dpkp / kafka-python

Kafka Python client ------------------------ .. image:: https://img.shields.io/badge/kafka-4.0--0.8-brightgreen.svg :target: https://kafka-python.readthedocs.io/en/master/compatibility.html .. image:: https://img.shields.io/pypi/pyversions/kafka-python.svg :target: https://pypi.python.org/pypi/kafka-python .. image:: https://coveralls.io/repos/dpkp/kafka-python/badge.svg?branch=master&service=github :target: https://coveralls.io/github/dpkp/kafka-python?branch=master .. image:: https://img.shields.io/badge/license-Apache%202-blue.svg :target: https://github.com/dpkp/kafka-python/blob/master/LICENSE .. image:: https://img.shields.io/pypi/dw/kafka-python.svg :target: https://pypistats.org/packages/kafka-python .. image:: https://img.shields.io/pypi/v/kafka-python.svg :target: https://pypi.org/project/kafka-python .. image:: https://img.shields.io/pypi/implementation/kafka-python :target: https://github.com/dpkp/kafka-python/blob/master/setup.py Python client for the Apache Kafka distributed stream processing system. kafka-python is designed to function much like the official java client, with a sprinkling of pythonic interfaces (e.g., consumer iterators). Please note that the master branch may contain unreleased features. For release documentation, please see readthedocs and/or python's inline help. New in 2.3 release: python -m kafka.* interfaces for quick scripts and testing. .. code-block:: bash $ pip install kafka-python KafkaConsumer ************* KafkaConsumer is a high-level message consumer, intended to operate as similarly as possible to the official java client. Full support for coordinated consumer groups requires use of kafka brokers that support the Group APIs: kafka v0.9+. See https://kafka-python.readthedocs.io/en/master/apidoc/KafkaConsumer.html for API and configuration details. The consumer iterator returns ConsumerRecords, which are simple namedtuples that expose basic message attributes: topic, partition, offset, key, and value: .. code-block:: python from kafka import KafkaConsumer consumer = KafkaConsumer('my_favorite_topic') for msg in consumer: print (msg) .. code-block:: python # join a consumer group for dynamic partition assignment and offset commits from kafka import KafkaConsumer consumer = KafkaConsumer('my_favorite_topic', group_id='my_favorite_group') for msg in consumer: print (msg) .. code-block:: python # manually assign the partition list for the consumer from kafka import TopicPartition consumer = KafkaConsumer(bootstrap_servers='localhost:1234') consumer.assign([TopicPartition('foobar', 2)]) msg = next(consumer) .. code-block:: python # Deserialize msgpack-encoded values consumer = KafkaConsumer(value_deserializer=msgpack.loads) consumer.subscribe(['msgpackfoo']) for msg in consumer: assert isinstance(msg.value, dict) .. code-block:: python # Access record headers. The returned value is a list of tuples # with str, bytes for key and value for msg in consumer: print (msg.headers) .. code-block:: python # Read only committed messages from transactional topic consumer = KafkaConsumer(isolation_level='read_committed') consumer.subscribe(['txn_topic']) for msg in consumer: print(msg) .. code-block:: python # Get consumer metrics metrics = consumer.metrics() KafkaProducer ************* KafkaProducer is a high-level, asynchronous message producer. The class is intended to operate as similarly as possible to the official java client. See https://kafka-python.readthedocs.io/en/master/apidoc/KafkaProducer.html for more details. .. code-block:: python from kafka import KafkaProducer producer = KafkaProducer(bootstrap_servers='localhost:1234') for _ in range(100): producer.send('foobar', b'some_message_bytes') .. code-block:: python # Block until a single message is sent (or timeout) future = producer.send('foobar', b'another_message') result = future.get(timeout=60) .. code-block:: python # Block until all pending messages are at least put on the network # NOTE: This does not guarantee delivery or success! It is really # only useful if you configure internal batching using linger_ms producer.flush() .. code-block:: python # Use a key for hashed-partitioning producer.send('foobar', key=b'foo', value=b'bar') .. code-block:: python # Serialize json messages import json producer = KafkaProducer(value_serializer=lambda v: json.dumps(v).encode('utf-8')) producer.send('fizzbuzz', {'foo': 'bar'}) .. code-block:: python # Serialize string keys producer = KafkaProducer(key_serializer=str.encode) producer.send('flipflap', key='ping', value=b'1234') .. code-block:: python # Compress messages producer = KafkaProducer(compression_type='gzip') for i in range(1000): producer.send('foobar', b'msg %d' % i) .. code-block:: python # Use transactions producer = KafkaProducer(transactional_id='fizzbuzz') producer.init_transactions() producer.begin_transaction() future = producer.send('txn_topic', value=b'yes') future.get() # wait for successful produce producer.commit_transaction() # commit the transaction producer.begin_transaction() future = producer.send('txn_topic', value=b'no') future.get() # wait for successful produce producer.abort_transaction() # abort the transaction .. code-block:: python # Include record headers. The format is list of tuples with string key # and bytes value. producer.send('foobar', value=b'c29tZSB2YWx1ZQ==', headers=[('content-encoding', b'base64')]) .. code-block:: python # Get producer performance metrics metrics = producer.metrics() Module CLI Interface ******************** kafka-python also provides simple command-line interfaces for consumer, producer, and admin clients. Access via python -m kafka.consumer , python -m kafka.producer , and python -m kafka.admin . See https://kafka-python.readthedocs.io/en/master/usage.html for more details. Thread safety ************* The KafkaProducer can be used across threads without issu…