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Usage
*****
KafkaConsumer
=============
.. code:: python
from kafka import KafkaConsumer
# To consume latest messages and auto-commit offsets
consumer = KafkaConsumer('my-topic',
group_id='my-group',
bootstrap_servers=['localhost:9092'])
for message in consumer:
# message value and key are raw bytes -- decode if necessary!
# e.g., for unicode: `message.value.decode('utf-8')`
print ("%s:%d:%d: key=%s value=%s" % (message.topic, message.partition,
message.offset, message.key,
message.value))
# consume earliest available messages, dont commit offsets
KafkaConsumer(auto_offset_reset='earliest', enable_auto_commit=False)
# consume json messages
KafkaConsumer(value_deserializer=lambda m: json.loads(m.decode('ascii')))
# consume msgpack
KafkaConsumer(value_deserializer=msgpack.unpackb)
# StopIteration if no message after 1sec
KafkaConsumer(consumer_timeout_ms=1000)
# Subscribe to a regex topic pattern
consumer = KafkaConsumer()
consumer.subscribe(pattern='^awesome.*')
# Use multiple consumers in parallel w/ 0.9 kafka brokers
# typically you would run each on a different server / process / CPU
consumer1 = KafkaConsumer('my-topic',
group_id='my-group',
bootstrap_servers='my.server.com')
consumer2 = KafkaConsumer('my-topic',
group_id='my-group',
bootstrap_servers='my.server.com')
There are many configuration options for the consumer class. See
:class:`~kafka.KafkaConsumer` API documentation for more details.
SimpleProducer
==============
Asynchronous Mode
-----------------
.. code:: python
from kafka import SimpleProducer, SimpleClient
# To send messages asynchronously
client = SimpleClient('localhost:9092')
producer = SimpleProducer(client, async=True)
producer.send_messages('my-topic', b'async message')
# To send messages in batch. You can use any of the available
# producers for doing this. The following producer will collect
# messages in batch and send them to Kafka after 20 messages are
# collected or every 60 seconds
# Notes:
# * If the producer dies before the messages are sent, there will be losses
# * Call producer.stop() to send the messages and cleanup
producer = SimpleProducer(client,
async=True,
batch_send_every_n=20,
batch_send_every_t=60)
Synchronous Mode
----------------
.. code:: python
from kafka import SimpleProducer, SimpleClient
# To send messages synchronously
client = SimpleClient('localhost:9092')
producer = SimpleProducer(client, async=False)
# Note that the application is responsible for encoding messages to type bytes
producer.send_messages('my-topic', b'some message')
producer.send_messages('my-topic', b'this method', b'is variadic')
# Send unicode message
producer.send_messages('my-topic', u'你怎么样?'.encode('utf-8'))
# To wait for acknowledgements
# ACK_AFTER_LOCAL_WRITE : server will wait till the data is written to
# a local log before sending response
# ACK_AFTER_CLUSTER_COMMIT : server will block until the message is committed
# by all in sync replicas before sending a response
producer = SimpleProducer(client,
async=False,
req_acks=SimpleProducer.ACK_AFTER_LOCAL_WRITE,
ack_timeout=2000,
sync_fail_on_error=False)
responses = producer.send_messages('my-topic', b'another message')
for r in responses:
logging.info(r.offset)
KeyedProducer
=============
.. code:: python
from kafka import (
SimpleClient, KeyedProducer,
Murmur2Partitioner, RoundRobinPartitioner)
kafka = SimpleClient('localhost:9092')
# HashedPartitioner is default (currently uses python hash())
producer = KeyedProducer(kafka)
producer.send_messages(b'my-topic', b'key1', b'some message')
producer.send_messages(b'my-topic', b'key2', b'this methode')
# Murmur2Partitioner attempts to mirror the java client hashing
producer = KeyedProducer(kafka, partitioner=Murmur2Partitioner)
# Or just produce round-robin (or just use SimpleProducer)
producer = KeyedProducer(kafka, partitioner=RoundRobinPartitioner)
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