forked from quantopian/zipline
-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathtest_data_portal.py
387 lines (343 loc) · 14.9 KB
/
test_data_portal.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
#
# Copyright 2016 Quantopian, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from collections import OrderedDict
from numpy import array, append, nan, full
from numpy.testing import assert_almost_equal
import pandas as pd
from pandas.tslib import Timedelta
from zipline.assets import Equity
from zipline.testing.fixtures import (
ZiplineTestCase,
WithTradingSessions,
WithDataPortal,
alias,
)
class DataPortalTestBase(WithDataPortal,
WithTradingSessions,
ZiplineTestCase):
ASSET_FINDER_EQUITY_SIDS = (1,)
START_DATE = pd.Timestamp('2016-08-01')
END_DATE = pd.Timestamp('2016-08-08')
TRADING_CALENDAR_STRS = ('NYSE', 'CME')
EQUITY_DAILY_BAR_SOURCE_FROM_MINUTE = True
@classmethod
def make_futures_info(cls):
trading_sessions = cls.trading_sessions['CME']
return pd.DataFrame({
'sid': [10000],
'root_symbol': ['BAR'],
'symbol': ['BARA'],
'start_date': [trading_sessions[1]],
'end_date': [cls.END_DATE],
# TODO: Make separate from 'end_date'
'notice_date': [cls.END_DATE],
'expiration_date': [cls.END_DATE],
'multiplier': [500],
'exchange': ['CME'],
})
@classmethod
def make_equity_minute_bar_data(cls):
trading_calendar = cls.trading_calendars[Equity]
# No data on first day.
dts = trading_calendar.minutes_for_session(cls.trading_days[0])
dfs = []
dfs.append(pd.DataFrame(
{
'open': full(len(dts), nan),
'high': full(len(dts), nan),
'low': full(len(dts), nan),
'close': full(len(dts), nan),
'volume': full(len(dts), 0),
},
index=dts))
dts = trading_calendar.minutes_for_session(cls.trading_days[1])
dfs.append(pd.DataFrame(
{
'open': append(100.5, full(len(dts) - 1, nan)),
'high': append(100.9, full(len(dts) - 1, nan)),
'low': append(100.1, full(len(dts) - 1, nan)),
'close': append(100.3, full(len(dts) - 1, nan)),
'volume': append(1000, full(len(dts) - 1, nan)),
},
index=dts))
dts = trading_calendar.minutes_for_session(cls.trading_days[2])
dfs.append(pd.DataFrame(
{
'open': [nan, 103.50, 102.50, 104.50, 101.50, nan],
'high': [nan, 103.90, 102.90, 104.90, 101.90, nan],
'low': [nan, 103.10, 102.10, 104.10, 101.10, nan],
'close': [nan, 103.30, 102.30, 104.30, 101.30, nan],
'volume': [0, 1003, 1002, 1004, 1001, 0]
},
index=dts[:6]
))
dts = trading_calendar.minutes_for_session(cls.trading_days[3])
dfs.append(pd.DataFrame(
{
'open': full(len(dts), nan),
'high': full(len(dts), nan),
'low': full(len(dts), nan),
'close': full(len(dts), nan),
'volume': full(len(dts), 0),
},
index=dts))
yield 1, pd.concat(dfs)
@classmethod
def make_future_minute_bar_data(cls):
asset = cls.asset_finder.retrieve_asset(10000)
trading_calendar = cls.trading_calendars[asset.exchange]
trading_sessions = cls.trading_sessions[asset.exchange]
# No data on first day, future asset intentionally not on the same
# dates as equities, so that cross-wiring of results do not create a
# false positive.
dts = trading_calendar.minutes_for_session(trading_sessions[1])
dfs = []
dfs.append(pd.DataFrame(
{
'open': full(len(dts), nan),
'high': full(len(dts), nan),
'low': full(len(dts), nan),
'close': full(len(dts), nan),
'volume': full(len(dts), 0),
},
index=dts))
dts = trading_calendar.minutes_for_session(trading_sessions[2])
dfs.append(pd.DataFrame(
{
'open': append(200.5, full(len(dts) - 1, nan)),
'high': append(200.9, full(len(dts) - 1, nan)),
'low': append(200.1, full(len(dts) - 1, nan)),
'close': append(200.3, full(len(dts) - 1, nan)),
'volume': append(2000, full(len(dts) - 1, nan)),
},
index=dts))
dts = trading_calendar.minutes_for_session(trading_sessions[3])
dfs.append(pd.DataFrame(
{
'open': [nan, 203.50, 202.50, 204.50, 201.50, nan],
'high': [nan, 203.90, 202.90, 204.90, 201.90, nan],
'low': [nan, 203.10, 202.10, 204.10, 201.10, nan],
'close': [nan, 203.30, 202.30, 204.30, 201.30, nan],
'volume': [0, 2003, 2002, 2004, 2001, 0]
},
index=dts[:6]
))
dts = trading_calendar.minutes_for_session(trading_sessions[4])
dfs.append(pd.DataFrame(
{
'open': full(len(dts), nan),
'high': full(len(dts), nan),
'low': full(len(dts), nan),
'close': full(len(dts), nan),
'volume': full(len(dts), 0),
},
index=dts))
yield asset.sid, pd.concat(dfs)
def test_get_last_traded_equity_minute(self):
trading_calendar = self.trading_calendars[Equity]
# Case: Missing data at front of data set, and request dt is before
# first value.
dts = trading_calendar.minutes_for_session(self.trading_days[0])
asset = self.asset_finder.retrieve_asset(1)
self.assertTrue(pd.isnull(
self.data_portal.get_last_traded_dt(
asset, dts[0], 'minute')))
# Case: Data on requested dt.
dts = trading_calendar.minutes_for_session(self.trading_days[2])
self.assertEqual(dts[1],
self.data_portal.get_last_traded_dt(
asset, dts[1], 'minute'))
# Case: No data on dt, but data occuring before dt.
self.assertEqual(dts[4],
self.data_portal.get_last_traded_dt(
asset, dts[5], 'minute'))
def test_get_last_traded_future_minute(self):
asset = self.asset_finder.retrieve_asset(10000)
trading_calendar = self.trading_calendars[asset.exchange]
# Case: Missing data at front of data set, and request dt is before
# first value.
dts = trading_calendar.minutes_for_session(self.trading_days[0])
self.assertTrue(pd.isnull(
self.data_portal.get_last_traded_dt(
asset, dts[0], 'minute')))
# Case: Data on requested dt.
dts = trading_calendar.minutes_for_session(self.trading_days[3])
self.assertEqual(dts[1],
self.data_portal.get_last_traded_dt(
asset, dts[1], 'minute'))
# Case: No data on dt, but data occuring before dt.
self.assertEqual(dts[4],
self.data_portal.get_last_traded_dt(
asset, dts[5], 'minute'))
def test_get_last_traded_dt_equity_daily(self):
# Case: Missing data at front of data set, and request dt is before
# first value.
asset = self.asset_finder.retrieve_asset(1)
self.assertTrue(pd.isnull(
self.data_portal.get_last_traded_dt(
asset, self.trading_days[0], 'daily')))
# Case: Data on requested dt.
self.assertEqual(self.trading_days[1],
self.data_portal.get_last_traded_dt(
asset, self.trading_days[1], 'daily'))
# Case: No data on dt, but data occuring before dt.
self.assertEqual(self.trading_days[2],
self.data_portal.get_last_traded_dt(
asset, self.trading_days[3], 'daily'))
def test_get_spot_value_equity_minute(self):
trading_calendar = self.trading_calendars[Equity]
asset = self.asset_finder.retrieve_asset(1)
dts = trading_calendar.minutes_for_session(self.trading_days[2])
# Case: Get data on exact dt.
dt = dts[1]
expected = OrderedDict({
'open': 103.5,
'high': 103.9,
'low': 103.1,
'close': 103.3,
'volume': 1003,
'price': 103.3
})
result = [self.data_portal.get_spot_value(asset,
field,
dt,
'minute')
for field in expected.keys()]
assert_almost_equal(array(list(expected.values())), result)
# Case: Get data on empty dt, return nan or most recent data for price.
dt = dts[100]
expected = OrderedDict({
'open': nan,
'high': nan,
'low': nan,
'close': nan,
'volume': 0,
'price': 101.3
})
result = [self.data_portal.get_spot_value(asset,
field,
dt,
'minute')
for field in expected.keys()]
assert_almost_equal(array(list(expected.values())), result)
def test_get_spot_value_future_minute(self):
trading_calendar = self.trading_calendars['CME']
asset = self.asset_finder.retrieve_asset(10000)
dts = trading_calendar.minutes_for_session(self.trading_days[3])
# Case: Get data on exact dt.
dt = dts[1]
expected = OrderedDict({
'open': 203.5,
'high': 203.9,
'low': 203.1,
'close': 203.3,
'volume': 2003,
'price': 203.3
})
result = [self.data_portal.get_spot_value(asset,
field,
dt,
'minute')
for field in expected.keys()]
assert_almost_equal(array(list(expected.values())), result)
# Case: Get data on empty dt, return nan or most recent data for price.
dt = dts[100]
expected = OrderedDict({
'open': nan,
'high': nan,
'low': nan,
'close': nan,
'volume': 0,
'price': 201.3
})
result = [self.data_portal.get_spot_value(asset,
field,
dt,
'minute')
for field in expected.keys()]
assert_almost_equal(array(list(expected.values())), result)
def test_bar_count_for_simple_transforms(self):
# July 2015
# Su Mo Tu We Th Fr Sa
# 1 2 3 4
# 5 6 7 8 9 10 11
# 12 13 14 15 16 17 18
# 19 20 21 22 23 24 25
# 26 27 28 29 30 31
# half an hour into july 9, getting a 4-"day" window should get us
# all the minutes of 7/6, 7/7, 7/8, and 31 minutes of 7/9
july_9_dt = self.trading_calendar.open_and_close_for_session(
pd.Timestamp("2015-07-09", tz='UTC')
)[0] + Timedelta("30 minutes")
self.assertEqual(
(3 * 390) + 31,
self.data_portal._get_minute_count_for_transform(july_9_dt, 4)
)
# November 2015
# Su Mo Tu We Th Fr Sa
# 1 2 3 4 5 6 7
# 8 9 10 11 12 13 14
# 15 16 17 18 19 20 21
# 22 23 24 25 26 27 28
# 29 30
# nov 26th closed
# nov 27th was an early close
# half an hour into nov 30, getting a 4-"day" window should get us
# all the minutes of 11/24, 11/25, 11/27 (half day!), and 31 minutes
# of 11/30
nov_30_dt = self.trading_calendar.open_and_close_for_session(
pd.Timestamp("2015-11-30", tz='UTC')
)[0] + Timedelta("30 minutes")
self.assertEqual(
390 + 390 + 210 + 31,
self.data_portal._get_minute_count_for_transform(nov_30_dt, 4)
)
def test_get_last_traded_dt_minute(self):
minutes = self.nyse_calendar.minutes_for_session(
self.trading_days[2])
equity = self.asset_finder.retrieve_asset(1)
result = self.data_portal.get_last_traded_dt(equity,
minutes[3],
'minute')
self.assertEqual(minutes[3], result,
"Asset 1 had a trade on third minute, so should "
"return that as the last trade on that dt.")
result = self.data_portal.get_last_traded_dt(equity,
minutes[5],
'minute')
self.assertEqual(minutes[4], result,
"Asset 1 had a trade on fourth minute, so should "
"return that as the last trade on the fifth.")
future = self.asset_finder.retrieve_asset(10000)
calendar = self.trading_calendars[future.exchange]
minutes = calendar.minutes_for_session(self.trading_days[3])
result = self.data_portal.get_last_traded_dt(future,
minutes[3],
'minute')
self.assertEqual(minutes[3], result,
"Asset 10000 had a trade on the third minute, so "
"return that as the last trade on that dt.")
result = self.data_portal.get_last_traded_dt(future,
minutes[5],
'minute')
self.assertEqual(minutes[4], result,
"Asset 10000 had a trade on fourth minute, so should "
"return that as the last trade on the fifth.")
class TestDataPortal(DataPortalTestBase):
DATA_PORTAL_LAST_AVAILABLE_SESSION = None
DATA_PORTAL_LAST_AVAILABLE_MINUTE = None
class TestDataPortalExplicitLastAvailable(DataPortalTestBase):
DATA_PORTAL_LAST_AVAILABLE_SESSION = alias('START_DATE')
DATA_PORTAL_LAST_AVAILABLE_MINUTE = alias('END_DATE')