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.trading_calendar.all_minutes.get_loc(minutes[0])
minute_locs = [
self.trading_calendar.all_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_truncate_between_data_points(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)
# Open a new writer to cover `open` method, also truncating only
# applies to an existing directory.
writer = BcolzMinuteBarWriter.open(self.dest)
# Truncate to first day with data.
writer.truncate(days[0])
# Refresh the reader since truncate update the metadata.
self.reader = BcolzMinuteBarReader(self.dest)
self.assertEqual(self.writer.last_date_in_output_for_sid(sid), days[0])
cal = self.trading_calendar
_, last_close = cal.open_and_close_for_session(days[0])
self.assertEqual(self.reader.last_available_dt, last_close)
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)
def test_minute_updates(self):
"""
Test minute updates.
"""
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)
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)
frames = {1: data_1, 2: data_2}
update_path = self.instance_tmpdir.getpath('updates.h5')
update_writer = H5MinuteBarUpdateWriter(update_path)
update_writer.write(frames)
update_reader = H5MinuteBarUpdateReader(update_path)
self.writer.write(update_reader.read(minutes, sids))
# Refresh the reader since truncate update the metadata.
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 __init__(self, exchange=None, catalyst_root=None):
if exchange is None:
raise ValueError('You should provide the exchange for which you')
if catalyst_root is None:
home = expanduser("~")
self.catalyst_root = home + "\\.catalyst"
else:
self.catalyst_root = catalyst_root
self.exchange = exchange
self.path = self.catalyst_root + "\\data\\exchanges\\" + exchange + "\\minute_bundle"
self.reader = BcolzMinuteBarReader(self.path)
def init_instance_fixtures(self):
super(BcolzMinuteBarTestCase, self).init_instance_fixtures()
self.dest = self.instance_tmpdir.getpath('minute_bars')
os.makedirs(self.dest)
self.writer = BcolzMinuteBarWriter(
self.dest,
self.trading_calendar,
TEST_CALENDAR_START,
TEST_CALENDAR_STOP,
US_EQUITIES_MINUTES_PER_DAY,
)
self.reader = BcolzMinuteBarReader(self.dest)
def test_minute_updates(self):
"""
Test minute updates.
"""
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)
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)
frames = {1: data_1, 2: data_2}
update_path = self.instance_tmpdir.getpath('updates.h5')
update_writer = H5MinuteBarUpdateWriter(update_path)
update_writer.write(frames)
update_reader = H5MinuteBarUpdateReader(update_path)
self.writer.write(update_reader.read(minutes, sids))
# Refresh the reader since truncate update the metadata.
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(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_truncate_between_data_points(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)
# Open a new writer to cover `open` method, also truncating only
# applies to an existing directory.
writer = BcolzMinuteBarWriter.open(self.dest)
# Truncate to first day with data.
writer.truncate(days[0])
# Refresh the reader since truncate update the metadata.
self.reader = BcolzMinuteBarReader(self.dest)
self.assertEqual(self.writer.last_date_in_output_for_sid(sid), days[0])
cal = self.trading_calendar
_, last_close = cal.open_and_close_for_session(days[0])
self.assertEqual(self.reader.last_available_dt, last_close)
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)
def create_data_portal(asset_finder, tempdir, sim_params, sids,
trading_calendar, adjustment_reader=None):
if sim_params.data_frequency == "daily":
daily_path = write_daily_data(tempdir, sim_params, sids,
trading_calendar)
equity_daily_reader = BcolzDailyBarReader(daily_path)
return DataPortal(
asset_finder, trading_calendar,
first_trading_day=equity_daily_reader.first_trading_day,
equity_daily_reader=equity_daily_reader,
adjustment_reader=adjustment_reader
)
else:
minutes = trading_calendar.minutes_in_range(
sim_params.first_open,
sim_params.last_close
)
minute_path = write_minute_data(trading_calendar, tempdir, minutes,
sids)
equity_minute_reader = BcolzMinuteBarReader(minute_path)
return DataPortal(
asset_finder, trading_calendar,
first_trading_day=equity_minute_reader.first_trading_day,
equity_minute_reader=equity_minute_reader,
adjustment_reader=adjustment_reader
)
def test_append_on_new_day(self):
sid = 1
ohlcv = {
'open': [2.0],
'high': [3.0],
'low': [1.0],
'close': [2.0],
'volume': [10.0]
}
dt = self.market_opens[TEST_CALENDAR_STOP]
data = DataFrame(
data=ohlcv,
index=[dt])
self.writer.write_sid(sid, data)
# Open a new writer to cover `open` method, also a common usage
# of appending new days will be writing to an existing directory.
cday = self.trading_calendar.schedule.index.freq
new_end_session = TEST_CALENDAR_STOP + cday
writer = BcolzMinuteBarWriter.open(self.dest, new_end_session)
next_day_minute = dt + cday
new_data = DataFrame(
data=ohlcv,
index=[next_day_minute])
writer.write_sid(sid, new_data)
# Get a new reader to test updated calendar.
reader = BcolzMinuteBarReader(self.dest)
second_minute = dt + Timedelta(minutes=1)
# The second minute should have been padded with zeros
for col in ('open', 'high', 'low', 'close'):
assert_almost_equal(
nan, reader.get_value(sid, second_minute, col)
)
self.assertEqual(
0, reader.get_value(sid, second_minute, 'volume')
)
# The next day minute should have data.
for col in ('open', 'high', 'low', 'close', 'volume'):
assert_almost_equal(
ohlcv[col], reader.get_value(sid, next_day_minute, col)
)
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 init_instance_fixtures(self):
super(BcolzMinuteBarTestCase, self).init_instance_fixtures()
self.dest = self.instance_tmpdir.getpath('minute_bars')
os.makedirs(self.dest)
self.writer = BcolzMinuteBarWriter(
self.dest,
self.trading_calendar,
TEST_CALENDAR_START,
TEST_CALENDAR_STOP,
US_EQUITIES_MINUTES_PER_DAY,
)
self.reader = BcolzMinuteBarReader(self.dest)
def test_append_on_new_day(self):
sid = 1
ohlcv = {
'open': [2.0],
'high': [3.0],
'low': [1.0],
'close': [2.0],
'volume': [10.0]
}
dt = self.market_opens[TEST_CALENDAR_STOP]
data = DataFrame(data=ohlcv, index=[dt])
self.writer.write_sid(sid, data)
# Open a new writer to cover `open` method, also a common usage
# of appending new days will be writing to an existing directory.
cday = self.trading_calendar.schedule.index.freq
new_end_session = TEST_CALENDAR_STOP + cday
writer = BcolzMinuteBarWriter.open(self.dest, new_end_session)
next_day_minute = dt + cday
new_data = DataFrame(data=ohlcv, index=[next_day_minute])
writer.write_sid(sid, new_data)
# Get a new reader to test updated calendar.
reader = BcolzMinuteBarReader(self.dest)
second_minute = dt + Timedelta(minutes=1)
# The second minute should have been padded with zeros
for col in ('open', 'high', 'low', 'close'):
assert_almost_equal(nan, reader.get_value(sid, second_minute, col))
self.assertEqual(0, reader.get_value(sid, second_minute, 'volume'))
# The next day minute should have data.
for col in ('open', 'high', 'low', 'close', 'volume'):
assert_almost_equal(ohlcv[col],
reader.get_value(sid, next_day_minute, col))
def test_truncate_all_data_points(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)
# Truncate to first day in the calendar, a day before the first
# day with minute data.
self.writer.truncate(self.test_calendar_start)
# Refresh the reader since truncate update the metadata.
self.reader = BcolzMinuteBarReader(self.dest)
self.assertEqual(
self.writer.last_date_in_output_for_sid(sid),
self.test_calendar_start,
)
cal = self.trading_calendar
_, last_close = cal.open_and_close_for_session(
self.test_calendar_start)
self.assertEqual(self.reader.last_available_dt, last_close)
def _create_minute_writer(self):
root = get_exchange_minute_writer_root(self.exchange.name)
filename = os.path.join(root, 'metadata.json')
if os.path.isfile(filename):
writer = BcolzMinuteBarWriter.open(root,
self.sim_params.end_session)
else:
writer = BcolzMinuteBarWriter(
rootdir=root,
calendar=self.trading_calendar,
minutes_per_day=1440,
start_session=self.sim_params.start_session,
end_session=self.sim_params.end_session,
write_metadata=True)
self.exchange.minute_writer = writer
self.exchange.minute_reader = BcolzMinuteBarReader(root)
def test_truncate_all_data_points(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)
# Truncate to first day in the calendar, a day before the first
# day with minute data.
self.writer.truncate(self.test_calendar_start)
# Refresh the reader since truncate update the metadata.
self.reader = BcolzMinuteBarReader(self.dest)
self.assertEqual(
self.writer.last_date_in_output_for_sid(sid),
self.test_calendar_start,
)
cal = self.trading_calendar
_, last_close = cal.open_and_close_for_session(
self.test_calendar_start)
self.assertEqual(self.reader.last_available_dt, last_close)
def test_write_one_ohlcv_with_ratios(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],
)
# Create a new writer with `ohlc_ratios_per_sid` defined.
writer_with_ratios = BcolzMinuteBarWriter(
self.dest,
self.trading_calendar,
TEST_CALENDAR_START,
TEST_CALENDAR_STOP,
US_EQUITIES_MINUTES_PER_DAY,
ohlc_ratios_per_sid={sid: 25},
)
writer_with_ratios.write_sid(sid, data)
reader = BcolzMinuteBarReader(self.dest)
open_price = reader.get_value(sid, minute, 'open')
self.assertEquals(10.0, open_price)
high_price = reader.get_value(sid, minute, 'high')
self.assertEquals(20.0, high_price)
low_price = reader.get_value(sid, minute, 'low')
self.assertEquals(30.0, low_price)
close_price = reader.get_value(sid, minute, 'close')
self.assertEquals(40.0, close_price)
volume_price = reader.get_value(sid, minute, 'volume')
self.assertEquals(50.0, volume_price)
def test_write_one_ohlcv_with_ratios(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],
)
# Create a new writer with `ohlc_ratios_per_sid` defined.
writer_with_ratios = BcolzMinuteBarWriter(
self.dest,
self.trading_calendar,
TEST_CALENDAR_START,
TEST_CALENDAR_STOP,
US_EQUITIES_MINUTES_PER_DAY,
ohlc_ratios_per_sid={sid: 25},
)
writer_with_ratios.write_sid(sid, data)
reader = BcolzMinuteBarReader(self.dest)
open_price = reader.get_value(sid, minute, 'open')
self.assertEquals(10.0, open_price)
high_price = reader.get_value(sid, minute, 'high')
self.assertEquals(20.0, high_price)
low_price = reader.get_value(sid, minute, 'low')
self.assertEquals(30.0, low_price)
close_price = reader.get_value(sid, minute, 'close')
self.assertEquals(40.0, close_price)
volume_price = reader.get_value(sid, minute, 'volume')
self.assertEquals(50.0, volume_price)
def create_data_portal_from_trade_history(asset_finder, trading_calendar,
tempdir, sim_params, trades_by_sid):
if sim_params.data_frequency == "daily":
path = os.path.join(tempdir.path, "testdaily.bcolz")
writer = BcolzDailyBarWriter(
path, trading_calendar,
sim_params.start_session,
sim_params.end_session
)
writer.write(
trades_by_sid_to_dfs(trades_by_sid, sim_params.sessions),
)
equity_daily_reader = BcolzDailyBarReader(path)
return DataPortal(
asset_finder, trading_calendar,
first_trading_day=equity_daily_reader.first_trading_day,
daily_reader=equity_daily_reader,
)
else:
minutes = trading_calendar.minutes_in_range(
sim_params.first_open,
sim_params.last_close
)
length = len(minutes)
assets = {}
for sidint, trades in iteritems(trades_by_sid):
opens = np.zeros(length)
highs = np.zeros(length)
lows = np.zeros(length)
closes = np.zeros(length)
volumes = np.zeros(length)
for trade in trades:
# put them in the right place
idx = minutes.searchsorted(trade.dt)
opens[idx] = trade.open_price * 1000
highs[idx] = trade.high * 1000
lows[idx] = trade.low * 1000
closes[idx] = trade.close_price * 1000
volumes[idx] = trade.volume
assets[sidint] = pd.DataFrame({
"open": opens,
"high": highs,
"low": lows,
"close": closes,
"volume": volumes,
"dt": minutes
}).set_index("dt")
write_bcolz_minute_data(
trading_calendar,
sim_params.sessions,
tempdir.path,
assets
)
equity_minute_reader = BcolzMinuteBarReader(tempdir.path)
return DataPortal(
asset_finder, trading_calendar,
first_trading_day=equity_minute_reader.first_trading_day,
equity_minute_reader=equity_minute_reader,
)
class BcolzMinuteBarTestCase(WithTradingCalendars, WithAssetFinder,
WithInstanceTmpDir, ZiplineTestCase):
ASSET_FINDER_EQUITY_SIDS = 1, 2
@classmethod
def init_class_fixtures(cls):
super(BcolzMinuteBarTestCase, cls).init_class_fixtures()
cal = cls.trading_calendar.schedule.loc[
TEST_CALENDAR_START:TEST_CALENDAR_STOP]
cls.market_opens = cal.market_open
cls.market_closes = cal.market_close
cls.test_calendar_start = cls.market_opens.index[0]
cls.test_calendar_stop = cls.market_opens.index[-1]
def init_instance_fixtures(self):
super(BcolzMinuteBarTestCase, self).init_instance_fixtures()
self.dest = self.instance_tmpdir.getpath('minute_bars')
os.makedirs(self.dest)
self.writer = BcolzMinuteBarWriter(
self.dest,
self.trading_calendar,
TEST_CALENDAR_START,
TEST_CALENDAR_STOP,
US_EQUITIES_MINUTES_PER_DAY,
)
self.reader = BcolzMinuteBarReader(self.dest)
def test_version(self):
metadata = self.reader._get_metadata()
self.assertEquals(
metadata.version,
BcolzMinuteBarMetadata.FORMAT_VERSION,
)
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_one_ohlcv_with_ratios(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],
)
# Create a new writer with `ohlc_ratios_per_sid` defined.
writer_with_ratios = BcolzMinuteBarWriter(
self.dest,
self.trading_calendar,
TEST_CALENDAR_START,
TEST_CALENDAR_STOP,
US_EQUITIES_MINUTES_PER_DAY,
ohlc_ratios_per_sid={sid: 25},
)
writer_with_ratios.write_sid(sid, data)
reader = BcolzMinuteBarReader(self.dest)
open_price = reader.get_value(sid, minute, 'open')
self.assertEquals(10.0, open_price)
high_price = reader.get_value(sid, minute, 'high')
self.assertEquals(20.0, high_price)
low_price = reader.get_value(sid, minute, 'low')
self.assertEquals(30.0, low_price)
close_price = reader.get_value(sid, minute, 'close')
self.assertEquals(40.0, close_price)
volume_price = 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_append_to_same_day(self):
"""
Test writing data with the same date as existing data in our file.
"""
sid = 1
first_minute = self.market_opens[TEST_CALENDAR_START]
data = DataFrame(data={
'open': [10.0],
'high': [20.0],
'low': [30.0],
'close': [40.0],
'volume': [50.0]
},
index=[first_minute])
self.writer.write_sid(sid, data)
# Write data in the same day as the previous minute
second_minute = first_minute + Timedelta(minutes=1)
new_data = DataFrame(data={
'open': [5.0],
'high': [10.0],
'low': [3.0],
'close': [7.0],
'volume': [10.0]
},
index=[second_minute])
self.writer.write_sid(sid, new_data)
open_price = self.reader.get_value(sid, second_minute, 'open')
self.assertEquals(5.0, open_price)
high_price = self.reader.get_value(sid, second_minute, 'high')
self.assertEquals(10.0, high_price)
low_price = self.reader.get_value(sid, second_minute, 'low')
self.assertEquals(3.0, low_price)
close_price = self.reader.get_value(sid, second_minute, 'close')
self.assertEquals(7.0, close_price)
volume_price = self.reader.get_value(sid, second_minute, 'volume')
self.assertEquals(10.0, volume_price)
def test_append_on_new_day(self):
sid = 1
ohlcv = {
'open': [2.0],
'high': [3.0],
'low': [1.0],
'close': [2.0],
'volume': [10.0]
}
dt = self.market_opens[TEST_CALENDAR_STOP]
data = DataFrame(data=ohlcv, index=[dt])
self.writer.write_sid(sid, data)
# Open a new writer to cover `open` method, also a common usage
# of appending new days will be writing to an existing directory.
cday = self.trading_calendar.schedule.index.freq
new_end_session = TEST_CALENDAR_STOP + cday
writer = BcolzMinuteBarWriter.open(self.dest, new_end_session)
next_day_minute = dt + cday
new_data = DataFrame(data=ohlcv, index=[next_day_minute])
writer.write_sid(sid, new_data)
# Get a new reader to test updated calendar.
reader = BcolzMinuteBarReader(self.dest)
second_minute = dt + Timedelta(minutes=1)
# The second minute should have been padded with zeros
for col in ('open', 'high', 'low', 'close'):
assert_almost_equal(nan, reader.get_value(sid, second_minute, col))
self.assertEqual(0, reader.get_value(sid, second_minute, 'volume'))
# The next day minute should have data.
for col in ('open', 'high', 'low', 'close', 'volume'):
assert_almost_equal(ohlcv[col],
reader.get_value(sid, next_day_minute, col))
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
day = TEST_CALENDAR_START + freq
minute = self.market_opens[day]
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)
# Check that if we then pad the rest of this day, we end up with
# 2 days worth of minutes.
self.writer.pad(sid, day)
self.assertEqual(
len(self.writer._ensure_ctable(sid)),
self.writer._minutes_per_day * 2,
)
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, 0.0),
},
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, 0.0),
},
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.trading_calendar.all_minutes.get_loc(minutes[0])
minute_locs = [
self.trading_calendar.all_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.trading_calendar.minutes_for_sessions_in_range(
self.trading_calendar.minute_to_session_label(start_day),
self.trading_calendar.minute_to_session_label(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)
with self.assertRaises(NoDataOnDate):
self.reader.get_value(sid, Timestamp('2015-06-02', tz='UTC'),
'open')
with self.assertRaises(NoDataOnDate):
self.reader.get_value(sid,
Timestamp('2015-06-02 20:01:00', tz='UTC'),
'open')
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.trading_calendar.minutes_for_sessions_in_range(
self.trading_calendar.minute_to_session_label(start_day),
self.trading_calendar.minute_to_session_label(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)
with self.assertRaises(NoDataOnDate):
self.reader.get_value(sid, Timestamp('2015-11-30', tz='UTC'),
'open')
with self.assertRaises(NoDataOnDate):
self.reader.get_value(sid,
Timestamp('2015-11-30 21:01:00', tz='UTC'),
'open')
def test_set_sid_attrs(self):
"""Confirm that we can set the attributes of a sid's file correctly.
"""
sid = 1
start_day = Timestamp('2015-11-27', tz='UTC')
end_day = Timestamp('2015-06-02', tz='UTC')
attrs = {
'start_day': start_day.value / int(1e9),
'end_day': end_day.value / int(1e9),
'factor': 100,
}
# Write the attributes
self.writer.set_sid_attrs(sid, **attrs)
# Read the attributes
for k, v in attrs.items():
self.assertEqual(self.reader.get_sid_attr(sid, k), v)
def test_truncate_between_data_points(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)
# Open a new writer to cover `open` method, also truncating only
# applies to an existing directory.
writer = BcolzMinuteBarWriter.open(self.dest)
# Truncate to first day with data.
writer.truncate(days[0])
# Refresh the reader since truncate update the metadata.
self.reader = BcolzMinuteBarReader(self.dest)
self.assertEqual(self.writer.last_date_in_output_for_sid(sid), days[0])
cal = self.trading_calendar
_, last_close = cal.open_and_close_for_session(days[0])
self.assertEqual(self.reader.last_available_dt, last_close)
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)
def test_truncate_all_data_points(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)
# Truncate to first day in the calendar, a day before the first
# day with minute data.
self.writer.truncate(self.test_calendar_start)
# Refresh the reader since truncate update the metadata.
self.reader = BcolzMinuteBarReader(self.dest)
self.assertEqual(
self.writer.last_date_in_output_for_sid(sid),
self.test_calendar_start,
)
cal = self.trading_calendar
_, last_close = cal.open_and_close_for_session(
self.test_calendar_start)
self.assertEqual(self.reader.last_available_dt, last_close)
def test_early_market_close(self):
# Date to test is 2015-11-30 9:31
# Early close is 2015-11-27 18:00
friday_after_tday = Timestamp('2015-11-27', tz='UTC')
friday_after_tday_close = self.market_closes[friday_after_tday]
before_early_close = friday_after_tday_close - timedelta(minutes=8)
after_early_close = friday_after_tday_close + timedelta(minutes=8)
monday_after_tday = Timestamp('2015-11-30', tz='UTC')
minute = self.market_opens[monday_after_tday]
# Test condition where there is data written after the market
# close (ideally, this should not occur in datasets, but guards
# against consumers of the minute bar writer, which do not filter
# out after close minutes.
minutes = [
before_early_close,
after_early_close,
minute,
]
sid = 1
data = DataFrame(data={
'open': [10.0, 11.0, nan],
'high': [20.0, 21.0, nan],
'low': [30.0, 31.0, nan],
'close': [40.0, 41.0, nan],
'volume': [50, 51, 0]
},
index=[minutes])
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 = self.reader.get_value(sid, minute, 'volume')
self.assertEquals(0, volume)
asset = self.asset_finder.retrieve_asset(sid)
last_traded_dt = self.reader.get_last_traded_dt(asset, minute)
self.assertEquals(
last_traded_dt, before_early_close,
"The last traded dt should be before the early "
"close, even when data is written between the early "
"close and the next open.")
def test_minute_updates(self):
"""
Test minute updates.
"""
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)
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)
frames = {1: data_1, 2: data_2}
update_path = self.instance_tmpdir.getpath('updates.h5')
update_writer = H5MinuteBarUpdateWriter(update_path)
update_writer.write(frames)
update_reader = H5MinuteBarUpdateReader(update_path)
self.writer.write(update_reader.read(minutes, sids))
# Refresh the reader since truncate update the metadata.
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 transaction_sim(self, **params):
"""This is a utility method that asserts expected
results for conversion of orders to transactions given a
trade history
"""
trade_count = params['trade_count']
trade_interval = params['trade_interval']
order_count = params['order_count']
order_amount = params['order_amount']
order_interval = params['order_interval']
expected_txn_count = params['expected_txn_count']
expected_txn_volume = params['expected_txn_volume']
# optional parameters
# ---------------------
# if present, alternate between long and short sales
alternate = params.get('alternate')
# if present, expect transaction amounts to match orders exactly.
complete_fill = params.get('complete_fill')
asset1 = self.asset_finder.retrieve_asset(1)
metadata = make_simple_equity_info([asset1.sid], self.start, self.end)
with TempDirectory() as tempdir, \
tmp_trading_env(equities=metadata,
load=self.make_load_function()) as env:
if trade_interval < timedelta(days=1):
sim_params = factory.create_simulation_parameters(
start=self.start,
end=self.end,
data_frequency="minute"
)
minutes = self.trading_calendar.minutes_window(
sim_params.first_open,
int((trade_interval.total_seconds() / 60) * trade_count)
+ 100)
price_data = np.array([10.1] * len(minutes))
assets = {
asset1.sid: pd.DataFrame({
"open": price_data,
"high": price_data,
"low": price_data,
"close": price_data,
"volume": np.array([100] * len(minutes)),
"dt": minutes
}).set_index("dt")
}
write_bcolz_minute_data(
self.trading_calendar,
self.trading_calendar.sessions_in_range(
self.trading_calendar.minute_to_session_label(
minutes[0]
),
self.trading_calendar.minute_to_session_label(
minutes[-1]
)
),
tempdir.path,
iteritems(assets),
)
equity_minute_reader = BcolzMinuteBarReader(tempdir.path)
data_portal = DataPortal(
env.asset_finder, self.trading_calendar,
first_trading_day=equity_minute_reader.first_trading_day,
minute_reader=equity_minute_reader,
)
else:
sim_params = factory.create_simulation_parameters(
data_frequency="daily"
)
days = sim_params.sessions
assets = {
1: pd.DataFrame({
"open": [10.1] * len(days),
"high": [10.1] * len(days),
"low": [10.1] * len(days),
"close": [10.1] * len(days),
"volume": [100] * len(days),
"day": [day.value for day in days]
}, index=days)
}
path = os.path.join(tempdir.path, "testdata.bcolz")
BcolzDailyBarWriter(path, self.trading_calendar, days[0],
days[-1]).write(
assets.items()
)
equity_daily_reader = BcolzDailyBarReader(path)
data_portal = DataPortal(
env.asset_finder, self.trading_calendar,
first_trading_day=equity_daily_reader.first_trading_day,
daily_reader=equity_daily_reader,
)
if "default_slippage" not in params or \
not params["default_slippage"]:
slippage_func = FixedSlippage()
else:
slippage_func = None
blotter = Blotter(sim_params.data_frequency, slippage_func)
start_date = sim_params.first_open
if alternate:
alternator = -1
else:
alternator = 1
tracker = PerformanceTracker(sim_params, self.trading_calendar,
self.env)
# replicate what tradesim does by going through every minute or day
# of the simulation and processing open orders each time
if sim_params.data_frequency == "minute":
ticks = minutes
else:
ticks = days
transactions = []
order_list = []
order_date = start_date
for tick in ticks:
blotter.current_dt = tick
if tick >= order_date and len(order_list) < order_count:
# place an order
direction = alternator ** len(order_list)
order_id = blotter.order(
asset1,
order_amount * direction,
MarketOrder())
order_list.append(blotter.orders[order_id])
order_date = order_date + order_interval
# move after market orders to just after market next
# market open.
if order_date.hour >= 21:
if order_date.minute >= 00:
order_date = order_date + timedelta(days=1)
order_date = order_date.replace(hour=14, minute=30)
else:
bar_data = BarData(
data_portal=data_portal,
simulation_dt_func=lambda: tick,
data_frequency=sim_params.data_frequency,
trading_calendar=self.trading_calendar,
restrictions=NoRestrictions(),
)
txns, _, closed_orders = blotter.get_transactions(bar_data)
for txn in txns:
tracker.process_transaction(txn)
transactions.append(txn)
blotter.prune_orders(closed_orders)
for i in range(order_count):
order = order_list[i]
self.assertEqual(order.asset, asset1)
self.assertEqual(order.amount, order_amount * alternator ** i)
if complete_fill:
self.assertEqual(len(transactions), len(order_list))
total_volume = 0
for i in range(len(transactions)):
txn = transactions[i]
total_volume += txn.amount
if complete_fill:
order = order_list[i]
self.assertEqual(order.amount, txn.amount)
self.assertEqual(total_volume, expected_txn_volume)
self.assertEqual(len(transactions), expected_txn_count)
cumulative_pos = tracker.position_tracker.positions[asset1]
if total_volume == 0:
self.assertIsNone(cumulative_pos)
else:
self.assertEqual(total_volume, cumulative_pos.amount)
# the open orders should not contain the asset.
oo = blotter.open_orders
self.assertNotIn(
asset1,
oo,
"Entry is removed when no open orders"
)
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.trading_calendar.all_minutes.get_loc(minutes[0])
minute_locs = [
self.trading_calendar.all_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])
class OHLCVDataAccessor:
"""
Class to retrieve OHLCV minute data from catalyst.
Attributes:
exchange (str): Exchange for which the data will be requested.
catalyst_root (str): Root directory where Catalyst data is stored (normally "<home directory>//.catalyst").
path (str): Path to the data bundle.
reader (catalyst.data.minute_bars.BcolzMinuteBarReader): BcolzMinuteBarReader object doing the heavy lifting to
retrieve the data.
Example:
>> import pandas as pd
>> from catalyst.research.data_accessor import OHLCVDataAccessor
>>
>> symbol = ['eth_btc', 'xrp_btc']
>> fields = ['open', 'high', 'low', 'close', 'volume', 'volume_quote']
>> start_dt = pd.Timestamp('2018-01-01')
>> end_dt = pd.Timestamp('2018-02-01')
>>
>> accessor = OHLCVDataAccessor(exchange='binance')
>> ohlcv_data = accessor.get_data(symbol, fields, start_dt, end_dt)
>> print(ohlcv_data.volume_quote)
>> print(ohlcv_data)
"""
def __init__(self, exchange=None, catalyst_root=None):
if exchange is None:
raise ValueError('You should provide the exchange for which you')
if catalyst_root is None:
home = expanduser("~")
self.catalyst_root = home + "\\.catalyst"
else:
self.catalyst_root = catalyst_root
self.exchange = exchange
self.path = self.catalyst_root + "\\data\\exchanges\\" + exchange + "\\minute_bundle"
self.reader = BcolzMinuteBarReader(self.path)
def get_data(self,
symbol=None,
fields=None,
start_dt=None,
end_dt=None,
current_time=None):
"""
Method to retrieve the OHLCV minute data.
Args:
symbol (str or list of str): Symbol of the pair for which data is requested, or list thereof.
fields (list of str): List containing the requested fields (among 'open', 'high', 'low', 'close', 'volume',
'volume_quote').
start_dt (pd.Timestamp): Start date of the period for which data is requested.
end_dt (pd.Timestamp): End date of the period for which data is requested.
current_time (pd.Timestamp, optional): The current time from the point of view of the algorithm/simulation.
The method will raise an error if end_dt is after current_time, in order to eliminate any unforeseen
look-ahead bias.
Returns (pd.DataFrame or pd.Panel):
If a single symbol is passed, the method returns a Pandas dataframe having the dates as an index and the
fields as columns.
If a list of symbols is passed, the method returns a Pandas panel having the fields along the item axis, the
dates along the major axis and the pairs along the minor axis.
"""
if current_time is not None:
if end_dt > current_time:
raise RuntimeError(
f"The end time ({end_dt}) is in the future of the current time ({current_time}). "
f"Proceeding would introduce look-ahead bias.")
if isinstance(symbol, str):
symbols = [symbol]
return self.get_data_multiple_symbols(symbols, fields, start_dt,
end_dt).iloc[:, :, 0]
elif isinstance(symbol, list):
return self.get_data_multiple_symbols(symbol, fields, start_dt,
end_dt)
@staticmethod
def pre_handle_volume_quote(fields):
adjusted_fields = fields.copy()
if 'volume_quote' in fields:
adjusted_fields.remove('volume_quote')
if 'volume' not in fields:
adjusted_fields.append('volume')
if 'close' not in fields:
adjusted_fields.append('close')
return adjusted_fields
def get_data_multiple_symbols(self, symbols, fields, start_dt, end_dt):
"""
Gets OHLCV minute data from catalyst for a list of pairs.
Args:
See self.get_data.
Returns (pd.Panel): Pandas panel having the fields along the item axis, the dates along the major axis and the
pairs along the minor axis.
"""
adjusted_fields = self.pre_handle_volume_quote(fields)
sids = list(map(get_sid, symbols))
data = self.reader.load_raw_arrays(fields=adjusted_fields,
start_dt=start_dt,
end_dt=end_dt,
sids=sids)
time_index = pd.DatetimeIndex(freq='1T', start=start_dt, end=end_dt)
# Constructs a dataframe out of the data
data_df = pd.Panel(data,
items=adjusted_fields,
major_axis=time_index,
minor_axis=symbols)
# Converts the volume from the base currency to the quote currency
if 'volume' in fields and 'close' in fields:
if 'volume_quote' in fields:
data_df['volume_quote'] = np.multiply(data_df.volume,
data_df.close)
if 'volume' not in fields:
data_df.drop('volume', axis=0)
if 'close' not in fields:
data_df.drop('close', axis=0)
return data_df
class BcolzMinuteBarTestCase(WithTradingCalendars,
WithAssetFinder,
WithInstanceTmpDir,
ZiplineTestCase):
ASSET_FINDER_EQUITY_SIDS = 1, 2
@classmethod
def init_class_fixtures(cls):
super(BcolzMinuteBarTestCase, cls).init_class_fixtures()
cal = cls.trading_calendar.schedule.loc[
TEST_CALENDAR_START:TEST_CALENDAR_STOP
]
cls.market_opens = cal.market_open
cls.market_closes = cal.market_close
cls.test_calendar_start = cls.market_opens.index[0]
cls.test_calendar_stop = cls.market_opens.index[-1]
def init_instance_fixtures(self):
super(BcolzMinuteBarTestCase, self).init_instance_fixtures()
self.dest = self.instance_tmpdir.getpath('minute_bars')
os.makedirs(self.dest)
self.writer = BcolzMinuteBarWriter(
self.dest,
self.trading_calendar,
TEST_CALENDAR_START,
TEST_CALENDAR_STOP,
US_EQUITIES_MINUTES_PER_DAY,
)
self.reader = BcolzMinuteBarReader(self.dest)
def test_version(self):
metadata = self.reader._get_metadata()
self.assertEquals(
metadata.version,
BcolzMinuteBarMetadata.FORMAT_VERSION,
)
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_one_ohlcv_with_ratios(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],
)
# Create a new writer with `ohlc_ratios_per_sid` defined.
writer_with_ratios = BcolzMinuteBarWriter(
self.dest,
self.trading_calendar,
TEST_CALENDAR_START,
TEST_CALENDAR_STOP,
US_EQUITIES_MINUTES_PER_DAY,
ohlc_ratios_per_sid={sid: 25},
)
writer_with_ratios.write_sid(sid, data)
reader = BcolzMinuteBarReader(self.dest)
open_price = reader.get_value(sid, minute, 'open')
self.assertEquals(10.0, open_price)
high_price = reader.get_value(sid, minute, 'high')
self.assertEquals(20.0, high_price)
low_price = reader.get_value(sid, minute, 'low')
self.assertEquals(30.0, low_price)
close_price = reader.get_value(sid, minute, 'close')
self.assertEquals(40.0, close_price)
volume_price = 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_append_to_same_day(self):
"""
Test writing data with the same date as existing data in our file.
"""
sid = 1
first_minute = self.market_opens[TEST_CALENDAR_START]
data = DataFrame(
data={
'open': [10.0],
'high': [20.0],
'low': [30.0],
'close': [40.0],
'volume': [50.0]
},
index=[first_minute])
self.writer.write_sid(sid, data)
# Write data in the same day as the previous minute
second_minute = first_minute + Timedelta(minutes=1)
new_data = DataFrame(
data={
'open': [5.0],
'high': [10.0],
'low': [3.0],
'close': [7.0],
'volume': [10.0]
},
index=[second_minute])
self.writer.write_sid(sid, new_data)
open_price = self.reader.get_value(sid, second_minute, 'open')
self.assertEquals(5.0, open_price)
high_price = self.reader.get_value(sid, second_minute, 'high')
self.assertEquals(10.0, high_price)
low_price = self.reader.get_value(sid, second_minute, 'low')
self.assertEquals(3.0, low_price)
close_price = self.reader.get_value(sid, second_minute, 'close')
self.assertEquals(7.0, close_price)
volume_price = self.reader.get_value(sid, second_minute, 'volume')
self.assertEquals(10.0, volume_price)
def test_append_on_new_day(self):
sid = 1
ohlcv = {
'open': [2.0],
'high': [3.0],
'low': [1.0],
'close': [2.0],
'volume': [10.0]
}
dt = self.market_opens[TEST_CALENDAR_STOP]
data = DataFrame(
data=ohlcv,
index=[dt])
self.writer.write_sid(sid, data)
# Open a new writer to cover `open` method, also a common usage
# of appending new days will be writing to an existing directory.
cday = self.trading_calendar.schedule.index.freq
new_end_session = TEST_CALENDAR_STOP + cday
writer = BcolzMinuteBarWriter.open(self.dest, new_end_session)
next_day_minute = dt + cday
new_data = DataFrame(
data=ohlcv,
index=[next_day_minute])
writer.write_sid(sid, new_data)
# Get a new reader to test updated calendar.
reader = BcolzMinuteBarReader(self.dest)
second_minute = dt + Timedelta(minutes=1)
# The second minute should have been padded with zeros
for col in ('open', 'high', 'low', 'close'):
assert_almost_equal(
nan, reader.get_value(sid, second_minute, col)
)
self.assertEqual(
0, reader.get_value(sid, second_minute, 'volume')
)
# The next day minute should have data.
for col in ('open', 'high', 'low', 'close', 'volume'):
assert_almost_equal(
ohlcv[col], reader.get_value(sid, next_day_minute, col)
)
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
day = TEST_CALENDAR_START + freq
minute = self.market_opens[day]
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)
# Check that if we then pad the rest of this day, we end up with
# 2 days worth of minutes.
self.writer.pad(sid, day)
self.assertEqual(
len(self.writer._ensure_ctable(sid)),
self.writer._minutes_per_day * 2,
)
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, 0.0),
},
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, 0.0),
},
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.trading_calendar.all_minutes.get_loc(minutes[0])
minute_locs = [
self.trading_calendar.all_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.trading_calendar.minutes_for_sessions_in_range(
self.trading_calendar.minute_to_session_label(start_day),
self.trading_calendar.minute_to_session_label(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)
with self.assertRaises(NoDataOnDate):
self.reader.get_value(
sid,
Timestamp('2015-06-02', tz='UTC'),
'open'
)
with self.assertRaises(NoDataOnDate):
self.reader.get_value(
sid,
Timestamp('2015-06-02 20:01:00', tz='UTC'),
'open'
)
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.trading_calendar.minutes_for_sessions_in_range(
self.trading_calendar.minute_to_session_label(start_day),
self.trading_calendar.minute_to_session_label(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)
with self.assertRaises(NoDataOnDate):
self.reader.get_value(
sid,
Timestamp('2015-11-30', tz='UTC'),
'open'
)
with self.assertRaises(NoDataOnDate):
self.reader.get_value(
sid,
Timestamp('2015-11-30 21:01:00', tz='UTC'),
'open'
)
def test_set_sid_attrs(self):
"""Confirm that we can set the attributes of a sid's file correctly.
"""
sid = 1
start_day = Timestamp('2015-11-27', tz='UTC')
end_day = Timestamp('2015-06-02', tz='UTC')
attrs = {
'start_day': start_day.value / int(1e9),
'end_day': end_day.value / int(1e9),
'factor': 100,
}
# Write the attributes
self.writer.set_sid_attrs(sid, **attrs)
# Read the attributes
for k, v in attrs.items():
self.assertEqual(self.reader.get_sid_attr(sid, k), v)
def test_truncate_between_data_points(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)
# Open a new writer to cover `open` method, also truncating only
# applies to an existing directory.
writer = BcolzMinuteBarWriter.open(self.dest)
# Truncate to first day with data.
writer.truncate(days[0])
# Refresh the reader since truncate update the metadata.
self.reader = BcolzMinuteBarReader(self.dest)
self.assertEqual(self.writer.last_date_in_output_for_sid(sid), days[0])
cal = self.trading_calendar
_, last_close = cal.open_and_close_for_session(days[0])
self.assertEqual(self.reader.last_available_dt, last_close)
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)
def test_truncate_all_data_points(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)
# Truncate to first day in the calendar, a day before the first
# day with minute data.
self.writer.truncate(self.test_calendar_start)
# Refresh the reader since truncate update the metadata.
self.reader = BcolzMinuteBarReader(self.dest)
self.assertEqual(
self.writer.last_date_in_output_for_sid(sid),
self.test_calendar_start,
)
cal = self.trading_calendar
_, last_close = cal.open_and_close_for_session(
self.test_calendar_start)
self.assertEqual(self.reader.last_available_dt, last_close)
def test_early_market_close(self):
# Date to test is 2015-11-30 9:31
# Early close is 2015-11-27 18:00
friday_after_tday = Timestamp('2015-11-27', tz='UTC')
friday_after_tday_close = self.market_closes[friday_after_tday]
before_early_close = friday_after_tday_close - timedelta(minutes=8)
after_early_close = friday_after_tday_close + timedelta(minutes=8)
monday_after_tday = Timestamp('2015-11-30', tz='UTC')
minute = self.market_opens[monday_after_tday]
# Test condition where there is data written after the market
# close (ideally, this should not occur in datasets, but guards
# against consumers of the minute bar writer, which do not filter
# out after close minutes.
minutes = [
before_early_close,
after_early_close,
minute,
]
sid = 1
data = DataFrame(
data={
'open': [10.0, 11.0, nan],
'high': [20.0, 21.0, nan],
'low': [30.0, 31.0, nan],
'close': [40.0, 41.0, nan],
'volume': [50, 51, 0]
},
index=[minutes])
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 = self.reader.get_value(sid, minute, 'volume')
self.assertEquals(0, volume)
asset = self.asset_finder.retrieve_asset(sid)
last_traded_dt = self.reader.get_last_traded_dt(asset, minute)
self.assertEquals(last_traded_dt, before_early_close,
"The last traded dt should be before the early "
"close, even when data is written between the early "
"close and the next open.")
def test_minute_updates(self):
"""
Test minute updates.
"""
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)
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)
frames = {1: data_1, 2: data_2}
update_path = self.instance_tmpdir.getpath('updates.h5')
update_writer = H5MinuteBarUpdateWriter(update_path)
update_writer.write(frames)
update_reader = H5MinuteBarUpdateReader(update_path)
self.writer.write(update_reader.read(minutes, sids))
# Refresh the reader since truncate update the metadata.
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])