def testPriority(self):
feed4 = RealtimeFeed([], None)
feed3 = RealtimeFeed([], None)
feed2 = RealtimeFeed([], 3)
feed1 = RealtimeFeed([], 0)
dispatcher = observer.Dispatcher()
dispatcher.addSubject(feed3)
dispatcher.addSubject(feed2)
dispatcher.addSubject(feed1)
self.assertEqual(dispatcher.getSubjects(), [feed1, feed2, feed3])
dispatcher = observer.Dispatcher()
dispatcher.addSubject(feed1)
dispatcher.addSubject(feed2)
dispatcher.addSubject(feed3)
self.assertEqual(dispatcher.getSubjects(), [feed1, feed2, feed3])
dispatcher = observer.Dispatcher()
dispatcher.addSubject(feed3)
dispatcher.addSubject(feed4)
dispatcher.addSubject(feed2)
dispatcher.addSubject(feed1)
self.assertEqual(dispatcher.getSubjects(),
[feed1, feed2, feed3, feed4])
def run(self, feed, useAdjustedCloseForReturns=True):
"""Runs the analysis using the bars supplied by the feed.
:param barFeed: The bar feed to use to run the analysis.
:type barFeed: :class:`pyalgotrade.barfeed.BarFeed`.
:param useAdjustedCloseForReturns: True if adjusted close values should be used to calculate returns.
:type useAdjustedCloseForReturns: boolean.
"""
try:
self.__feed = feed
self.__rets = {}
self.__futureRets = {}
for instrument in feed.getRegisteredInstruments():
self.__events.setdefault(instrument, [])
self.__futureRets[instrument] = []
if useAdjustedCloseForReturns:
ds = feed[instrument].getAdjCloseDataSeries()
else:
ds = feed[instrument].getCloseDataSeries()
self.__rets[instrument] = roc.RateOfChange(ds, 1)
feed.getNewBarsEvent().subscribe(self.__onBars)
dispatcher = observer.Dispatcher()
dispatcher.addSubject(feed)
dispatcher.run()
finally:
feed.getNewBarsEvent().unsubscribe(self.__onBars)
def testFeedWithQuandl(self):
class RowFilter(csvfeed.RowFilter):
def includeRow(self, dateTime, values):
return dateTime.year == 2013
feed = csvfeed.Feed("Date",
"%Y-%m-%d",
maxLen=40,
timezone=marketsession.USEquities.timezone)
feed.setRowFilter(RowFilter())
feed.setTimeDelta(datetime.timedelta(hours=23, minutes=59, seconds=59))
feed.addValuesFromCSV(common.get_data_file_path("quandl_gold_2.csv"))
for col in ["USD", "GBP", "EUR"]:
self.assertEqual(len(feed[col]), 0)
dispatcher = observer.Dispatcher()
dispatcher.addSubject(feed)
dispatcher.run()
for col in ["USD", "GBP", "EUR"]:
self.assertEqual(len(feed[col]), 39)
self.assertEqual(feed["USD"][-1], 1333.0)
self.assertEqual(feed["GBP"][-1], 831.203)
self.assertEqual(feed["EUR"][-1], 986.75)
self.assertFalse(dt.datetime_is_naive(feed["USD"].getDateTimes()[-1]))
self.assertEqual(
feed["USD"].getDateTimes()[-1],
dt.localize(datetime.datetime(2013, 9, 29, 23, 59, 59),
marketsession.USEquities.timezone))
def resample_impl(barFeed, frequency, csvFile):
sampler = Sampler(barFeed, frequency, csvFile)
# Process all bars.
disp = observer.Dispatcher()
disp.addSubject(barFeed)
disp.run()
sampler.finish()
def tstBaseFeedInterface(testCase, feed):
# This tests the observer.Subject interface.
dispatcher = observer.Dispatcher()
dispatcher.addSubject(feed)
dispatcher.run()
# This tests the feed.BaseFeed interface.
feed.isRealTime()
feed.createDataSeries("any", 10)
feed.getNextValues()
def test1NrtFeed(self):
values = []
now = datetime.datetime.now()
datetimes = [now + datetime.timedelta(seconds=i) for i in xrange(10)]
nrtFeed = NonRealtimeFeed(copy.copy(datetimes))
nrtFeed.getEvent().subscribe(lambda x: values.append(x))
dispatcher = observer.Dispatcher()
dispatcher.addSubject(nrtFeed)
dispatcher.run()
self.assertEqual(values, datetimes)
def testDispatchOrder(self):
values = []
now = datetime.datetime.now()
feed1 = NonRealtimeFeed([now], 0)
feed2 = RealtimeFeed([now + datetime.timedelta(seconds=1)], None)
feed1.getEvent().subscribe(lambda x: values.append(x))
feed2.getEvent().subscribe(lambda x: values.append(x))
dispatcher = observer.Dispatcher()
dispatcher.addSubject(feed2)
dispatcher.addSubject(feed1)
self.assertEqual(dispatcher.getSubjects(), [feed1, feed2])
dispatcher.run()
# Check that although feed2 is realtime, feed1 was dispatched before.
self.assertTrue(values[0] < values[1])
def test2NrtFeeds(self): values = [] now = datetime.datetime.now() datetimes1 = [now + datetime.timedelta(seconds=i) for i in xrange(10)] datetimes2 = [now + datetime.timedelta(seconds=i+len(datetimes1)) for i in xrange(10)] nrtFeed1 = NonRealtimeFeed(copy.copy(datetimes1)) nrtFeed1.getEvent().subscribe(lambda x: values.append(x)) nrtFeed2 = NonRealtimeFeed(copy.copy(datetimes2)) nrtFeed2.getEvent().subscribe(lambda x: values.append(x)) dispatcher = observer.Dispatcher() dispatcher.addSubject(nrtFeed1) dispatcher.addSubject(nrtFeed2) dispatcher.run() self.assertEquals(len(values), len(datetimes1) + len(datetimes2)) self.assertEquals(values[:len(datetimes1)], datetimes1) self.assertEquals(values[len(datetimes1):], datetimes2)
def testFeed(self):
values = [(datetime.datetime.now() + datetime.timedelta(seconds=i), {
"i": i
}) for i in xrange(100)]
feed = memfeed.MemFeed()
feed.addValues(values)
# Check that the dataseries are available after adding values.
self.assertTrue("i" in feed)
self.assertEqual(len(feed["i"]), 0)
self.assertFalse("dt" in feed)
dispatcher = observer.Dispatcher()
dispatcher.addSubject(feed)
dispatcher.run()
self.assertTrue("i" in feed)
self.assertFalse("dt" in feed)
self.assertEqual(feed["i"][0], 0)
self.assertEqual(feed["i"][-1], 99)
def testFeedWithBars(self):
feed = csvfeed.Feed("Date", "%Y-%m-%d")
feed.addValuesFromCSV(
common.get_data_file_path("orcl-2000-yahoofinance.csv"))
self.assertEqual(len(feed.getKeys()), 6)
for col in ["Open", "High", "Low", "Close", "Volume", "Adj Close"]:
self.assertEqual(len(feed[col]), 0)
dispatcher = observer.Dispatcher()
dispatcher.addSubject(feed)
dispatcher.run()
for col in ["Open", "High", "Low", "Close", "Volume", "Adj Close"]:
self.assertEqual(len(feed[col]), 252)
self.assertEqual(feed["Open"][-1], 30.87)
self.assertEqual(feed["High"][-1], 31.31)
self.assertEqual(feed["Low"][-1], 28.69)
self.assertEqual(feed["Close"][-1], 29.06)
self.assertEqual(feed["Volume"][-1], 31655500)
self.assertEqual(feed["Adj Close"][-1], 28.41)