Afkak is a Twisted-native Apache Kafka client library. It provides support for:
- Producing messages, with automatic batching and optional compression.
- Consuming messages, with group coordination and automatic commit.
Learn more in the documentation, download from PyPI, or review the contribution guidelines. Please report any issues on GitHub.
Afkak supports these Pythons:
- CPython 3.7, 3.8, and 3.9
- PyPy3
We aim to support Kafka 1.1.x and later. Integration tests are run against these Kafka broker versions:
- 0.9.0.1
- 1.1.1
Testing against 2.0.0 is planned (see #45).
Newer broker releases will generally function, but not all Afkak features will work on older brokers. In particular, the coordinated consumer won’t work before Kafka 0.9.0.1. We don’t recommend deploying such old releases of Kafka anyway, as they have serious bugs.
Note: This code is not meant to be runnable. See producer_example and consumer_example for runnable example code.
from afkak.client import KafkaClient
from afkak.consumer import Consumer
from afkak.producer import Producer
from afkak.common import (OFFSET_EARLIEST, PRODUCER_ACK_ALL_REPLICAS,
PRODUCER_ACK_LOCAL_WRITE)
kClient = KafkaClient("localhost:9092")
# To send messages
producer = Producer(kClient)
d1 = producer.send_messages("my-topic", msgs=[b"some message"])
d2 = producer.send_messages("my-topic", msgs=[b"takes a list", b"of messages"])
# To get confirmations/errors on the sends, add callbacks to the returned deferreds
d1.addCallbacks(handleResponses, handleErrors)
# To wait for acknowledgements
# PRODUCER_ACK_LOCAL_WRITE : server will wait till the data is written to
# a local log before sending response
# [ the default ]
# PRODUCER_ACK_ALL_REPLICAS : server will block until the message is committed
# by all in sync replicas before sending a response
producer = Producer(kClient,
req_acks=Producer.PRODUCER_ACK_LOCAL_WRITE,
ack_timeout=2000)
responseD = producer.send_messages("my-topic", msgs=[b"message"])
# Using twisted's @inlineCallbacks:
responses = yield responseD
if response:
print(response[0].error)
print(response[0].offset)
# To send messages in batch: You can use a producer with any of the
# partitioners 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 (whichever comes first). You can
# also batch by number of bytes.
# Notes:
# * If the producer dies before the messages are sent, the caller would
# * not have had the callbacks called on the send_messages() returned
# * deferreds, and so can retry.
# * Calling producer.stop() before the messages are sent will
# errback() the deferred(s) returned from the send_messages call(s)
producer = Producer(kClient, batch_send=True,
batch_send_every_n=20,
batch_send_every_t=60)
responseD1 = producer.send_messages("my-topic", msgs=[b"message"])
responseD2 = producer.send_messages("my-topic", msgs=[b"message 2"])
# To consume messages
# define a function which takes a list of messages to process and
# possibly returns a deferred which fires when the processing is
# complete.
def processor_func(consumer, messages):
# Store_Messages_In_Database may return a deferred
result = store_messages_in_database(messages)
# record last processed message
consumer.commit()
return result
the_partition = 3 # Consume only from partition 3.
consumer = Consumer(kClient, "my-topic", the_partition, processor_func)
d = consumer.start(OFFSET_EARLIEST) # Start reading at earliest message
# The deferred returned by consumer.start() will fire when an error
# occurs that can't handled by the consumer, or when consumer.stop()
# is called
yield d
consumer.stop()
kClient.close()from afkak.client import KafkaClient
from afkak.producer import Producer
from afkak.partitioner import HashedPartitioner, RoundRobinPartitioner
kafka = KafkaClient("localhost:9092")
# Use the HashedPartitioner so that the producer will use the optional key
# argument on send_messages()
producer = Producer(kafka, partitioner_class=HashedPartitioner)
producer.send_messages("my-topic", "key1", [b"some message"])
producer.send_messages("my-topic", "key2", [b"this method"])
from afkak.client import KafkaClient
kafka = KafkaClient("localhost:9092")
req = ProduceRequest(topic="my-topic", partition=1,
messages=[KafkaProtocol.encode_message(b"some message")])
resps = afkak.send_produce_request(payloads=[req], fail_on_error=True)
kafka.close()
resps[0].topic # b"my-topic"
resps[0].partition # 1
resps[0].error # 0 (hopefully)
resps[0].offset # offset of the first message sent in this requestAfkak releases are available on PyPI.
Because the Afkak dependencies Twisted and python-snappy have binary extension modules you will need to install the Python development headers for the interpreter you wish to use:
| Debian/Ubuntu: | sudo apt-get install build-essential python3-dev pypy3-dev libsnappy-dev
|
| OS X | brew install python pypy snappypip install virtualenv |
Then Afkak can be installed with pip as usual:
Copyright 2013, 2014, 2015 David Arthur under Apache License, v2.0. See LICENSE
Copyright 2014, 2015 Cyan, Inc. under Apache License, v2.0. See LICENSE
Copyright 2015–2021 Ciena Corporation under Apache License, v2.0. See LICENSE
This project began as a port of the kafka-python library to Twisted.
See AUTHORS.md for the full contributor list.
In order to run Afkak's tests, you need to install the dependencies as specified in the install section.
The Afkak test suite uses Tox to execute the tests in all the supported Python versions. The preferred method to run the tests is to install Tox in a virtual environment before running the tests:
make venvAfkak has two types of tests:
-
Unit tests — unit tests are fast tests. They don't do I/O.
-
Integration tests — tests that run against a real Kafka broker.
To run all unit tests in all the supported Python versions (requires all the versions to be installed in the system where the tests will run):
make toxuAlternatively, you might want to run unit tests in a list of specific Python versions:
.env/bin/tox -e py35-unit-snappy,py38-unit-snappyPlease run the tests on the minimum and maximum supported Python versions before submitting a pull request.
The integration tests will actually start up real local ZooKeeper instance and Kafka brokers, and send messages in using the client.
The makefile knows how to download several versions of Kafka. This will run just the integration tests against Kafka 1.1.1:
KAFKA_VER=1.1.1 make toximake toxamake toxik