def testInvalidDateTimes(self):
b1 = bar.BasicBar(datetime.datetime.now(), 2, 3, 1, 2.1, 10, 5,
bar.Frequency.DAY)
b2 = bar.BasicBar(datetime.datetime.now() + datetime.timedelta(days=1),
2, 3, 1, 2.1, 10, 5, bar.Frequency.DAY)
with self.assertRaises(Exception):
bar.Bars({"a": b1, "b": b2})
def testResample(self):
barDs = bards.BarDataSeries()
resampledDS = resampled_ds.ResampledDataSeries(barDs.getCloseDataSeries(), bar.Frequency.MINUTE, sum)
resampledBarDS = resampled_ds.ResampledBarDataSeries(barDs, bar.Frequency.MINUTE)
barDs.append(bar.BasicBar(datetime.datetime(2011, 1, 1, 1, 1, 1), 2.1, 3, 1, 2, 10, 1, bar.Frequency.SECOND))
barDs.append(bar.BasicBar(datetime.datetime(2011, 1, 1, 1, 1, 2), 2, 3, 1, 2.3, 10, 2, bar.Frequency.SECOND))
barDs.append(bar.BasicBar(datetime.datetime(2011, 1, 1, 1, 2, 1), 2, 3, 1, 2, 10, 2, bar.Frequency.SECOND))
self.assertEqual(len(resampledBarDS), 1)
self.assertEqual(resampledBarDS[0].getDateTime(), datetime.datetime(2011, 1, 1, 1, 1))
self.assertEqual(resampledBarDS[0].getOpen(), 2.1)
self.assertEqual(resampledBarDS[0].getHigh(), 3)
self.assertEqual(resampledBarDS[0].getLow(), 1)
self.assertEqual(resampledBarDS[0].getClose(), 2.3)
self.assertEqual(resampledBarDS[0].getVolume(), 20)
self.assertEqual(resampledBarDS[0].getAdjClose(), 2)
self.assertEqual(resampledDS[-1], 2 + 2.3)
resampledBarDS.pushLast()
self.assertEqual(len(resampledBarDS), 2)
self.assertEqual(resampledBarDS[1].getDateTime(), datetime.datetime(2011, 1, 1, 1, 2))
self.assertEqual(resampledBarDS[1].getOpen(), 2)
self.assertEqual(resampledBarDS[1].getHigh(), 3)
self.assertEqual(resampledBarDS[1].getLow(), 1)
self.assertEqual(resampledBarDS[1].getClose(), 2)
self.assertEqual(resampledBarDS[1].getVolume(), 10)
self.assertEqual(resampledBarDS[1].getAdjClose(), 2)
resampledDS.pushLast()
self.assertEqual(resampledDS[1], 2)
def testBasic(self):
dt = datetime.datetime.now()
b1 = bar.BasicBar(dt, 1, 1, 1, 1, 10, 1, bar.Frequency.DAY)
b2 = bar.BasicBar(dt, 2, 2, 2, 2, 10, 2, bar.Frequency.DAY)
bars = bar.Bars({"a": b1, "b": b2})
self.assertEqual(bars["a"].getClose(), 1)
self.assertEqual(bars["b"].getClose(), 2)
self.assertTrue("a" in bars)
self.assertEqual(bars.items(), [("a", b1), ("b", b2)])
self.assertEqual(bars.keys(), ["a", "b"])
self.assertEqual(bars.getInstruments(), ["a", "b"])
self.assertEqual(bars.getDateTime(), dt)
self.assertEqual(bars.getBar("a").getClose(), 1)
def testBlackWhiteReversal(self):
bds = bards.BarDataSeries()
lb = linebreak.LineBreak(bds, 2)
bds.append(bar.BasicBar(datetime.datetime(2008, 3, 5), 10, 12, 8, 9, 1, None, bar.Frequency.DAY))
self.assertEqual(len(lb), 1)
bds.append(bar.BasicBar(datetime.datetime(2008, 3, 6), 9, 12, 9, 12, 1, None, bar.Frequency.DAY))
self.assertEqual(len(lb), 1)
self.assertEqual(lb[-1].isBlack(), True)
self.assertEqual(lb[-1].getDateTime(), datetime.datetime(2008, 3, 5))
bds.append(bar.BasicBar(datetime.datetime(2008, 3, 7), 9, 13, 5, 13, 1, None, bar.Frequency.DAY))
self.assertEqual(len(lb), 2)
self.assertEqual(lb[-1].isWhite(), True)
self.assertEqual(lb[-1].getDateTime(), datetime.datetime(2008, 3, 7))
def testAppendInvalidDatetime(self):
ds = bards.BarDataSeries()
for i in xrange(10):
now = datetime.datetime.now() + datetime.timedelta(seconds=i)
ds.append(bar.BasicBar(now, 0, 0, 0, 0, 0, 0,
bar.Frequency.SECOND))
# Adding the same datetime twice should fail
with self.assertRaises(Exception):
ds.append(
bar.BasicBar(now, 0, 0, 0, 0, 0, 0, bar.Frequency.SECOND))
# Adding a previous datetime should fail
with self.assertRaises(Exception):
ds.append(
bar.BasicBar(now - datetime.timedelta(seconds=i), 0, 0, 0,
0, 0, 0, bar.Frequency.SECOND))
def testBaseBarFeedNoAdjClose(self):
bars = [
bar.Bars({
"orcl":
bar.BasicBar(datetime.datetime(2001, 1, 1), 1, 1, 1, 1, 1,
None, bar.Frequency.DAY)
}),
bar.Bars({
"orcl":
bar.BasicBar(datetime.datetime(2001, 1, 2), 1, 1, 1, 1, 1,
None, bar.Frequency.DAY)
}),
]
barFeed = barfeed.OptimizerBarFeed(bar.Frequency.DAY, ["orcl"], bars)
check_base_barfeed(self, barFeed, False)
def __buildBar(self, openPrice, highPrice, lowPrice, closePrice):
dateTime = datetime.datetime.now() + datetime.timedelta(
seconds=self.__currSeconds)
self.__currSeconds += 1
return bar.BasicBar(dateTime, openPrice, highPrice, lowPrice,
closePrice, closePrice * 10, closePrice,
bar.Frequency.DAY)
def getBars(self,
instrument,
frequency,
timezone=None,
fromDateTime=None,
toDateTime=None):
instrument = normalize_instrument(instrument)
sql = "select bar.timestamp, bar.open, bar.high, bar.low, bar.close, bar.volume, bar.adj_close, bar.frequency" \
" from bar join instrument on (bar.instrument_id = instrument.instrument_id)" \
" where instrument.name = ? and bar.frequency = ?"
args = [instrument, frequency]
if fromDateTime is not None:
sql += " and bar.timestamp >= ?"
args.append(dt.datetime_to_timestamp(fromDateTime))
if toDateTime is not None:
sql += " and bar.timestamp <= ?"
args.append(dt.datetime_to_timestamp(toDateTime))
sql += " order by bar.timestamp asc"
cursor = self.__connection.cursor()
cursor.execute(sql, args)
ret = []
for row in cursor:
dateTime = dt.timestamp_to_datetime(row[0])
if timezone:
dateTime = dt.localize(dateTime, timezone)
ret.append(
bar.BasicBar(dateTime, row[1], row[2], row[3], row[4], row[5],
row[6], row[7]))
cursor.close()
return ret
def testInvalidConstruction(self):
with self.assertRaises(Exception):
bar.BasicBar(datetime.datetime.now(), 2, 1, 1, 1, 1, 1,
bar.Frequency.DAY)
with self.assertRaises(Exception):
bar.BasicBar(datetime.datetime.now(), 1, 1, 1, 2, 1, 1,
bar.Frequency.DAY)
with self.assertRaises(Exception):
bar.BasicBar(datetime.datetime.now(), 1, 2, 1.5, 1, 1, 1,
bar.Frequency.DAY)
with self.assertRaises(Exception):
bar.BasicBar(datetime.datetime.now(), 2, 2, 1.5, 1, 1, 1,
bar.Frequency.DAY)
with self.assertRaises(Exception):
bar.BasicBar(datetime.datetime.now(), 1, 1, 1.5, 1, 1, 1,
bar.Frequency.DAY)
def parseBar(self, csvRowDict):
dateTime = self.__parseDateTime(csvRowDict["Date Time"])
close = float(csvRowDict["Close"])
open_ = float(csvRowDict["Open"])
high = float(csvRowDict["High"])
low = float(csvRowDict["Low"])
volume = float(csvRowDict["Volume"])
return bar.BasicBar(dateTime, open_, high, low, close, volume, None, self.__frequency)
def testDateTimesNotInOrder(self):
bars = [
bar.Bars({
"orcl":
bar.BasicBar(datetime.datetime(2001, 1, 2), 1, 1, 1, 1, 1, 1,
bar.Frequency.DAY)
}),
bar.Bars({
"orcl":
bar.BasicBar(datetime.datetime(2001, 1, 1), 1, 1, 1, 1, 1, 1,
bar.Frequency.DAY)
}),
]
f = barfeed.OptimizerBarFeed(bar.Frequency.DAY, ["orcl"], bars)
with self.assertRaisesRegex(Exception,
"Bar date times are not in order.*"):
for dt, b in f:
pass
def addBarsFromListofDicts(self, instrument, list_of_dicts, timezone=None):
"""Loads bars for a given instrument from a list of dictionaries.
The instrument gets registered in the bar feed.
:param instrument: Instrument identifier.
:type instrument: string.
:param list_of_dicts: A list of dicts. First item should contain
columns.
:type list_of_dicts: list
:param timezone: The timezone to use to localize bars. Check :mod:`quantworks.marketsession`.
:type timezone: A pytz timezone.
"""
if timezone is None:
timezone = self.__timezone
if not isinstance(list_of_dicts, (list, tuple)):
raise ValueError(
'This function only supports types: {list, tuple}')
if not isinstance(list_of_dicts[0], dict):
raise ValueError('List should only contain dicts')
dicts_have_adj_close = self.__columnNames[
'adj_close'] in list_of_dicts[0].keys()
missing_columns = [
col for col in self.__columnNames.values()
if col not in list_of_dicts[0].keys()
]
if missing_columns:
raise ValueError('Missing required columns: {}'.format(
repr(missing_columns)))
# Convert dicts to Bar(s)
loadedBars = map(
lambda row: bar.BasicBar(
self.__localize_dt(row[self.__columnNames['datetime']]),
row[self.__columnNames['open']],
row[self.__columnNames['high']],
row[self.__columnNames['low']],
row[self.__columnNames['close']],
row[self.__columnNames['volume']],
row[self.__columnNames['adj_close']],
self.getFrequency(),
extra={
key: row[key]
for key in set(row.keys()).difference(self.__columnNames.
values())
}), list_of_dicts)
super(Feed, self)._addBars(instrument, loadedBars)
if dicts_have_adj_close:
self.__haveAdjClose = True
elif self.__haveAdjClose:
raise Exception(
"Previous bars had adjusted close and these ones don't have.")
def run_test(cls):
bf = MockBarFeed(bar.Frequency.DAY)
bars = [
bar.BasicBar(datetime.datetime(2000, 1, 1), 10, 10, 10, 10, 10, 10, bar.Frequency.DAY),
]
bf.addBarsFromSequence("orcl", bars)
strat = MockStrategy(bf, 1000)
strat.run()
def build_bars_from_closing_prices(closingPrices):
ret = []
nextDateTime = datetime.datetime.now()
for closePrice in closingPrices:
bar_ = bar.BasicBar(nextDateTime, closePrice, closePrice, closePrice, closePrice, closePrice, closePrice, bar.Frequency.DAY)
ret.append(bar_)
nextDateTime = nextDateTime + datetime.timedelta(days=1)
return ret
def testNonEmpty(self):
ds = bards.BarDataSeries()
for i in xrange(10):
ds.append(
bar.BasicBar(
datetime.datetime.now() + datetime.timedelta(seconds=i), 0,
0, 0, 0, 0, 0, bar.Frequency.SECOND))
for i in xrange(0, 10):
self.assertTrue(ds[i].getOpen() == 0)
def testDateTimes(self):
ds = bards.BarDataSeries()
firstDt = datetime.datetime.now()
for i in xrange(10):
ds.append(
bar.BasicBar(firstDt + datetime.timedelta(seconds=i), 2, 4, 1,
3, 10, 3, bar.Frequency.SECOND))
for i in xrange(10):
self.assertEqual(ds[i].getDateTime(), ds.getDateTimes()[i])
self.assertEqual(ds.getDateTimes()[i],
firstDt + datetime.timedelta(seconds=i))
def __loadSarTestBarDs(self):
seconds = 0
ret = bards.BarDataSeries()
for i in xrange(len(SAR_HIGH)):
dateTime = datetime.datetime.now() + datetime.timedelta(
seconds=seconds)
ret.append(
bar.BasicBar(dateTime, SAR_LOW[i], SAR_HIGH[i], SAR_LOW[i],
SAR_HIGH[i], 0, SAR_LOW[i], bar.Frequency.DAY))
seconds += 1
return ret
def __loadBarDS(self):
seconds = 0
ret = bards.BarDataSeries()
for i in xrange(len(OPEN_VALUES)):
dateTime = datetime.datetime.now() + datetime.timedelta(
seconds=seconds)
ret.append(
bar.BasicBar(dateTime, OPEN_VALUES[i], HIGH_VALUES[i],
LOW_VALUES[i], CLOSE_VALUES[i], VOLUME_VALUES[i],
CLOSE_VALUES[i], bar.Frequency.DAY))
seconds += 1
return ret
def testNoAdjClose(self):
b = bar.BasicBar(datetime.datetime.now(), 2, 3, 1, 2.1, 10, None,
bar.Frequency.DAY)
with self.assertRaises(Exception):
b.setUseAdjustedValue(True)
with self.assertRaises(Exception):
b.getOpen(True)
with self.assertRaises(Exception):
b.getHigh(True)
with self.assertRaises(Exception):
b.getLow(True)
with self.assertRaises(Exception):
b.getClose(True)
def testSeqLikeOps(self):
seq = []
ds = bards.BarDataSeries()
for i in xrange(10):
bar_ = bar.BasicBar(
datetime.datetime.now() + datetime.timedelta(seconds=i), 2, 4,
1, 3, 10, 3, bar.Frequency.SECOND)
ds.append(bar_)
seq.append(bar_)
self.assertEqual(ds[-1], seq[-1])
self.assertEqual(ds[-2], seq[-2])
self.assertEqual(ds[0], seq[0])
self.assertEqual(ds[1], seq[1])
self.assertEqual(ds[-2:][-1], seq[-2:][-1])
def testNestedDataSeries(self):
ds = bards.BarDataSeries()
for i in xrange(10):
ds.append(
bar.BasicBar(
datetime.datetime.now() + datetime.timedelta(seconds=i), 2,
4, 1, 3, 10, 3, bar.Frequency.SECOND))
self.__testGetValue(ds.getOpenDataSeries(), 10, 2)
self.__testGetValue(ds.getCloseDataSeries(), 10, 3)
self.__testGetValue(ds.getHighDataSeries(), 10, 4)
self.__testGetValue(ds.getLowDataSeries(), 10, 1)
self.__testGetValue(ds.getVolumeDataSeries(), 10, 10)
self.__testGetValue(ds.getAdjCloseDataSeries(), 10, 3)
self.__testGetValue(ds.getPriceDataSeries(), 10, 3)
def parseBar(self, csvRowDict):
dateTime = self.__parseDate(csvRowDict["Date"])
close = float(csvRowDict["Close"])
open_ = float(csvRowDict["Open"])
high = float(csvRowDict["High"])
low = float(csvRowDict["Low"])
volume = float(csvRowDict["Volume"])
adjClose = None
if self.__sanitize:
open_, high, low, close = common.sanitizeOhlc(
open_, high, low, close)
return bar.BasicBar(dateTime, open_, high, low, close, volume,
adjClose, self.__frequency)
def addBarsFromDataFrame(self, instrument, df, timezone=None):
"""Loads bars for a given instrument from a Pandas DataFrame.
The instrument gets registered in the bar feed.
:param instrument: Instrument identifier.
:type instrument: string.
:param df: The pandas DataFrame
:type df: pd.DataFrame
:param timezone: The timezone to use to localize bars. Check :mod:`quantworks.marketsession`.
:type timezone: A pytz timezone.
"""
if timezone is None:
timezone = self.__timezone
df_has_adj_close = self.__columnNames['adj_close'] in df.columns
missing_columns = [
col for col in self.__columnNames.values() if col not in df.columns
]
if missing_columns:
raise ValueError('Missing required columns: {}'.format(
repr(missing_columns)))
# Convert DataFrame row(s) to Bar(s)
loadedBars = map(
lambda row: bar.BasicBar(
self.__localize_dt(row[self.__columnNames['datetime']]),
row[self.__columnNames['open']],
row[self.__columnNames['high']],
row[self.__columnNames['low']],
row[self.__columnNames['close']],
row[self.__columnNames['volume']],
row[self.__columnNames['adj_close']],
self.getFrequency(),
extra={
key: row[key]
for key in set(row.keys()).difference(self.__columnNames.
values())
}), df.to_dict(orient='record'))
self._addBars(instrument, loadedBars)
if df_has_adj_close:
self.__haveAdjClose = True
elif self.__haveAdjClose:
raise Exception(
"Previous bars had adjusted close and these ones don't have.")
def testCheckNow(self):
barDs = bards.BarDataSeries()
resampledBarDS = resampled_ds.ResampledBarDataSeries(barDs, bar.Frequency.MINUTE)
barDateTime = datetime.datetime(2014, 7, 7, 22, 46, 28, 10000)
barDs.append(bar.BasicBar(barDateTime, 2.1, 3, 1, 2, 10, 1, bar.Frequency.MINUTE))
self.assertEqual(len(resampledBarDS), 0)
resampledBarDS.checkNow(barDateTime + datetime.timedelta(minutes=1))
self.assertEqual(len(resampledBarDS), 1)
self.assertEqual(barDs[0].getOpen(), resampledBarDS[0].getOpen())
self.assertEqual(barDs[0].getHigh(), resampledBarDS[0].getHigh())
self.assertEqual(barDs[0].getLow(), resampledBarDS[0].getLow())
self.assertEqual(barDs[0].getClose(), resampledBarDS[0].getClose())
self.assertEqual(barDs[0].getVolume(), resampledBarDS[0].getVolume())
self.assertEqual(barDs[0].getAdjClose(), resampledBarDS[0].getAdjClose())
self.assertEqual(resampledBarDS[0].getDateTime(), datetime.datetime(2014, 7, 7, 22, 46))
def testPickle(self):
b1 = bar.BasicBar(datetime.datetime.now(), 2, 3, 1, 2.1, 10, 5,
bar.Frequency.DAY)
b2 = cPickle.loads(cPickle.dumps(b1))
self.assertEqual(b1.getDateTime(), b2.getDateTime())
self.assertEqual(b1.getOpen(), b2.getOpen())
self.assertEqual(b1.getHigh(), b2.getHigh())
self.assertEqual(b1.getLow(), b2.getLow())
self.assertEqual(b1.getClose(), b2.getClose())
self.assertEqual(b1.getVolume(), b2.getVolume())
self.assertEqual(b1.getAdjClose(), b2.getAdjClose())
self.assertEqual(b1.getFrequency(), b2.getFrequency())
self.assertEqual(b1.getPrice(), b2.getPrice())
self.assertEqual(b1.getOpen(True), b2.getOpen(True))
self.assertEqual(b1.getHigh(True), b2.getHigh(True))
self.assertEqual(b1.getLow(True), b2.getLow(True))
self.assertEqual(b1.getClose(True), b2.getClose(True))
def testStockChartsATRAdjusted(self):
# Test data from http://stockcharts.com/help/doku.php?id=chart_school:technical_indicators:average_true_range_a
high = [
48.70, 48.72, 48.90, 48.87, 48.82, 49.05, 49.20, 49.35, 49.92,
50.19, 50.12, 49.66, 49.88, 50.19, 50.36, 50.57, 50.65, 50.43,
49.63, 50.33, 50.29, 50.17, 49.32, 48.50, 48.32, 46.80, 47.80,
48.39, 48.66, 48.79
]
low = [
47.790, 48.140, 48.390, 48.370, 48.240, 48.635, 48.940, 48.860,
49.500, 49.870, 49.200, 48.900, 49.430, 49.725, 49.260, 50.090,
50.300, 49.210, 48.980, 49.610, 49.200, 49.430, 48.080, 47.640,
41.550, 44.283, 47.310, 47.200, 47.900, 47.730
]
close = [
48.160, 48.610, 48.750, 48.630, 48.740, 49.030, 49.070, 49.320,
49.910, 50.130, 49.530, 49.500, 49.750, 50.030, 50.310, 50.520,
50.410, 49.340, 49.370, 50.230, 49.238, 49.930, 48.430, 48.180,
46.570, 45.410, 47.770, 47.720, 48.620, 47.850
]
expected = [
None, None, None, None, None, None, None, None, None, None, None,
None, None, 0.555000, 0.593929, 0.585791, 0.568949, 0.615452,
0.617920, 0.642354, 0.674329, 0.692770, 0.775429, 0.781470,
1.209229, 1.302620, 1.380290, 1.366698, 1.336219, 1.316482
]
# Build a bar dataseries using the test data.
barDataSeries = bards.BarDataSeries()
atrDS = atr.ATR(barDataSeries, 14, True)
now = datetime.datetime(2000, 1, 1)
for i in xrange(len(high)):
b = bar.BasicBar(now + datetime.timedelta(days=i), close[i],
high[i], low[i], close[i], 100, close[i] / 2,
bar.Frequency.DAY)
barDataSeries.append(b)
if expected[i] is None:
self.assertEqual(atrDS[-1], None)
else:
self.assertEqual(common.safe_round(atrDS[-1], 2),
round(expected[i] / 2, 2))
def testGetPrice(self):
b = bar.BasicBar(datetime.datetime.now(), 2, 3, 1, 2.1, 10, 5,
bar.Frequency.DAY)
self.assertEqual(b.getPrice(), b.getClose())
b.setUseAdjustedValue(True)
self.assertEqual(b.getPrice(), b.getAdjClose())
def testTypicalPrice(self):
b = bar.BasicBar(datetime.datetime.now(), 2, 3, 1, 2.1, 10, 5,
bar.Frequency.DAY)
self.assertEqual(b.getTypicalPrice(), (3 + 1 + 2.1) / 3)
