def __init__(
self,
call: Annotated[
Union[
Callable[..., "SendableMessage"],
Callable[..., Awaitable["SendableMessage"]],
],
Doc(
"Message handler function "
"to wrap the same with `@broker.subscriber(...)` way."
),
],
*topics: Annotated[
str,
Doc("Kafka topics to consume messages from."),
],
publishers: Annotated[
Iterable[KafkaPublisher],
Doc("Kafka publishers to broadcast the handler result."),
] = (),
batch: Annotated[
bool,
Doc("Whether to consume messages in batches or not."),
] = False,
group_id: Annotated[
Optional[str],
Doc(
"""
Name of the consumer group to join for dynamic
partition assignment (if enabled), and to use for fetching and
committing offsets. If `None`, auto-partition assignment (via
group coordinator) and offset commits are disabled.
"""
),
] = None,
key_deserializer: Annotated[
Optional[Callable[[bytes], Any]],
Doc(
"Any callable that takes a raw message `bytes` "
"key and returns a deserialized one."
),
] = None,
value_deserializer: Annotated[
Optional[Callable[[bytes], Any]],
Doc(
"Any callable that takes a raw message `bytes` "
"value and returns a deserialized value."
),
] = None,
fetch_max_bytes: Annotated[
int,
Doc(
"""
The maximum amount of data the server should
return for a fetch request. This is not an absolute maximum, if
the first message in the first non-empty partition of the fetch
is larger than this value, the message will still be returned
to ensure that the consumer can make progress. NOTE: consumer
performs fetches to multiple brokers in parallel so memory
usage will depend on the number of brokers containing
partitions for the topic.
"""
),
] = 50 * 1024 * 1024,
fetch_min_bytes: Annotated[
int,
Doc(
"""
Minimum amount of data the server should
return for a fetch request, otherwise wait up to
`fetch_max_wait_ms` for more data to accumulate.
"""
),
] = 1,
fetch_max_wait_ms: Annotated[
int,
Doc(
"""
The maximum amount of time in milliseconds
the server will block before answering the fetch request if
there isn't sufficient data to immediately satisfy the
requirement given by `fetch_min_bytes`.
"""
),
] = 500,
max_partition_fetch_bytes: Annotated[
int,
Doc(
"""
The maximum amount of data
per-partition the server will return. The maximum total memory
used for a request ``= #partitions * max_partition_fetch_bytes``.
This size must be at least as large as the maximum message size
the server allows or else it is possible for the producer to
send messages larger than the consumer can fetch. If that
happens, the consumer can get stuck trying to fetch a large
message on a certain partition.
"""
),
] = 1 * 1024 * 1024,
auto_offset_reset: Annotated[
Literal["latest", "earliest", "none"],
Doc(
"""
A policy for resetting offsets on `OffsetOutOfRangeError` errors:
* `earliest` will move to the oldest available message
* `latest` will move to the most recent
* `none` will raise an exception so you can handle this case
"""
),
] = "latest",
auto_commit: Annotated[
bool,
Doc(
"""
If `True` the consumer's offset will be
periodically committed in the background.
"""
),
] = True,
auto_commit_interval_ms: Annotated[
int,
Doc(
"""
Milliseconds between automatic
offset commits, if `auto_commit` is `True`."""
),
] = 5 * 1000,
check_crcs: Annotated[
bool,
Doc(
"""
Automatically check the CRC32 of the records
consumed. This ensures no on-the-wire or on-disk corruption to
the messages occurred. This check adds some overhead, so it may
be disabled in cases seeking extreme performance.
"""
),
] = True,
partition_assignment_strategy: Annotated[
Sequence["AbstractPartitionAssignor"],
Doc(
"""
List of objects to use to
distribute partition ownership amongst consumer instances when
group management is used. This preference is implicit in the order
of the strategies in the list. When assignment strategy changes:
to support a change to the assignment strategy, new versions must
enable support both for the old assignment strategy and the new
one. The coordinator will choose the old assignment strategy until
all members have been updated. Then it will choose the new
strategy.
"""
),
] = (RoundRobinPartitionAssignor,),
max_poll_interval_ms: Annotated[
int,
Doc(
"""
Maximum allowed time between calls to
consume messages in batches. If this interval
is exceeded the consumer is considered failed and the group will
rebalance in order to reassign the partitions to another consumer
group member. If API methods block waiting for messages, that time
does not count against this timeout.
"""
),
] = 5 * 60 * 1000,
rebalance_timeout_ms: Annotated[
Optional[int],
Doc(
"""
The maximum time server will wait for this
consumer to rejoin the group in a case of rebalance. In Java client
this behaviour is bound to `max.poll.interval.ms` configuration,
but as ``aiokafka`` will rejoin the group in the background, we
decouple this setting to allow finer tuning by users that use
`ConsumerRebalanceListener` to delay rebalacing. Defaults
to ``session_timeout_ms``
"""
),
] = None,
session_timeout_ms: Annotated[
int,
Doc(
"""
Client group session and failure detection
timeout. The consumer sends periodic heartbeats
(`heartbeat.interval.ms`) to indicate its liveness to the broker.
If no hearts are received by the broker for a group member within
the session timeout, the broker will remove the consumer from the
group and trigger a rebalance. The allowed range is configured with
the **broker** configuration properties
`group.min.session.timeout.ms` and `group.max.session.timeout.ms`.
"""
),
] = 10 * 1000,
heartbeat_interval_ms: Annotated[
int,
Doc(
"""
The expected time in milliseconds
between heartbeats to the consumer coordinator when using
Kafka's group management feature. Heartbeats are used to ensure
that the consumer's session stays active and to facilitate
rebalancing when new consumers join or leave the group. The
value must be set lower than `session_timeout_ms`, but typically
should be set no higher than 1/3 of that value. It can be
adjusted even lower to control the expected time for normal
rebalances.
"""
),
] = 3 * 1000,
consumer_timeout_ms: Annotated[
int,
Doc(
"""
Maximum wait timeout for background fetching
routine. Mostly defines how fast the system will see rebalance and
request new data for new partitions.
"""
),
] = 200,
max_poll_records: Annotated[
Optional[int],
Doc(
"""
The maximum number of records returned in a
single call by batch consumer. Has no limit by default.
"""
),
] = None,
exclude_internal_topics: Annotated[
bool,
Doc(
"""
Whether records from internal topics
(such as offsets) should be exposed to the consumer. If set to True
the only way to receive records from an internal topic is
subscribing to it.
"""
),
] = True,
isolation_level: Annotated[
Literal["read_uncommitted", "read_committed"],
Doc(
"""
Controls how to read messages written
transactionally.
* `read_committed`, batch consumer will only return
transactional messages which have been committed.
* `read_uncommitted` (the default), batch consumer will
return all messages, even transactional messages which have been
aborted.
Non-transactional messages will be returned unconditionally in
either mode.
Messages will always be returned in offset order. Hence, in
`read_committed` mode, batch consumer will only return
messages up to the last stable offset (LSO), which is the one less
than the offset of the first open transaction. In particular any
messages appearing after messages belonging to ongoing transactions
will be withheld until the relevant transaction has been completed.
As a result, `read_committed` consumers will not be able to read up
to the high watermark when there are in flight transactions.
Further, when in `read_committed` the seek_to_end method will
return the LSO. See method docs below.
"""
),
] = "read_uncommitted",
batch_timeout_ms: Annotated[
int,
Doc(
"""
Milliseconds spent waiting if
data is not available in the buffer. If 0, returns immediately
with any records that are available currently in the buffer,
else returns empty.
"""
),
] = 200,
max_records: Annotated[
Optional[int],
Doc("Number of messages to consume as one batch."),
] = None,
listener: Annotated[
Optional["ConsumerRebalanceListener"],
Doc(
"""
Optionally include listener
callback, which will be called before and after each rebalance
operation.
As part of group management, the consumer will keep track of
the list of consumers that belong to a particular group and
will trigger a rebalance operation if one of the following
events trigger:
* Number of partitions change for any of the subscribed topics
* Topic is created or deleted
* An existing member of the consumer group dies
* A new member is added to the consumer group
When any of these events are triggered, the provided listener
will be invoked first to indicate that the consumer's
assignment has been revoked, and then again when the new
assignment has been received. Note that this listener will
immediately override any listener set in a previous call
to subscribe. It is guaranteed, however, that the partitions
revoked/assigned
through this interface are from topics subscribed in this call.
"""
),
] = None,
pattern: Annotated[
Optional[str],
Doc(
"""
Pattern to match available topics. You must provide either topics or pattern, but not both.
"""
),
] = None,
partitions: Annotated[
Optional[Iterable["TopicPartition"]],
Doc(
"""
A topic and partition tuple. You can't use 'topics' and 'partitions' in the same time.
"""
),
] = (),
# broker args
dependencies: Annotated[
Iterable["Depends"],
Doc("Dependencies list (`[Depends(),]`) to apply to the subscriber."),
] = (),
parser: Annotated[
Optional["CustomCallable"],
Doc("Parser to map original **ConsumerRecord** object to FastStream one."),
] = None,
decoder: Annotated[
Optional["CustomCallable"],
Doc("Function to decode FastStream msg bytes body to python objects."),
] = None,
middlewares: Annotated[
Iterable["SubscriberMiddleware[KafkaMessage]"],
Doc("Subscriber middlewares to wrap incoming message processing."),
] = (),
filter: Annotated[
"Filter[KafkaMessage]",
Doc(
"Overload subscriber to consume various messages from the same source."
),
deprecated(
"Deprecated in **FastStream 0.5.0**. "
"Please, create `subscriber` object and use it explicitly instead. "
"Argument will be removed in **FastStream 0.6.0**."
),
] = default_filter,
retry: Annotated[
bool,
Doc("Whether to `nack` message at processing exception."),
] = False,
no_ack: Annotated[
bool,
Doc("Whether to disable **FastStream** autoacknowledgement logic or not."),
] = False,
no_reply: Annotated[
bool,
Doc(
"Whether to disable **FastStream** RPC and Reply To auto responses or not."
),
] = False,
# AsyncAPI args
title: Annotated[
Optional[str],
Doc("AsyncAPI subscriber object title."),
] = None,
description: Annotated[
Optional[str],
Doc(
"AsyncAPI subscriber object description. "
"Uses decorated docstring as default."
),
] = None,
include_in_schema: Annotated[
bool,
Doc("Whetever to include operation in AsyncAPI schema or not."),
] = True,
) -> None:
super().__init__(
call,
*topics,
publishers=publishers,
group_id=group_id,
key_deserializer=key_deserializer,
value_deserializer=value_deserializer,
fetch_max_wait_ms=fetch_max_wait_ms,
fetch_max_bytes=fetch_max_bytes,
fetch_min_bytes=fetch_min_bytes,
max_partition_fetch_bytes=max_partition_fetch_bytes,
auto_offset_reset=auto_offset_reset,
auto_commit=auto_commit,
auto_commit_interval_ms=auto_commit_interval_ms,
check_crcs=check_crcs,
partition_assignment_strategy=partition_assignment_strategy,
max_poll_interval_ms=max_poll_interval_ms,
rebalance_timeout_ms=rebalance_timeout_ms,
session_timeout_ms=session_timeout_ms,
heartbeat_interval_ms=heartbeat_interval_ms,
consumer_timeout_ms=consumer_timeout_ms,
max_poll_records=max_poll_records,
exclude_internal_topics=exclude_internal_topics,
isolation_level=isolation_level,
max_records=max_records,
batch_timeout_ms=batch_timeout_ms,
batch=batch,
listener=listener,
pattern=pattern,
partitions=partitions,
# basic args
dependencies=dependencies,
parser=parser,
decoder=decoder,
middlewares=middlewares,
filter=filter,
no_reply=no_reply,
# AsyncAPI args
title=title,
description=description,
include_in_schema=include_in_schema,
# FastDepends args
retry=retry,
no_ack=no_ack,
)