afc64e7de1
This patch changes the use of "async" with the PEP8 recommended convention. As of Python 3.6, the following deprecation warning is displayed: See PEP 492 for further details.: https://www.python.org/dev/peps/pep-0492/ Change-Id: I0e3fd5b70fb34ee3b4f1eb444c27279479b3bc60 Story: 2006176 Task: 35700
71 lines
2.4 KiB
Python
71 lines
2.4 KiB
Python
# Licensed under the Apache License, Version 2.0 (the "License"); you may
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# not use this file except in compliance with the License. You may obtain
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# a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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# License for the specific language governing permissions and limitations
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# under the License.
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from __future__ import absolute_import
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from itertools import cycle
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import logging
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import random
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import six
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from six.moves import xrange
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from .base import Producer
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log = logging.getLogger(__name__)
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class SimpleProducer(Producer):
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"""A simple, round-robin producer.
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See Producer class for Base Arguments
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Additional Arguments:
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random_start (bool, optional): randomize the initial partition which
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the first message block will be published to, otherwise
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if false, the first message block will always publish
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to partition 0 before cycling through each partition,
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defaults to True.
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"""
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def __init__(self, *args, **kwargs):
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self.partition_cycles = {}
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self.random_start = kwargs.pop('random_start', True)
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super(SimpleProducer, self).__init__(*args, **kwargs)
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def _next_partition(self, topic):
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if topic not in self.partition_cycles:
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if not self.client.has_metadata_for_topic(topic):
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self.client.load_metadata_for_topics(topic)
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self.partition_cycles[topic] = cycle(self.client.get_partition_ids_for_topic(topic))
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# Randomize the initial partition that is returned
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if self.random_start:
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num_partitions = len(self.client.get_partition_ids_for_topic(topic))
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for _ in xrange(random.randint(0, num_partitions - 1)):
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next(self.partition_cycles[topic])
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return next(self.partition_cycles[topic])
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def send_messages(self, topic, *msg):
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if not isinstance(topic, six.binary_type):
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topic = topic.encode('utf-8')
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partition = self._next_partition(topic)
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return super(SimpleProducer, self).send_messages(
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topic, partition, *msg
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)
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def __repr__(self):
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return '<SimpleProducer batch=%s>' % self.is_async
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