def __init__(self, upstream, func, *args, **kwargs):
self.func = func
# this is one of a few stream specific kwargs
stream_name = kwargs.pop('stream_name', None)
self.kwargs = kwargs
self.args = args
Stream.__init__(self, upstream, stream_name=stream_name)
def __init__(self, upstream, topic, producer_config, **kwargs):
import confluent_kafka as ck
self.topic = topic
self.producer = ck.Producer(producer_config)
kwargs["ensure_io_loop"] = True
Stream.__init__(self, upstream, **kwargs)
self.stopped = False
self.polltime = 0.2
self.loop.add_callback(self.poll)
self.futures = []
def __init__(self, upstream, batch_size, **kwargs):
if not isinstance(batch_size, int):
raise TypeError(
"Expected batch_size to be an integer. Got {}.".format(
type(batch_size)))
if batch_size <= 0:
raise ValueError(
"Expected batch_size to be a positive integer. Got {}.".format(
batch_size))
self.batch_size = batch_size
self.item_buffer = []
stream_name = kwargs.pop('stream_name', None)
Stream.__init__(self, upstream, stream_name=stream_name)
def __init__(self, upstream, n, **kwargs):
self.n = n
self._buffer = []
self.metadata_buffer = []
Stream.__init__(self, upstream, **kwargs)
