SimpleConsumer (DEPRECATED)

from kafka import SimpleProducer, SimpleClient

# To consume messages
client = SimpleClient('localhost:9092')
consumer = SimpleConsumer(client, "my-group", "my-topic")
for message in consumer:
    # message is raw byte string -- decode if necessary!
    # e.g., for unicode: `message.decode('utf-8')`

# Use multiprocessing for parallel consumers
from kafka import MultiProcessConsumer

# This will split the number of partitions among two processes
consumer = MultiProcessConsumer(client, "my-group", "my-topic", num_procs=2)

# This will spawn processes such that each handles 2 partitions max
consumer = MultiProcessConsumer(client, "my-group", "my-topic",

for message in consumer:

for message in consumer.get_messages(count=5, block=True, timeout=4):


SimpleProducer (DEPRECATED)

Asynchronous Mode

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,

Synchronous Mode

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,

responses = producer.send_messages('my-topic', b'another message')
for r in responses:

KeyedProducer (DEPRECATED)

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)

SimpleClient (DEPRECATED)

import time
from kafka import SimpleClient
from kafka.common import (
    LeaderNotAvailableError, NotLeaderForPartitionError,
from kafka.protocol import create_message

kafka = SimpleClient('localhost:9092')
payload = ProduceRequestPayload(topic='my-topic', partition=0,
                                messages=[create_message("some message")])

retries = 5
resps = []
while retries and not resps:
    retries -= 1
        resps = kafka.send_produce_request(
            payloads=[payload], fail_on_error=True)
    except LeaderNotAvailableError, NotLeaderForPartitionError:

    # Other exceptions you might consider handling:
    # UnknownTopicOrPartitionError, TopicAuthorizationFailedError,
    # RequestTimedOutError, MessageSizeTooLargeError, InvalidTopicError,
    # RecordListTooLargeError, InvalidRequiredAcksError,
    # NotEnoughReplicasError, NotEnoughReplicasAfterAppendError


resps[0].topic      # 'my-topic'
resps[0].partition  # 0
resps[0].error      # 0
resps[0].offset     # offset of the first message sent in this request