def __init__(self,
datafn=random_datablock,
interval='500ms',
dask=False,
start=True,
**kwargs):
if dask:
from streamz.dask import DaskStream
source = DaskStream()
else:
source = Source()
self.loop = source.loop
self.interval = pd.Timedelta(interval).total_seconds()
self.source = source
self.continue_ = [False] # like the oppose of self.stopped
self.kwargs = kwargs
stream = self.source.map(lambda x: datafn(**x, **kwargs))
example = datafn(last=pd.Timestamp.now(),
now=pd.Timestamp.now(),
**kwargs)
super(PeriodicDataFrame, self).__init__(stream, example)
if start:
self.start()
def __init__(self,
datafn=random_datablock,
interval='500ms',
dask=False,
**kwargs):
if dask:
from streamz.dask import DaskStream
source = DaskStream()
loop = source.loop
else:
source = Source()
loop = IOLoop.current()
self.interval = pd.Timedelta(interval).total_seconds()
self.source = source
self.continue_ = [True]
self.kwargs = kwargs
stream = self.source.map(lambda x: datafn(**x, **kwargs))
example = datafn(last=pd.Timestamp.now(),
now=pd.Timestamp.now(),
**kwargs)
super(PeriodicDataFrame, self).__init__(stream, example)
loop.add_callback(self._cb, self.interval, self.source, self.continue_)
def __init__(self, freq='100ms', interval='500ms', dask=False):
if dask:
from streamz.dask import DaskStream
source = DaskStream()
loop = source.loop
else:
source = Source()
loop = IOLoop.current()
self.freq = pd.Timedelta(freq)
self.interval = pd.Timedelta(interval).total_seconds()
self.source = source
self.continue_ = [True]
stream = self.source.map(_random_df)
example = _random_df((time(), time(), self.freq))
super(Random, self).__init__(stream, example)
loop.add_callback(self._cb, self.interval, self.freq, self.source,
self.continue_)
def __init__(self,
parameters,
url,
auth={},
frequency=100,
dask=False,
start=False,
timeout=2):
if dask:
from streamz.dask import DaskStream
source = DaskStream()
self.loop = source.loop
else:
source = streamz.Source(asynchronous=False)
self.loop = IOLoop.current()
self.source = source
self.url = url
self.parameters = [(param, "") if isinstance(param, str) else
(param[0], param[1]) for param in parameters]
self.frequency = frequency
self.continue_ = [True]
self.timeout = timeout
auth_kwargs = auth.copy()
auth_url = auth.pop(
"url",
urlparse.urlunsplit(
urlparse.urlsplit(url)[:2] + ("Login", "", "")))
self.auth = HistorianAuth(auth_url, **auth)
example = self.make_df(
tuple([(time.time(), name, float("nan"), unit)
for name, unit in self.parameters]))
stream = self.source.unique().map(self.make_df)
super(sdf.DataFrame, self).__init__(stream, example=example)
self.http_client = AsyncHTTPClient()
if start:
self.start()
def __init__(self, freq='100ms', interval='500ms', dask=False):
if dask:
from streamz.dask import DaskStream
source = DaskStream()
else:
source = Source()
self.source = source
start = {'last': time(), 'freq': pd.Timedelta(freq)}
stream = self.source.accumulate(_random_accumulator,
returns_state=True,
start=start)
from tornado.ioloop import PeriodicCallback
self.interval = pd.Timedelta(interval).total_seconds() * 1000
def trigger():
source._emit(None)
self.pc = PeriodicCallback(trigger, self.interval)
self.pc.start()
_, example = _random_accumulator(start, None)
super(Random, self).__init__(stream, example)
def stream(loop, request, client): # flake8: noqa
if request.param == 'core':
return Stream()
else:
return DaskStream()
def stream(request, client): # flake8: noqa
if request.param == "core":
return Stream()
else:
return DaskStream()
