
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@property
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def row_end_index(self):
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return self.row_end - 1
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def __str__(self):
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return "'{sheet_name}'!{col}{row_start}:{col}{row_end}".format(
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sheet_name=self.sheet_name,
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col=self.col,
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row_start=self.row_start,
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row_end=self.row_end
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)
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class AnswerKey(object):
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RETURNS = DataIndex('Sim Period', 'D', 4, 255)
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# Below matches the inconsistent capitalization in spreadsheet
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BENCHMARK_PERIOD_RETURNS = {
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'Monthly': DataIndex('s_p', 'P', 8, 19),
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'3-Month': DataIndex('s_p', 'Q', 10, 19),
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'6-month': DataIndex('s_p', 'R', 13, 19),
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'year': DataIndex('s_p', 'S', 19, 19),
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}
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BENCHMARK_PERIOD_VOLATILITY = {
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'Monthly': DataIndex('s_p', 'T', 8, 19),
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'3-Month': DataIndex('s_p', 'U', 10, 19),
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'6-month': DataIndex('s_p', 'V', 13, 19),
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'year': DataIndex('s_p', 'W', 19, 19),
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}
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ALGORITHM_PERIOD_RETURNS = {
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'Monthly': DataIndex('Sim Period', 'V', 23, 34),
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'3-Month': DataIndex('Sim Period', 'W', 25, 34),
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'6-month': DataIndex('Sim Period', 'X', 28, 34),
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'year': DataIndex('Sim Period', 'Y', 34, 34),
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}
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ALGORITHM_PERIOD_VOLATILITY = {
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'Monthly': DataIndex('Sim Period', 'Z', 23, 34),
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'3-Month': DataIndex('Sim Period', 'AA', 25, 34),
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'6-month': DataIndex('Sim Period', 'AB', 28, 34),
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'year': DataIndex('Sim Period', 'AC', 34, 34),
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}
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ALGORITHM_PERIOD_SHARPE = {
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'Monthly': DataIndex('Sim Period', 'AD', 23, 34),
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'3-Month': DataIndex('Sim Period', 'AE', 25, 34),
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'6-month': DataIndex('Sim Period', 'AF', 28, 34),
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'year': DataIndex('Sim Period', 'AG', 34, 34),
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}
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ALGORITHM_PERIOD_BETA = {
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'Monthly': DataIndex('Sim Period', 'AH', 23, 34),
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'3-Month': DataIndex('Sim Period', 'AI', 25, 34),
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'6-month': DataIndex('Sim Period', 'AJ', 28, 34),
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'year': DataIndex('Sim Period', 'AK', 34, 34),
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}
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ALGORITHM_PERIOD_ALPHA = {
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'Monthly': DataIndex('Sim Period', 'AL', 23, 34),
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'3-Month': DataIndex('Sim Period', 'AM', 25, 34),
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'6-month': DataIndex('Sim Period', 'AN', 28, 34),
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'year': DataIndex('Sim Period', 'AO', 34, 34),
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}
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ALGORITHM_PERIOD_BENCHMARK_VARIANCE = {
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'Monthly': DataIndex('Sim Period', 'BB', 23, 34),
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'3-Month': DataIndex('Sim Period', 'BC', 25, 34),
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'6-month': DataIndex('Sim Period', 'BD', 28, 34),
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'year': DataIndex('Sim Period', 'BE', 34, 34),
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}
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ALGORITHM_PERIOD_COVARIANCE = {
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'Monthly': DataIndex('Sim Period', 'AX', 23, 34),
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'3-Month': DataIndex('Sim Period', 'AY', 25, 34),
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'6-month': DataIndex('Sim Period', 'AZ', 28, 34),
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'year': DataIndex('Sim Period', 'BA', 34, 34),
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}
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def __init__(self):
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self.workbook = xlrd.open_workbook(ANSWER_KEY_PATH)
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self.sheets = {}
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self.sheets['Sim Period'] = self.workbook.sheet_by_name('Sim Period')
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self.sheets['s_p'] = self.workbook.sheet_by_name('s_p')
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def get_values(self, data_index, decimal=4):
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return [np.round(x, decimal) for x in
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self.sheets[data_index.sheet_name].col_values(
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data_index.col_index,
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data_index.row_start_index,
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data_index.row_end_index + 1)]
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