Simple APIs (DEPRECATED)¶
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')`
print(message)
# 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",
partitions_per_proc=2)
for message in consumer:
print(message)
for message in consumer.get_messages(count=5, block=True, timeout=4):
print(message)
client.close()
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,
async=True,
batch_send_every_n=20,
batch_send_every_t=60)
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,
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 (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.errors import LeaderNotAvailableError, NotLeaderForPartitionError
from kafka.protocol import create_message
from kafka.structs import ProduceRequestPayload
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
try:
resps = kafka.send_produce_request(
payloads=[payload], fail_on_error=True)
except LeaderNotAvailableError, NotLeaderForPartitionError:
kafka.load_metadata_for_topics()
time.sleep(1)
# Other exceptions you might consider handling:
# UnknownTopicOrPartitionError, TopicAuthorizationFailedError,
# RequestTimedOutError, MessageSizeTooLargeError, InvalidTopicError,
# RecordListTooLargeError, InvalidRequiredAcksError,
# NotEnoughReplicasError, NotEnoughReplicasAfterAppendError
kafka.close()
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