Welcome to Confluent’s Apache Kafka Python client documentation

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confluent_kafka — Confluent’s Apache Kafka Python client

Consumer

class confluent_kafka.Consumer

High-level Kafka Consumer

Consumer(**kwargs)

Create new Consumer instance using provided configuration dict.

Special configuration properties:

on_commit: Optional callback will be called when a commit request has succeeded or failed.

on_commit(err, partitions)

Parameters:

• consumer (Consumer) – Consumer instance.
• err (KafkaError) – Commit error object, or None on success.
• partitions (list(TopicPartition)) – List of partitions with their committed offsets or per-partition errors.

assign()

assign(partitions)

Set consumer partition assignment to the provided list of TopicPartition and starts consuming.

Parameters:partitions (list(TopicPartition)) – List of topic+partitions and optionally initial offsets to start consuming. Raises:RuntimeError if called on a closed consumer

assignment()

assignment()

Returns the current partition assignment.

Returns:List of assigned topic+partitions. Return type:list(TopicPartition) Raises:KafkaException Raises:RuntimeError if called on a closed consumer

close()

Close down and terminate the Kafka Consumer.

Actions performed:

• Stops consuming
• Commits offsets - except if the consumer property ‘enable.auto.commit’ is set to False
• Leave consumer group

Return type:None Raises:RuntimeError if called on a closed consumer

commit()

commit([message=None][, offsets=None][, asynchronous=True])

Commit a message or a list of offsets.

message and offsets are mutually exclusive, if neither is set the current partition assignment’s offsets are used instead. The consumer relies on your use of this method if you have set ‘enable.auto.commit’ to False

Parameters:

• message (confluent_kafka.Message) – Commit message’s offset+1.
• offsets (list(TopicPartition)) – List of topic+partitions+offsets to commit.
• asynchronous (bool) – Asynchronous commit, return None immediately. If False the commit() call will block until the commit succeeds or fails and the committed offsets will be returned (on success). Note that specific partitions may have failed and the .err field of each partition will need to be checked for success.

Return type:

None|list(TopicPartition)

Raises:

KafkaException

Raises:

RuntimeError if called on a closed consumer

committed()

committed(partitions[, timeout=None])

Retrieve committed offsets for the list of partitions.

Parameters:

• partitions (list(TopicPartition)) – List of topic+partitions to query for stored offsets.
• timeout (float) – Request timeout. (Seconds)

Returns:

List of topic+partitions with offset and possibly error set.

Return type:

list(TopicPartition)

Raises:

KafkaException

Raises:

RuntimeError if called on a closed consumer

consume()

consume([num_messages=1][, timeout=-1])

Consume messages, calls callbacks and returns list of messages (possibly empty on timeout).

The application must check the returned Message object’s Message.error() method to distinguish between proper messages (error() returns None), or an event or error for each Message in the list (see error().code() for specifics).

Parameters:

• num_messages (int) – Maximum number of messages to return (default: 1).
• timeout (float) – Maximum time to block waiting for message, event or callback (default: infinite (-1)). (Seconds)

Returns:

A list of Message objects (possibly empty on timeout)

Return type:

list(Message)

Raises:

RuntimeError if called on a closed consumer, KafkaError in case of internal error, or ValueError if num_messages > 1M.

get_watermark_offsets()

get_watermark_offsets(partition[, timeout=None][, cached=False])

Retrieve low and high offsets for partition.

Parameters:

• partition (TopicPartition) – Topic+partition to return offsets for. :param float timeout: Request timeout (when cached=False). (Seconds)
• cached (bool) – Instead of querying the broker used cached information. Cached values: The low offset is updated periodically (if statistics.interval.ms is set) while the high offset is updated on each message fetched from the broker for this partition. :returns: Tuple of (low,high) on success or None on timeout.

Return type:

tuple(int,int)

Raises:

KafkaException

Raises:

RuntimeError if called on a closed consumer

offsets_for_times()

offsets_for_times(partitions[, timeout=None])

offsets_for_times looks up offsets by timestamp for the given partitions.

The returned offsets for each partition is the earliest offset whose timestamp is greater than or equal to the given timestamp in the corresponding partition.

param list(TopicPartition) partitions:  topic+partitions with timestamps in the TopicPartition.offset field. :param float timeout: Request timeout. (Seconds) returns:list of topic+partition with offset field set and possibly error set rtype:list(TopicPartition) raises:KafkaException raises:RuntimeError if called on a closed consumer

pause()

pause(partitions)

Pause consumption for the provided list of partitions.

Parameters:partitions (list(TopicPartition)) – List of topic+partitions to pause. Return type:None Raises:KafkaException

poll()

poll([timeout=None])

Consume messages, calls callbacks and returns events.

The application must check the returned Message object’s Message.error() method to distinguish between proper messages (error() returns None), or an event or error (see error().code() for specifics).

Parameters:timeout (float) – Maximum time to block waiting for message, event or callback. (Seconds) Returns:A Message object or None on timeout Return type:Message or None Raises:RuntimeError if called on a closed consumer

position()

position(partitions[, timeout=None])

Retrieve current positions (offsets) for the list of partitions.

Parameters:partitions (list(TopicPartition)) – List of topic+partitions to return current offsets for. The current offset is the offset of the last consumed message + 1. Returns:List of topic+partitions with offset and possibly error set. Return type:list(TopicPartition) Raises:KafkaException Raises:RuntimeError if called on a closed consumer

resume()

resume(partitions)

Resume consumption for the provided list of partitions.

Parameters:partitions (list(TopicPartition)) – List of topic+partitions to resume. Return type:None Raises:KafkaException

seek()

seek(partition)

Set consume position for partition to offset. The offset may be an absolute (>=0) or a logical offset (OFFSET_BEGINNING et.al).

seek() may only be used to update the consume offset of an actively consumed partition (i.e., after assign()), to set the starting offset of partition not being consumed instead pass the offset in an assign() call.

Parameters:partition (TopicPartition) – Topic+partition+offset to seek to. Raises:KafkaException

store_offsets()

store_offsets([message=None][, offsets=None])

Store offsets for a message or a list of offsets.

message and offsets are mutually exclusive. The stored offsets will be committed according to ‘auto.commit.interval.ms’ or manual offset-less commit(). Note that ‘enable.auto.offset.store’ must be set to False when using this API.

Parameters:

• message (confluent_kafka.Message) – Store message’s offset+1.
• offsets (list(TopicPartition)) – List of topic+partitions+offsets to store.

Return type:

None

Raises:

KafkaException

Raises:

RuntimeError if called on a closed consumer

subscribe()

subscribe(topics[, listener=None])

Set subscription to supplied list of topics This replaces a previous subscription.

Regexp pattern subscriptions are supported by prefixing the topic string with "^", e.g.:

consumer.subscribe(["^my_topic.*", "^another[0-9]-?[a-z]+$", "not_a_regex"])

Parameters:

• topics (list(str)) – List of topics (strings) to subscribe to.
• on_assign (callable) – callback to provide handling of customized offsets on completion of a successful partition re-assignment.
• on_revoke (callable) – callback to provide handling of offset commits to a customized store on the start of a rebalance operation.

Raises:

KafkaException –

Raises:

RuntimeError if called on a closed consumer

on_assign(consumer, partitions)

on_revoke(consumer, partitions)

Parameters:

• consumer (Consumer) – Consumer instance.
• partitions (list(TopicPartition)) – Absolute list of partitions being assigned or revoked.

unassign()

Removes the current partition assignment and stops consuming. :raises: KafkaException :raises: RuntimeError if called on a closed consumer

unsubscribe()

Remove current subscription.

Raises:KafkaException Raises:RuntimeError if called on a closed consumer

Producer

class confluent_kafka.Producer

Asynchronous Kafka Producer

Producer(**kwargs)

Create new Producer instance using provided configuration dict.

len()

Returns:Number of messages and Kafka protocol requests waiting to be delivered to broker. Return type:int

flush()

flush([timeout])

Wait for all messages in the Producer queue to be delivered. This is a convenience method that calls poll() until len() is zero or the optional timeout elapses.

Param:float timeout: Maximum time to block (requires librdkafka >= v0.9.4). (Seconds) Returns:Number of messages still in queue.

Note

See poll() for a description on what callbacks may be triggered.

poll()

poll([timeout])

Polls the producer for events and calls the corresponding callbacks (if registered).

Callbacks:

• on_delivery callbacks from produce()
• …

Parameters:timeout (float) – Maximum time to block waiting for events. (Seconds) Returns:Number of events processed (callbacks served) Return type:int

produce()

produce(topic[, value][, key][, partition][, on_delivery][, timestamp])

Produce message to topic. This is an asynchronous operation, an application may use the callback (alias on_delivery) argument to pass a function (or lambda) that will be called from poll() when the message has been successfully delivered or permanently fails delivery.

Currently message headers are not supported on the message returned to the callback. The msg.headers() will return None even if the original message had headers set.

Parameters:

• topic (str) – Topic to produce message to
• value (str|bytes) – Message payload
• key (str|bytes) – Message key
• partition (int) – Partition to produce to, elses uses the configured partitioner.
• on_delivery(err,msg) (func) – Delivery report callback to call (from poll() or flush()) on successful or failed delivery
• timestamp (int) – Message timestamp (CreateTime) in microseconds since epoch UTC (requires librdkafka >= v0.9.4, api.version.request=true, and broker >= 0.10.0.0). Default value is current time.

Return type:

None

Raises:

• BufferError – if the internal producer message queue is full (queue.buffering.max.messages exceeded)
• KafkaException – for other errors, see exception code
• NotImplementedError – if timestamp is specified without underlying library support.

Message

class confluent_kafka.Message

The Message object represents either a single consumed or produced message, or an event (error() is not None).

An application must check with error() to see if the object is a proper message (error() returns None) or an error/event.

This class is not user-instantiable.

len()

Returns:Message value (payload) size in bytes Return type:int

error()

The message object is also used to propagate errors and events, an application must check error() to determine if the Message is a proper message (error() returns None) or an error or event (error() returns a KafkaError object)

Return type:None or KafkaError

headers()

Retrieve the headers set on a message. Each header is a key valuepair. Please note that header keys are ordered and can repeat.

Returns:list of two-tuples, one (key, value) pair for each header. Return type:[(str, bytes),..] or None.

key()

Returns:message key or None if not available. Return type:str|bytes or None

offset()

Returns:message offset or None if not available. Return type:int or None

partition()

Returns:partition number or None if not available. Return type:int or None

set_headers()

Set the field ‘Message.headers’ with new value. :param: object value: Message.headers. :returns: None. :rtype: None

set_key()

Set the field ‘Message.key’ with new value. :param: object value: Message.key. :returns: None. :rtype: None

set_value()

Set the field ‘Message.value’ with new value. :param: object value: Message.value. :returns: None. :rtype: None

timestamp()

Retrieve timestamp type and timestamp from message. The timestamp type is one of:

• TIMESTAMP_NOT_AVAILABLE - Timestamps not supported by broker
• TIMESTAMP_CREATE_TIME - Message creation time (or source / producer time)
• TIMESTAMP_LOG_APPEND_TIME - Broker receive time

The returned timestamp should be ignored if the timestamp type is TIMESTAMP_NOT_AVAILABLE.

The timestamp is the number of milliseconds since the epoch (UTC).

Timestamps require broker version 0.10.0.0 or later and {'api.version.request': True} configured on the client.

Returns:tuple of message timestamp type, and timestamp. Return type:(int, int)

topic()

Returns:topic name or None if not available. Return type:str or None

value()

Returns:message value (payload) or None if not available. Return type:str|bytes or None

TopicPartition

class confluent_kafka.TopicPartition

TopicPartition is a generic type to hold a single partition and various information about it.

It is typically used to provide a list of topics or partitions for various operations, such as Consumer.assign().

TopicPartition(topic[, partition][, offset])

Instantiate a TopicPartition object.

Parameters:

• topic (string) – Topic name
• partition (int) – Partition id
• offset (int) – Initial partition offset

Return type:

TopicPartition

error

Py:attribute:Indicates an error (with KafkaError) unless None.

offset

Py:attribute:Offset (long)

Either an absolute offset (>=0) or a logical offset: OFFSET_BEGINNING, OFFSET_END, OFFSET_STORED, OFFSET_INVALID

partition

Py:attribute:Partition number (int)

topic

:py:attribute:topic - Topic name (string)

KafkaError

class confluent_kafka.KafkaError

Kafka error and event object

The KafkaError class serves multiple purposes:

• Propagation of errors
• Propagation of events
• Exceptions

This class is not user-instantiable.

Error and event constants:

Constant	Description
_BAD_MSG	Local: Bad message format
_BAD_COMPRESSION	Local: Invalid compressed data
_DESTROY	Local: Broker handle destroyed
_FAIL	Local: Communication failure with broker
_TRANSPORT	Local: Broker transport failure
_CRIT_SYS_RESOURCE	Local: Critical system resource failure
_RESOLVE	Local: Host resolution failure
_MSG_TIMED_OUT	Local: Message timed out
_PARTITION_EOF	Broker: No more messages
_UNKNOWN_PARTITION	Local: Unknown partition
_FS	Local: File or filesystem error
_UNKNOWN_TOPIC	Local: Unknown topic
_ALL_BROKERS_DOWN	Local: All broker connections are down
_INVALID_ARG	Local: Invalid argument or configuration
_TIMED_OUT	Local: Timed out
_QUEUE_FULL	Local: Queue full
_ISR_INSUFF	Local: ISR count insufficient
_NODE_UPDATE	Local: Broker node update
_SSL	Local: SSL error
_WAIT_COORD	Local: Waiting for coordinator
_UNKNOWN_GROUP	Local: Unknown group
_IN_PROGRESS	Local: Operation in progress
_PREV_IN_PROGRESS	Local: Previous operation in progress
_EXISTING_SUBSCRIPTION	Local: Existing subscription
_ASSIGN_PARTITIONS	Local: Assign partitions
_REVOKE_PARTITIONS	Local: Revoke partitions
_CONFLICT	Local: Conflicting use
_STATE	Local: Erroneous state
_UNKNOWN_PROTOCOL	Local: Unknown protocol
_NOT_IMPLEMENTED	Local: Not implemented
_AUTHENTICATION	Local: Authentication failure
_NO_OFFSET	Local: No offset stored
_OUTDATED	Local: Outdated
_TIMED_OUT_QUEUE	Local: Timed out in queue
_UNSUPPORTED_FEATURE	Local: Required feature not supported by broker
_WAIT_CACHE	Local: Awaiting cache update
_INTR	Local: Operation interrupted
_KEY_SERIALIZATION	Local: Key serialization error
_VALUE_SERIALIZATION	Local: Value serialization error
_KEY_DESERIALIZATION	Local: Key deserialization error
_VALUE_DESERIALIZATION	Local: Value deserialization error
_PARTIAL	Local: Partial response
_READ_ONLY	Local: Read-only object
_NOENT	Local: No such entry
_UNDERFLOW	Local: Read underflow
UNKNOWN	Unknown broker error
NO_ERROR	Success
OFFSET_OUT_OF_RANGE	Broker: Offset out of range
INVALID_MSG	Broker: Invalid message
UNKNOWN_TOPIC_OR_PART	Broker: Unknown topic or partition
INVALID_MSG_SIZE	Broker: Invalid message size
LEADER_NOT_AVAILABLE	Broker: Leader not available
NOT_LEADER_FOR_PARTITION	Broker: Not leader for partition
REQUEST_TIMED_OUT	Broker: Request timed out
BROKER_NOT_AVAILABLE	Broker: Broker not available
REPLICA_NOT_AVAILABLE	Broker: Replica not available
MSG_SIZE_TOO_LARGE	Broker: Message size too large
STALE_CTRL_EPOCH	Broker: StaleControllerEpochCode
OFFSET_METADATA_TOO_LARGE	Broker: Offset metadata string too large
NETWORK_EXCEPTION	Broker: Broker disconnected before response received
GROUP_LOAD_IN_PROGRESS	Broker: Group coordinator load in progress
GROUP_COORDINATOR_NOT_AVAILABLE	Broker: Group coordinator not available
NOT_COORDINATOR_FOR_GROUP	Broker: Not coordinator for group
TOPIC_EXCEPTION	Broker: Invalid topic
RECORD_LIST_TOO_LARGE	Broker: Message batch larger than configured server segment size
NOT_ENOUGH_REPLICAS	Broker: Not enough in-sync replicas
NOT_ENOUGH_REPLICAS_AFTER_APPEND	Broker: Message(s) written to insufficient number of in-sync replicas
INVALID_REQUIRED_ACKS	Broker: Invalid required acks value
ILLEGAL_GENERATION	Broker: Specified group generation id is not valid
INCONSISTENT_GROUP_PROTOCOL	Broker: Inconsistent group protocol
INVALID_GROUP_ID	Broker: Invalid group.id
UNKNOWN_MEMBER_ID	Broker: Unknown member
INVALID_SESSION_TIMEOUT	Broker: Invalid session timeout
REBALANCE_IN_PROGRESS	Broker: Group rebalance in progress
INVALID_COMMIT_OFFSET_SIZE	Broker: Commit offset data size is not valid
TOPIC_AUTHORIZATION_FAILED	Broker: Topic authorization failed
GROUP_AUTHORIZATION_FAILED	Broker: Group authorization failed
CLUSTER_AUTHORIZATION_FAILED	Broker: Cluster authorization failed
INVALID_TIMESTAMP	Broker: Invalid timestamp
UNSUPPORTED_SASL_MECHANISM	Broker: Unsupported SASL mechanism
ILLEGAL_SASL_STATE	Broker: Request not valid in current SASL state
UNSUPPORTED_VERSION	Broker: API version not supported
TOPIC_ALREADY_EXISTS	Broker: Topic already exists
INVALID_PARTITIONS	Broker: Invalid number of partitions
INVALID_REPLICATION_FACTOR	Broker: Invalid replication factor
INVALID_REPLICA_ASSIGNMENT	Broker: Invalid replica assignment
INVALID_CONFIG	Broker: Configuration is invalid
NOT_CONTROLLER	Broker: Not controller for cluster
INVALID_REQUEST	Broker: Invalid request
UNSUPPORTED_FOR_MESSAGE_FORMAT	Broker: Message format on broker does not support request
POLICY_VIOLATION	Broker: Isolation policy volation
OUT_OF_ORDER_SEQUENCE_NUMBER	Broker: Broker received an out of order sequence number
DUPLICATE_SEQUENCE_NUMBER	Broker: Broker received a duplicate sequence number
INVALID_PRODUCER_EPOCH	Broker: Producer attempted an operation with an old epoch
INVALID_TXN_STATE	Broker: Producer attempted a transactional operation in an invalid state
INVALID_PRODUCER_ID_MAPPING	Broker: Producer attempted to use a producer id which is not currently assigned to its transactional
INVALID_TRANSACTION_TIMEOUT	Broker: Transaction timeout is larger than the maximum value allowed by the broker’s max.transaction
CONCURRENT_TRANSACTIONS	Broker: Producer attempted to update a transaction while another concurrent operation on the same tr
TRANSACTION_COORDINATOR_FENCED	Broker: Indicates that the transaction coordinator sending a WriteTxnMarker is no longer the current
TRANSACTIONAL_ID_AUTHORIZATION_FAILED	Broker: Transactional Id authorization failed
SECURITY_DISABLED	Broker: Security features are disabled
OPERATION_NOT_ATTEMPTED	Broker: Operation not attempted

code()

Returns the error/event code for comparison toKafkaError.<ERR_CONSTANTS>.

Returns:error/event code Return type:int

name()

Returns the enum name for error/event.

Returns:error/event enum name string Return type:str

str()

Returns the human-readable error/event string.

Returns:error/event message string Return type:str

KafkaException

class confluent_kafka.KafkaException

Kafka exception that wraps the KafkaError class.

Use exception.args[0] to extract the KafkaError object

Offset

Logical offset constants:

• OFFSET_BEGINNING - Beginning of partition (oldest offset)
• OFFSET_END - End of partition (next offset)
• OFFSET_STORED - Use stored/committed offset
• OFFSET_INVALID - Invalid/Default offset

Configuration

Configuration of producer and consumer instances is performed by providing a dict of configuration properties to the instance constructor, e.g.:

conf = {'bootstrap.servers': 'mybroker.com',
        'group.id': 'mygroup', 'session.timeout.ms': 6000,
        'on_commit': my_commit_callback,
        'default.topic.config': {'auto.offset.reset': 'smallest'}}
consumer = confluent_kafka.Consumer(conf)

The supported configuration values are dictated by the underlying librdkafka C library. For the full range of configuration properties please consult librdkafka’s documentation: https://github.com/edenhill/librdkafka/blob/master/CONFIGURATION.md

The Python bindings also provide some additional configuration properties:

• default.topic.config: value is a dict of topic-level configuration properties that are applied to all used topics for the instance.

• error_cb(kafka.KafkaError): Callback for generic/global error events. This callback is served by poll().

• stats_cb(json_str): Callback for statistics data. This callback is triggered by poll() every statistics.interval.ms (needs to be configured separately). Function argument json_str is a str instance of a JSON document containing statistics data.

• on_delivery(kafka.KafkaError, kafka.Message) (Producer): value is a Python function reference that is called once for each produced message to indicate the final delivery result (success or failure). This property may also be set per-message by passing callback=callable (or on_delivery=callable) to the confluent_kafka.Producer.produce() function. Currently message headers are not supported on the message returned to the callback. The msg.headers() will return None even if the original message had headers set.

• on_commit(kafka.KafkaError, list(kafka.TopicPartition)) (Consumer): Callback used to indicate success or failure of commit requests.

• logger=logging.Handler kwarg: forward logs from the Kafka client to the provided logging.Handler instance. To avoid spontaneous calls from non-Python threads the log messages will only be forwarded when client.poll() is called.

  mylogger = logging.getLogger() mylogger.addHandler(logging.StreamHandler()) producer = confluent_kafka.Producer({‘bootstrap.servers’: ‘mybroker.com’},

  logger=mylogger)