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catalyst/tests/data/test_minute_bars.py
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Joe Jevnik 59c8e371a2 ENH: Updates the cli, data bundles and extensions. 
Adds the data bundle concept which makes it easy for users to register
loading functions to build out minute and daily data along with an
assets db and adjustments db. By default we have provided a `quandl`
bundle which pulls from the public domain WIKI dataset. Users may
register new bundles by decorating an ingest function with
`zipline.data.bundles.register(<name>)`. This also provides a
`yahoo_equities` function for creating an ingestion function that will
load a static set of assets from yahoo.

The cli is now structured as a couple of subcommands and has been
changed to `python -m zipline`. The old behavior of `run_algo.py` has
been moved to the `run` subcommand. This is almost entirely the same
except that it now takes the name of the data bundle to use, defaulting
to `quandl`.

The next subcommand is `ingest` which takes the name of
a data bundle to ingest. This will run the loading machinery and write
the data to a specified location that `run` can find.

There is also a `clean` subcommand which deletes the data that was
written with `ingest`.

Extensions have also been added to zipline. This is an experimental
feature where users can provide an extra set of python files to run at
the start of the process. These can be used to configure aspects of
zipline. Right now the only thing that is supported in an extension file
is the registration of a new data bundle.
2016-05-03 18:38:24 -04:00

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#
# 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 datetime import timedelta
import os
from unittest import TestCase
from numpy import (
arange,
array,
int64,
float64,
full,
nan,
transpose,
zeros,
)
from numpy.testing import assert_almost_equal, assert_array_equal
from pandas import (
DataFrame,
DatetimeIndex,
Timestamp,
Timedelta,
NaT,
date_range,
)
from testfixtures import TempDirectory
from zipline.data.minute_bars import (
BcolzMinuteBarWriter,
BcolzMinuteBarReader,
BcolzMinuteOverlappingData,
US_EQUITIES_MINUTES_PER_DAY,
BcolzMinuteWriterColumnMismatch
)
from zipline.finance.trading import TradingEnvironment
# Calendar is set to cover several half days, to check a case where half
# days would be read out of order in cases of windows which spanned over
# multiple half days.
TEST_CALENDAR_START = Timestamp('2014-06-02', tz='UTC')
TEST_CALENDAR_STOP = Timestamp('2015-12-31', tz='UTC')
class BcolzMinuteBarTestCase(TestCase):
@classmethod
def setUpClass(cls):
cls.env = TradingEnvironment()
all_market_opens = cls.env.open_and_closes.market_open
all_market_closes = cls.env.open_and_closes.market_close
indexer = all_market_opens.index.slice_indexer(
start=TEST_CALENDAR_START,
end=TEST_CALENDAR_STOP
)
cls.market_opens = all_market_opens[indexer]
cls.market_closes = all_market_closes[indexer]
cls.test_calendar_start = cls.market_opens.index[0]
cls.test_calendar_stop = cls.market_opens.index[-1]
def setUp(self):
self.dir_ = TempDirectory()
self.dir_.create()
self.dest = self.dir_.getpath('minute_bars')
os.makedirs(self.dest)
self.writer = BcolzMinuteBarWriter(
TEST_CALENDAR_START,
self.dest,
self.market_opens,
self.market_closes,
US_EQUITIES_MINUTES_PER_DAY,
)
self.reader = BcolzMinuteBarReader(self.dest)
def tearDown(self):
self.dir_.cleanup()
def test_write_one_ohlcv(self):
minute = self.market_opens[self.test_calendar_start]
sid = 1
data = DataFrame(
data={
'open': [10.0],
'high': [20.0],
'low': [30.0],
'close': [40.0],
'volume': [50.0]
},
index=[minute])
self.writer.write_sid(sid, data)
open_price = self.reader.get_value(sid, minute, 'open')
self.assertEquals(10.0, open_price)
high_price = self.reader.get_value(sid, minute, 'high')
self.assertEquals(20.0, high_price)
low_price = self.reader.get_value(sid, minute, 'low')
self.assertEquals(30.0, low_price)
close_price = self.reader.get_value(sid, minute, 'close')
self.assertEquals(40.0, close_price)
volume_price = self.reader.get_value(sid, minute, 'volume')
self.assertEquals(50.0, volume_price)
def test_write_two_bars(self):
minute_0 = self.market_opens[self.test_calendar_start]
minute_1 = minute_0 + timedelta(minutes=1)
sid = 1
data = DataFrame(
data={
'open': [10.0, 11.0],
'high': [20.0, 21.0],
'low': [30.0, 31.0],
'close': [40.0, 41.0],
'volume': [50.0, 51.0]
},
index=[minute_0, minute_1])
self.writer.write_sid(sid, data)
open_price = self.reader.get_value(sid, minute_0, 'open')
self.assertEquals(10.0, open_price)
high_price = self.reader.get_value(sid, minute_0, 'high')
self.assertEquals(20.0, high_price)
low_price = self.reader.get_value(sid, minute_0, 'low')
self.assertEquals(30.0, low_price)
close_price = self.reader.get_value(sid, minute_0, 'close')
self.assertEquals(40.0, close_price)
volume_price = self.reader.get_value(sid, minute_0, 'volume')
self.assertEquals(50.0, volume_price)
open_price = self.reader.get_value(sid, minute_1, 'open')
self.assertEquals(11.0, open_price)
high_price = self.reader.get_value(sid, minute_1, 'high')
self.assertEquals(21.0, high_price)
low_price = self.reader.get_value(sid, minute_1, 'low')
self.assertEquals(31.0, low_price)
close_price = self.reader.get_value(sid, minute_1, 'close')
self.assertEquals(41.0, close_price)
volume_price = self.reader.get_value(sid, minute_1, 'volume')
self.assertEquals(51.0, volume_price)
def test_write_on_second_day(self):
second_day = self.test_calendar_start + 1
minute = self.market_opens[second_day]
sid = 1
data = DataFrame(
data={
'open': [10.0],
'high': [20.0],
'low': [30.0],
'close': [40.0],
'volume': [50.0]
},
index=[minute])
self.writer.write_sid(sid, data)
open_price = self.reader.get_value(sid, minute, 'open')
self.assertEquals(10.0, open_price)
high_price = self.reader.get_value(sid, minute, 'high')
self.assertEquals(20.0, high_price)
low_price = self.reader.get_value(sid, minute, 'low')
self.assertEquals(30.0, low_price)
close_price = self.reader.get_value(sid, minute, 'close')
self.assertEquals(40.0, close_price)
volume_price = self.reader.get_value(sid, minute, 'volume')
self.assertEquals(50.0, volume_price)
def test_write_empty(self):
minute = self.market_opens[self.test_calendar_start]
sid = 1
data = DataFrame(
data={
'open': [0],
'high': [0],
'low': [0],
'close': [0],
'volume': [0]
},
index=[minute])
self.writer.write_sid(sid, data)
open_price = self.reader.get_value(sid, minute, 'open')
assert_almost_equal(nan, open_price)
high_price = self.reader.get_value(sid, minute, 'high')
assert_almost_equal(nan, high_price)
low_price = self.reader.get_value(sid, minute, 'low')
assert_almost_equal(nan, low_price)
close_price = self.reader.get_value(sid, minute, 'close')
assert_almost_equal(nan, close_price)
volume_price = self.reader.get_value(sid, minute, 'volume')
assert_almost_equal(0, volume_price)
def test_write_on_multiple_days(self):
tds = self.market_opens.index
days = tds[tds.slice_indexer(
start=self.test_calendar_start + 1,
end=self.test_calendar_start + 3
)]
minutes = DatetimeIndex([
self.market_opens[days[0]] + timedelta(minutes=60),
self.market_opens[days[1]] + timedelta(minutes=120),
])
sid = 1
data = DataFrame(
data={
'open': [10.0, 11.0],
'high': [20.0, 21.0],
'low': [30.0, 31.0],
'close': [40.0, 41.0],
'volume': [50.0, 51.0]
},
index=minutes)
self.writer.write_sid(sid, data)
minute = minutes[0]
open_price = self.reader.get_value(sid, minute, 'open')
self.assertEquals(10.0, open_price)
high_price = self.reader.get_value(sid, minute, 'high')
self.assertEquals(20.0, high_price)
low_price = self.reader.get_value(sid, minute, 'low')
self.assertEquals(30.0, low_price)
close_price = self.reader.get_value(sid, minute, 'close')
self.assertEquals(40.0, close_price)
volume_price = self.reader.get_value(sid, minute, 'volume')
self.assertEquals(50.0, volume_price)
minute = minutes[1]
open_price = self.reader.get_value(sid, minute, 'open')
self.assertEquals(11.0, open_price)
high_price = self.reader.get_value(sid, minute, 'high')
self.assertEquals(21.0, high_price)
low_price = self.reader.get_value(sid, minute, 'low')
self.assertEquals(31.0, low_price)
close_price = self.reader.get_value(sid, minute, 'close')
self.assertEquals(41.0, close_price)
volume_price = self.reader.get_value(sid, minute, 'volume')
self.assertEquals(51.0, volume_price)
def test_no_overwrite(self):
minute = self.market_opens[TEST_CALENDAR_START]
sid = 1
data = DataFrame(
data={
'open': [10.0],
'high': [20.0],
'low': [30.0],
'close': [40.0],
'volume': [50.0]
},
index=[minute])
self.writer.write_sid(sid, data)
with self.assertRaises(BcolzMinuteOverlappingData):
self.writer.write_sid(sid, data)
def test_write_multiple_sids(self):
"""
Test writing multiple sids.
Tests both that the data is written to the correct sid, as well as
ensuring that the logic for creating the subdirectory path to each sid
does not cause issues from attempts to recreate existing paths.
(Calling out this coverage, because an assertion of that logic does not
show up in the test itself, but is exercised by the act of attempting
to write two consecutive sids, which would be written to the same
containing directory, `00/00/000001.bcolz` and `00/00/000002.bcolz)
Before applying a check to make sure the path writing did not
re-attempt directory creation an OSError like the following would
occur:
```
OSError: [Errno 17] File exists: '/tmp/tmpR7yzzT/minute_bars/00/00'
```
"""
minute = self.market_opens[TEST_CALENDAR_START]
sids = [1, 2]
data = DataFrame(
data={
'open': [15.0],
'high': [17.0],
'low': [11.0],
'close': [15.0],
'volume': [100.0]
},
index=[minute])
self.writer.write_sid(sids[0], data)
data = DataFrame(
data={
'open': [25.0],
'high': [27.0],
'low': [21.0],
'close': [25.0],
'volume': [200.0]
},
index=[minute])
self.writer.write_sid(sids[1], data)
sid = sids[0]
open_price = self.reader.get_value(sid, minute, 'open')
self.assertEquals(15.0, open_price)
high_price = self.reader.get_value(sid, minute, 'high')
self.assertEquals(17.0, high_price)
low_price = self.reader.get_value(sid, minute, 'low')
self.assertEquals(11.0, low_price)
close_price = self.reader.get_value(sid, minute, 'close')
self.assertEquals(15.0, close_price)
volume_price = self.reader.get_value(sid, minute, 'volume')
self.assertEquals(100.0, volume_price)
sid = sids[1]
open_price = self.reader.get_value(sid, minute, 'open')
self.assertEquals(25.0, open_price)
high_price = self.reader.get_value(sid, minute, 'high')
self.assertEquals(27.0, high_price)
low_price = self.reader.get_value(sid, minute, 'low')
self.assertEquals(21.0, low_price)
close_price = self.reader.get_value(sid, minute, 'close')
self.assertEquals(25.0, close_price)
volume_price = self.reader.get_value(sid, minute, 'volume')
self.assertEquals(200.0, volume_price)
def test_pad_data(self):
"""
Test writing empty data.
"""
sid = 1
last_date = self.writer.last_date_in_output_for_sid(sid)
self.assertIs(last_date, NaT)
self.writer.pad(sid, TEST_CALENDAR_START)
last_date = self.writer.last_date_in_output_for_sid(sid)
self.assertEqual(last_date, TEST_CALENDAR_START)
freq = self.market_opens.index.freq
minute = self.market_opens[TEST_CALENDAR_START + freq]
data = DataFrame(
data={
'open': [15.0],
'high': [17.0],
'low': [11.0],
'close': [15.0],
'volume': [100.0]
},
index=[minute])
self.writer.write_sid(sid, data)
open_price = self.reader.get_value(sid, minute, 'open')
self.assertEquals(15.0, open_price)
high_price = self.reader.get_value(sid, minute, 'high')
self.assertEquals(17.0, high_price)
low_price = self.reader.get_value(sid, minute, 'low')
self.assertEquals(11.0, low_price)
close_price = self.reader.get_value(sid, minute, 'close')
self.assertEquals(15.0, close_price)
volume_price = self.reader.get_value(sid, minute, 'volume')
self.assertEquals(100.0, volume_price)
def test_nans(self):
"""
Test writing empty data.
"""
sid = 1
last_date = self.writer.last_date_in_output_for_sid(sid)
self.assertIs(last_date, NaT)
self.writer.pad(sid, TEST_CALENDAR_START)
last_date = self.writer.last_date_in_output_for_sid(sid)
self.assertEqual(last_date, TEST_CALENDAR_START)
freq = self.market_opens.index.freq
minute = self.market_opens[TEST_CALENDAR_START + freq]
minutes = date_range(minute, periods=9, freq='min')
data = DataFrame(
data={
'open': full(9, nan),
'high': full(9, nan),
'low': full(9, nan),
'close': full(9, nan),
'volume': full(9, 0),
},
index=[minutes])
self.writer.write_sid(sid, data)
fields = ['open', 'high', 'low', 'close', 'volume']
ohlcv_window = list(map(transpose, self.reader.load_raw_arrays(
fields, minutes[0], minutes[-1], [sid],
)))
for i, field in enumerate(fields):
if field != 'volume':
assert_array_equal(full(9, nan), ohlcv_window[i][0])
else:
assert_array_equal(zeros(9), ohlcv_window[i][0])
def test_differing_nans(self):
"""
Also test nans of differing values/construction.
"""
sid = 1
last_date = self.writer.last_date_in_output_for_sid(sid)
self.assertIs(last_date, NaT)
self.writer.pad(sid, TEST_CALENDAR_START)
last_date = self.writer.last_date_in_output_for_sid(sid)
self.assertEqual(last_date, TEST_CALENDAR_START)
freq = self.market_opens.index.freq
minute = self.market_opens[TEST_CALENDAR_START + freq]
minutes = date_range(minute, periods=9, freq='min')
data = DataFrame(
data={
'open': ((0b11111111111 << 52) + arange(1, 10, dtype=int64)).
view(float64),
'high': ((0b11111111111 << 52) + arange(11, 20, dtype=int64)).
view(float64),
'low': ((0b11111111111 << 52) + arange(21, 30, dtype=int64)).
view(float64),
'close': ((0b11111111111 << 52) + arange(31, 40, dtype=int64)).
view(float64),
'volume': full(9, 0),
},
index=[minutes])
self.writer.write_sid(sid, data)
fields = ['open', 'high', 'low', 'close', 'volume']
ohlcv_window = list(map(transpose, self.reader.load_raw_arrays(
fields, minutes[0], minutes[-1], [sid],
)))
for i, field in enumerate(fields):
if field != 'volume':
assert_array_equal(full(9, nan), ohlcv_window[i][0])
else:
assert_array_equal(zeros(9), ohlcv_window[i][0])
def test_write_cols(self):
minute_0 = self.market_opens[self.test_calendar_start]
minute_1 = minute_0 + timedelta(minutes=1)
sid = 1
cols = {
'open': array([10.0, 11.0]),
'high': array([20.0, 21.0]),
'low': array([30.0, 31.0]),
'close': array([40.0, 41.0]),
'volume': array([50.0, 51.0])
}
dts = array([minute_0, minute_1], dtype='datetime64[s]')
self.writer.write_cols(sid, dts, cols)
open_price = self.reader.get_value(sid, minute_0, 'open')
self.assertEquals(10.0, open_price)
high_price = self.reader.get_value(sid, minute_0, 'high')
self.assertEquals(20.0, high_price)
low_price = self.reader.get_value(sid, minute_0, 'low')
self.assertEquals(30.0, low_price)
close_price = self.reader.get_value(sid, minute_0, 'close')
self.assertEquals(40.0, close_price)
volume_price = self.reader.get_value(sid, minute_0, 'volume')
self.assertEquals(50.0, volume_price)
open_price = self.reader.get_value(sid, minute_1, 'open')
self.assertEquals(11.0, open_price)
high_price = self.reader.get_value(sid, minute_1, 'high')
self.assertEquals(21.0, high_price)
low_price = self.reader.get_value(sid, minute_1, 'low')
self.assertEquals(31.0, low_price)
close_price = self.reader.get_value(sid, minute_1, 'close')
self.assertEquals(41.0, close_price)
volume_price = self.reader.get_value(sid, minute_1, 'volume')
self.assertEquals(51.0, volume_price)
def test_write_cols_mismatch_length(self):
dts = date_range(self.market_opens[self.test_calendar_start],
periods=2, freq='min').asi8.astype('datetime64[s]')
sid = 1
cols = {
'open': array([10.0, 11.0, 12.0]),
'high': array([20.0, 21.0]),
'low': array([30.0, 31.0, 33.0, 34.0]),
'close': array([40.0, 41.0]),
'volume': array([50.0, 51.0, 52.0])
}
with self.assertRaises(BcolzMinuteWriterColumnMismatch):
self.writer.write_cols(sid, dts, cols)
def test_unadjusted_minutes(self):
"""
Test unadjusted minutes.
"""
start_minute = self.market_opens[TEST_CALENDAR_START]
minutes = [start_minute,
start_minute + Timedelta('1 min'),
start_minute + Timedelta('2 min')]
sids = [1, 2]
data_1 = DataFrame(
data={
'open': [15.0, nan, 15.1],
'high': [17.0, nan, 17.1],
'low': [11.0, nan, 11.1],
'close': [14.0, nan, 14.1],
'volume': [1000, 0, 1001]
},
index=minutes)
self.writer.write_sid(sids[0], data_1)
data_2 = DataFrame(
data={
'open': [25.0, nan, 25.1],
'high': [27.0, nan, 27.1],
'low': [21.0, nan, 21.1],
'close': [24.0, nan, 24.1],
'volume': [2000, 0, 2001]
},
index=minutes)
self.writer.write_sid(sids[1], data_2)
reader = BcolzMinuteBarReader(self.dest)
columns = ['open', 'high', 'low', 'close', 'volume']
sids = [sids[0], sids[1]]
arrays = list(map(transpose, reader.load_raw_arrays(
columns, minutes[0], minutes[-1], sids,
)))
data = {sids[0]: data_1, sids[1]: data_2}
for i, col in enumerate(columns):
for j, sid in enumerate(sids):
assert_almost_equal(data[sid][col], arrays[i][j])
def test_unadjusted_minutes_early_close(self):
"""
Test unadjusted minute window, ensuring that early closes are filtered
out.
"""
day_before_thanksgiving = Timestamp('2015-11-25', tz='UTC')
xmas_eve = Timestamp('2015-12-24', tz='UTC')
market_day_after_xmas = Timestamp('2015-12-28', tz='UTC')
minutes = [self.market_closes[day_before_thanksgiving] -
Timedelta('2 min'),
self.market_closes[xmas_eve] - Timedelta('1 min'),
self.market_opens[market_day_after_xmas] +
Timedelta('1 min')]
sids = [1, 2]
data_1 = DataFrame(
data={
'open': [
15.0, 15.1, 15.2],
'high': [17.0, 17.1, 17.2],
'low': [11.0, 11.1, 11.3],
'close': [14.0, 14.1, 14.2],
'volume': [1000, 1001, 1002],
},
index=minutes)
self.writer.write_sid(sids[0], data_1)
data_2 = DataFrame(
data={
'open': [25.0, 25.1, 25.2],
'high': [27.0, 27.1, 27.2],
'low': [21.0, 21.1, 21.2],
'close': [24.0, 24.1, 24.2],
'volume': [2000, 2001, 2002],
},
index=minutes)
self.writer.write_sid(sids[1], data_2)
reader = BcolzMinuteBarReader(self.dest)
columns = ['open', 'high', 'low', 'close', 'volume']
sids = [sids[0], sids[1]]
arrays = list(map(transpose, reader.load_raw_arrays(
columns, minutes[0], minutes[-1], sids,
)))
data = {sids[0]: data_1, sids[1]: data_2}
start_minute_loc = self.env.market_minutes.get_loc(minutes[0])
minute_locs = [self.env.market_minutes.get_loc(minute) -
start_minute_loc
for minute in minutes]
for i, col in enumerate(columns):
for j, sid in enumerate(sids):
assert_almost_equal(data[sid].loc[minutes, col],
arrays[i][j][minute_locs])
def test_adjust_non_trading_minutes(self):
start_day = Timestamp('2015-06-01', tz='UTC')
end_day = Timestamp('2015-06-02', tz='UTC')
sid = 1
cols = {
'open': arange(1, 781),
'high': arange(1, 781),
'low': arange(1, 781),
'close': arange(1, 781),
'volume': arange(1, 781)
}
dts = array(self.env.minutes_for_days_in_range(start_day, end_day))
self.writer.write_cols(sid, dts, cols)
self.assertEqual(
self.reader.get_value(
sid,
Timestamp('2015-06-01 20:00:00', tz='UTC'),
'open'),
390)
self.assertEqual(
self.reader.get_value(
sid,
Timestamp('2015-06-02 20:00:00', tz='UTC'),
'open'),
780)
self.assertEqual(
self.reader.get_value(
sid,
Timestamp('2015-06-02', tz='UTC'),
'open'),
390)
self.assertEqual(
self.reader.get_value(
sid,
Timestamp('2015-06-02 20:01:00', tz='UTC'),
'open'),
780)
def test_adjust_non_trading_minutes_half_days(self):
# half day
start_day = Timestamp('2015-11-27', tz='UTC')
end_day = Timestamp('2015-11-30', tz='UTC')
sid = 1
cols = {
'open': arange(1, 601),
'high': arange(1, 601),
'low': arange(1, 601),
'close': arange(1, 601),
'volume': arange(1, 601)
}
dts = array(self.env.minutes_for_days_in_range(start_day, end_day))
self.writer.write_cols(sid, dts, cols)
self.assertEqual(
self.reader.get_value(
sid,
Timestamp('2015-11-27 18:00:00', tz='UTC'),
'open'),
210)
self.assertEqual(
self.reader.get_value(
sid,
Timestamp('2015-11-30 21:00:00', tz='UTC'),
'open'),
600)
self.assertEqual(
self.reader.get_value(
sid,
Timestamp('2015-11-27 18:01:00', tz='UTC'),
'open'),
210)
self.assertEqual(
self.reader.get_value(
sid,
Timestamp('2015-11-30', tz='UTC'),
'open'),
210)
self.assertEqual(
self.reader.get_value(
sid,
Timestamp('2015-11-30 21:01:00', tz='UTC'),
'open'),
600)
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