def test_gc_random():
from weakref import WeakValueDictionary
w = WeakValueDictionary()
a = sd.Random(freq='5ms', interval='100ms')
w[1] = a
yield gen.sleep(0.1)
a = sd.Random(freq='5ms', interval='100ms')
w[2] = a
yield gen.sleep(0.1)
a = sd.Random(freq='5ms', interval='100ms')
w[3] = a
yield gen.sleep(0.1)
assert len(w) == 1
def test_gc():
sdf = sd.Random(freq='5ms', interval='100ms')
a = StreamingDataFrame({
'volatility': sdf.x.rolling('100ms').var(),
'sub': sdf.x - sdf.x.rolling('100ms').mean()
})
n = len(sdf.stream.downstreams)
yield gen.sleep(0.1)
a = StreamingDataFrame({
'volatility': sdf.x.rolling('100ms').var(),
'sub': sdf.x - sdf.x.rolling('100ms').mean()
})
yield gen.sleep(0.1)
a = StreamingDataFrame({
'volatility': sdf.x.rolling('100ms').var(),
'sub': sdf.x - sdf.x.rolling('100ms').mean()
})
yield gen.sleep(0.1)
a = StreamingDataFrame({
'volatility': sdf.x.rolling('100ms').var(),
'sub': sdf.x - sdf.x.rolling('100ms').mean()
})
assert len(sdf.stream.downstreams) == n
del a
import gc
gc.collect()
assert len(sdf.stream.downstreams) == 0
def test_random_source():
source = sd.Random(freq='10ms', interval='100ms')
L = source.stream.sink_to_list()
yield gen.sleep(0.5)
assert 2 < len(L) < 8
assert all(2 < len(df) < 25 for df in L)
source.x
source.rolling('10s')
def test_plot():
pytest.importorskip('bokeh')
sdf = sd.Random(freq='10ms', interval='50ms')
result = sdf[['x', 'y']].plot()
cds = result['cds']
assert set(cds.data) == {'x', 'y', 'index'}
assert not len(cds.data['x'])
yield gen.sleep(0.130)
assert len(cds.data['x'])
assert len(set(map(len, cds.data.values()))) == 1
assert set(sdf.x.plot()['cds'].data) == {'x', 'index'}
def test_repartition_interval(n):
source = sd.Random(freq='10ms', interval='100ms')
L = source.stream.sink_to_list()
L2 = source.repartition(interval='150ms').stream.sink_to_list()
yield gen.sleep(0.400)
assert L2
for df in L2:
assert df.index.max() - df.index.min() <= pd.Timedelta('150ms')
expected = pd.concat(L).iloc[:sum(map(len, L2))]
assert_eq(pd.concat(L2), expected)
def test_random_source(client):
n = len(client.cluster.scheduler.tasks)
source = sd.Random(freq='1ms', interval='10ms', dask=True)
L = source.x.stream.gather().sink_to_list()
sleep(0.20)
assert len(client.cluster.scheduler.tasks) < n + 10
def test_random_source(loop):
with Client(processes=False, diagnostics_port=False, loop=loop) as client:
source = sd.Random(freq='1ms', interval='10ms', dask=True)
L = source.x.stream.gather().sink_to_list()
sleep(0.20)
assert len(client.cluster.scheduler.tasks) < 10
