def test_minutely_fetcher(self):
self.responses.add(
self.responses.GET,
'https://fake.urls.com/aapl_minute_csv_data.csv',
body=AAPL_MINUTE_CSV_DATA,
content_type='text/csv',
)
sim_params = factory.create_simulation_parameters(
start=pd.Timestamp("2006-01-03", tz='UTC'),
end=pd.Timestamp("2006-01-10", tz='UTC'),
emission_rate="minute",
data_frequency="minute"
)
test_algo = TradingAlgorithm(
script="""
from zipline.api import fetch_csv, record, sid
def initialize(context):
fetch_csv('https://fake.urls.com/aapl_minute_csv_data.csv')
def handle_data(context, data):
record(aapl_signal=data.current(sid(24), "signal"))
""", sim_params=sim_params, data_frequency="minute", env=self.env)
# manually setting data portal and getting generator because we need
# the minutely emission packets here. TradingAlgorithm.run() only
# returns daily packets.
test_algo.data_portal = FetcherDataPortal(self.env,
self.trading_calendar)
gen = test_algo.get_generator()
perf_packets = list(gen)
signal = [result["minute_perf"]["recorded_vars"]["aapl_signal"] for
result in perf_packets if "minute_perf" in result]
self.assertEqual(6 * 390, len(signal))
# csv data is:
# symbol,date,signal
# aapl,1/4/06 5:31AM, 1
# aapl,1/4/06 11:30AM, 2
# aapl,1/5/06 5:31AM, 1
# aapl,1/5/06 11:30AM, 3
# aapl,1/9/06 5:31AM, 1
# aapl,1/9/06 11:30AM, 4 for dates 1/3 to 1/10
# 2 signals per day, only last signal is taken. So we expect
# 390 bars of signal NaN on 1/3
# 390 bars of signal 2 on 1/4
# 390 bars of signal 3 on 1/5
# 390 bars of signal 3 on 1/6 (forward filled)
# 390 bars of signal 4 on 1/9
# 390 bars of signal 4 on 1/9 (forward filled)
np.testing.assert_array_equal([np.NaN] * 390, signal[0:390])
np.testing.assert_array_equal([2] * 390, signal[390:780])
np.testing.assert_array_equal([3] * 780, signal[780:1560])
np.testing.assert_array_equal([4] * 780, signal[1560:])
def run_algo(self, code, sim_params=None, data_frequency="daily"):
if sim_params is None:
sim_params = self.sim_params
test_algo = TradingAlgorithm(script=code,
sim_params=sim_params,
env=self.env,
data_frequency=data_frequency)
results = test_algo.run(FetcherDataPortal(self.env))
return results
def run_algo(self, code, sim_params=None, data_frequency="daily"):
if sim_params is None:
sim_params = self.sim_params
test_algo = self.make_algo(
script=code,
sim_params=sim_params,
data_frequency=data_frequency,
data_portal=FetcherDataPortal(self.env, self.trading_calendar),
)
results = test_algo.run()
return results
def run_algo(self, code, sim_params=None):
if sim_params is None:
sim_params = self.sim_params
test_algo = self.make_algo(
script=code,
sim_params=sim_params,
data_portal=FetcherDataPortal(self.asset_finder,
self.trading_calendar,
self.DATA_PORTAL_FIRST_TRADING_DAY),
)
results = test_algo.run()
return results