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)