pykicak

pykicak makes it easy to build RabbitMQ-connected agent nodes with idempotent message processing. It provides abstract base classes — Injector and Executor — that handle RabbitMQ connection setup and queue/exchange declaration, so subclasses only need to implement their specific behavior. Delivery is at-least-once, so the processing your agents implement must be idempotent; see Requirement: idempotent processing.

• Injector — short-lived node that creates and publishes an initial message to start a processing flow (e.g. a document ingestion trigger).
• Executor — long-running node that consumes messages from a queue, executes them, and optionally publishes the results to an exchange. Messages that can never be processed are dead-lettered instead of blocking the queue. Can operate in "terminator" mode where it consumes but does not publish (e.g. a database writer or quality checker).

Requirement: idempotent processing

pykicak is designed for idempotent agents only. It delivers every message at least once, never exactly once: it never loses a message, and the price is that a message can be processed, and its results published, more than once. Every agent built on pykicak must therefore be idempotent: processing the same message twice, or twice at the same time, must leave the system in the same state as processing it once. Using pykicak for processing that is not idempotent can corrupt data or repeat external actions.

A message is processed more than once when:

• an Executor is killed or stopped without stop() (crash, SystemExit, KeyboardInterrupt, a supervisor's forced kill) while it processes a message, so RabbitMQ redelivers the message, which is executed again, and its results are published again if they had already been published; a graceful stop() finishes the message first and avoids this;
• the connection is lost while an Executor publishes its results, so the input is executed again;
• execute() runs longer than heartbeat_seconds, so the input is redelivered while it is still being executed, and with several instances it runs concurrently on another instance;
• execute() raises TransientProcessingError, so it is called again, and requeued after max_processing_attempts failed calls, so it is executed again later;
• RabbitMQ refuses an Executor's results (UnroutableError or NackError), so the input is requeued and executed again, and results confirmed before the refusal are published again;
• the acknowledgement fails, for example because the connection was lost right after the results were published, so RabbitMQ redelivers the input, which is executed again and its results published again;
• an Injector loses its connection before RabbitMQ confirms a message, so it publishes the message again.

What this requires from an application:

• Idempotent side effects in execute(). Enforce them in the database (unique constraints, upserts keyed by a message ID), not by checking first and writing afterwards, which fails when two instances run the same message concurrently. This includes partial work done by a call that then raises TransientProcessingError.
• Stable message IDs. Every message has a required message_id (see Message types). Give each message a unique ID when it is first created, and derive the IDs of results from the input's ID (for example with uuid.uuid5), not from uuid4(), so that executing an input again produces results with the same IDs, which downstream agents can deduplicate.
• Idempotent downstream agents. Every Executor in a pipeline receives duplicates, so the requirement applies to all of them.
• No at-most-once actions without a deduplication key. Actions that must not be repeated, such as sending an email, charging a payment, or calling a non-idempotent API, need an idempotency key derived from the message ID, or must not be performed by a pykicak agent.

Installation

pip install pykicak

Requires Python 3.12+. Depends on pika for the RabbitMQ connection.

Configuration: the .kicak file

Applications load RabbitMQ connection details with KicakConfig.from_file(path) and pass the resulting config to an agent. The library does not select a config path or read environment variables. A .kicak file is a simple KEY=VALUE text file, read as UTF-8 on every platform (a leading byte order mark is allowed); blank lines and lines starting with # are ignored. See .kicak.example for a template.

Key	Description
RABBIT_MQ_USERNAME	RabbitMQ username
RABBIT_MQ_PASSWORD	RabbitMQ password
RABBIT_MQ_HOST	RabbitMQ host
RABBIT_MQ_PORT	RabbitMQ port
RABBIT_MQ_VIRTUAL_HOST	RabbitMQ virtual host

Never commit a real .kicak file; .kicak files are excluded by .gitignore.

Missing or unreadable files, invalid UTF-8, malformed lines (including a line with an empty key), duplicate keys, and missing required keys raise KicakConfigError. The port is converted to an integer when rabbitmq_port is accessed, and a value that is not an integer from 1 to 65535 also raises KicakConfigError.

KicakConfig keeps values out of its repr() and its errors, so they do not reach logs or crash reporters: the repr lists only the keys (KicakConfig(keys=['RABBIT_MQ_HOST', ...])), and a malformed line or invalid value is reported by its line number or key, never its content.

The .kicak file does not hold queue, exchange, or binding names — that is application topology, not connection configuration. See RabbitMQ topology below.

RabbitMQ topology

Queue and exchange names are declared outside the Kicak abstract classes, in your application's own messaging/ module (e.g. messaging/queues.py, messaging/exchanges.py, messaging/bindings.py), and passed into agent constructors in code. This keeps a single owner for each queue/exchange name, so independent agents reference the same definitions instead of inventing their own. See examples/poc/messaging/ for a worked example.

Constructor arg	Used by	Description
exchange_name	KicakInjectorAbstract (required)	Exchange to publish messages to
source_queue	KicakExecutorAbstract (required)	Queue to consume messages from
source_exchange	KicakExecutorAbstract (required)	Upstream exchange source_queue is bound to
dead_letter_exchange	KicakExecutorAbstract (required)	Exchange that rejected deliveries from source_queue are routed to
dead_letter_queue	KicakExecutorAbstract (required)	Queue bound to dead_letter_exchange that retains rejected deliveries
destination_exchange	KicakExecutorAbstract (optional)	Exchange that the results returned by execute() are published to
queue_type	KicakExecutorAbstract (optional, default QueueType.CLASSIC)	RabbitMQ type of both source_queue and dead_letter_queue: QueueType.CLASSIC or QueueType.QUORUM (see Queue type)
max_processing_attempts	KicakExecutorAbstract (optional, default 3)	How many times execute() is called for one delivery while it raises TransientProcessingError, before the delivery is requeued (see Error handling and dead-lettering)
heartbeat_seconds	KicakExecutorAbstract (optional, default 600)	Heartbeat timeout of the Executor's connections; must exceed the longest execute() (see Long-running execute())

Constructor arguments after config are keyword-only, for both the Injector and the Executor (exchange_name="...", source_queue="...", and so on). An Executor declares its own durable input queue of type queue_type with the x-dead-letter-exchange argument set to dead_letter_exchange, and binds that queue to the durable fanout source exchange. It also declares the durable fanout dead-letter exchange and the durable dead-letter queue, of the same type, bound to it, so rejected messages are kept for inspection or replay. It may also declare a durable fanout destination_exchange. Executors never create or bind downstream queues. Each downstream consumer owns its queue and binding. Omit destination_exchange for terminator mode.

The dead-letter exchange must differ from the source and destination exchanges, and the dead-letter queue must differ from the source queue.

The library assumes this deployment model:

• Each queue belongs to one Executor type, which can run as several instances. To scale an Executor, run more processes of it with the same configuration; they consume from the same queue and RabbitMQ shares its messages between them (see Scaling an Executor).
• Permanent topology. Once declared, exchanges and queues stay in the broker, and agents never delete them. Agents declare their topology idempotently each time they connect, including every reconnection, so an agent still running recreates anything removed in the meantime. To redesign the topology, stop injecting, let the Executors drain every queue, stop every instance with stop(), remove the whole structure, then start the new Executors, which declare the new structure.
• Topology installed before publishing. Start each Executor at least once before anything publishes to its source exchange. Until its queue is declared and bound, publishing to that exchange fails with UnroutableError (see Delivery guarantees).

RabbitMQ queue arguments cannot change after a queue is created. If source_queue already exists without the same x-dead-letter-exchange argument, or either queue exists with another queue type, connecting fails with 406 PRECONDITION_FAILED and is not retried. Delete the old queue (after draining it) before deploying an Executor that declares it differently.

Queue type

queue_type selects the RabbitMQ queue type of the Executor's input queue and its dead-letter queue; both always have the same type. Pass a member of the exported QueueType enum:

• QueueType.CLASSIC (the default) is a queue stored on one broker node.
• QueueType.QUORUM is a queue replicated across the nodes of a RabbitMQ cluster, which keeps its messages when a node fails. It also works on a single node.

from pykicak import QueueType

executor = ClassifyingExecutor(
    config,
    source_queue="classifier",
    source_exchange="items.inbox",
    dead_letter_exchange="classifier.dlx",
    dead_letter_queue="classifier.dlq",
    destination_exchange="items.classified",
    queue_type=QueueType.QUORUM,
)

QueueType is a string enum, so the values "classic" and "quorum" work too, for example when the type comes from your own configuration; any other value raises ValueError.

The type is always declared explicitly (x-queue-type), so a default queue type configured for the vhost never applies. Queues declared without a type, for example by another tool, are classic queues and keep working with the default QueueType.CLASSIC. To change the type of an existing queue, follow the topology redesign steps above: drain it, stop every instance, delete the queue, then start the Executors with the new queue_type.

Quorum queues count the deliveries of each message. On RabbitMQ 4.0 and newer they apply a default delivery limit of 20: a message delivered 21 times is dead-lettered with the x-death reason delivery_limit instead of being delivered again. Every requeue counts, whether after TransientProcessingError exhausted max_processing_attempts, or after a lost connection or a hard stop. A classic queue has no such limit and requeues a message indefinitely. The limit can be changed with a RabbitMQ policy (delivery-limit).

Message types

Messages sent and received by agents are declared as KicakMessage subclasses, independent of any agent class, so the same type can be imported by both the publishing side (injector/executor) and the consuming side (executor):

import dataclasses
from pykicak import KicakMessage

@dataclasses.dataclass(frozen=True, slots=True)
class CrawledItem(KicakMessage):
    url: str
    content: str

item = CrawledItem(url="https://example.com", content="...", message_id="5f0c7b1e-...")

Every message has a message_id, a field that KicakMessage declares for all message types, so your classes do not declare it. Idempotent processing depends on it (see Requirement: idempotent processing):

• It is required and keyword-only, with no default. A generated default would give the results of a re-executed input new IDs, so each message's creator chooses it: a new ID (for example str(uuid.uuid4())) where a message is first created, and an ID derived from the input's ID for the results of an Executor.
• It must be a non-empty string of at most 255 bytes in UTF-8; otherwise creating the message raises TypeError or ValueError, and a received message is dead-lettered as malformed.
• It is sent in the message body and as the AMQP message_id property, and the library includes it in its log records.

A message class that defines __post_init__ must call KicakMessage.__post_init__(self), which validates the ID. Zero-argument super() does not work in a slots=True dataclass on Python 3.12.

Fields must be JSON-serializable (store timestamps as ISO-8601 strings, not datetime objects). Decoding checks that the body is a JSON object with exactly the class's fields; it does not convert or check the types of their values, so a nested dataclass, for example, is decoded as a dict. Validate values in execute() and raise MalformedMessageError for invalid ones.

Usage

The examples use the CrawledItem message defined above and literal topology names for brevity. In an application, define these names centrally in its messaging/ module as described in RabbitMQ topology.

Executor (terminator mode — no publishing):

from pykicak import (
    KicakConfig,
    KicakExecutorAbstract,
    MalformedMessageError,
    TransientProcessingError,
)

class SaveToDbExecutor(KicakExecutorAbstract[CrawledItem]):
    def message_type(self) -> type[CrawledItem]:
        return CrawledItem

    def execute(self, message: CrawledItem) -> None:
        if not message.url:
            raise MalformedMessageError("url is empty")  # dead-lettered
        try:
            ...  # upsert the item into a database, keyed by message.message_id
        except ConnectionError as error:
            raise TransientProcessingError("database unavailable") from error  # retried
        return None  # a terminator publishes nothing

config = KicakConfig.from_file(".kicak")
executor = SaveToDbExecutor(
    config,
    source_queue="db-writer",
    source_exchange="items.inbox",
    dead_letter_exchange="db-writer.dlx",
    dead_letter_queue="db-writer.dlq",
)
executor.run()

Injector (publishes an initial message):

import uuid

from pykicak import KicakConfig, KicakInjectorAbstract

class StartProcessingInjector(KicakInjectorAbstract):
    def generate(self) -> CrawledItem:
        # A new ID where the message is first created; it never changes afterwards
        return CrawledItem(message_id=str(uuid.uuid4()), url="https://example.com", content="...")

config = KicakConfig.from_file(".kicak")
injector = StartProcessingInjector(config, exchange_name="items.inbox")
injector.run()  # publishes once, then returns

Each injection is short-lived. run() calls generate() and, if it returns a message, opens a connection, publishes the message, waits for RabbitMQ's confirmation, and closes the connection. If generate() returns None, no connection is opened. Connecting and publishing are attempted up to three times: immediately, after 1 second, and after 2 more seconds, each time on a new connection and with the same message.

run() returns normally only if the message was injected. Otherwise it closes the connection and raises InjectionError. Its __cause__ is the error that ended the last attempt, for example pika.exceptions.UnroutableError when no queue is bound to the exchange yet, or a pika connection error when RabbitMQ is unreachable. Its message attribute is the message that was not injected, and its text names the message type and message_id, never the payload. Catch it to learn that the message was not injected:

from pykicak import InjectionError

try:
    injector.run()
except InjectionError as error:  # nothing was injected; the connection is already closed
    ...  # e.g. return an error to the API caller, or exit with a non-zero status

publish(), used with connect() or a with block, raises InjectionError in the same way. It raises RuntimeError without a connection, including after close() or the end of the with block. Errors from your own generate(), or from serializing its message, are not wrapped and propagate unchanged, because they are application bugs rather than delivery failures.

injector.run(interval_seconds=60) repeats the injection every 60 seconds until the process ends; there is no stop(). No connection is kept open between injections, so the interval is not limited by RabbitMQ's heartbeat. A failed injection ends run() with its error, as above, so no message is skipped silently.

Executor (with publishing to an exchange):

import dataclasses
import uuid

from pykicak import KicakConfig, KicakExecutorAbstract, KicakMessage

@dataclasses.dataclass(frozen=True, slots=True)
class ClassifiedItem(KicakMessage):
    url: str
    category: str

class ClassifyingExecutor(KicakExecutorAbstract[CrawledItem]):
    def message_type(self) -> type[CrawledItem]:
        return CrawledItem

    def execute(self, message: CrawledItem) -> ClassifiedItem:
        # The result's ID is derived from the input's, so executing the input again
        # publishes a result with the same ID, which downstream agents can deduplicate
        result_id = uuid.uuid5(uuid.NAMESPACE_URL, f"classified:{message.message_id}")
        return ClassifiedItem(message_id=str(result_id), url=message.url, category="news")

config = KicakConfig.from_file(".kicak")
executor = ClassifyingExecutor(
    config,
    source_queue="classifier",
    source_exchange="items.inbox",
    dead_letter_exchange="classifier.dlx",
    dead_letter_queue="classifier.dlq",
    destination_exchange="items.classified",
)
executor.run()

execute() returns a message, a sequence of messages, or None. The Executor publishes the results itself, only after execute() succeeds, so a failed message never produces partial output.

Subclassing KicakExecutorAbstract[CrawledItem] tells type checkers that execute() receives a CrawledItem. A subclass of the plain KicakExecutorAbstract works too; its execute() then receives a KicakMessage.

All queues/exchanges are declared automatically (idempotently) when the agent connects.

Error handling and dead-lettering

The Executor decides the outcome of every delivery from how execute() ends:

Outcome	Cause	Delivery is…	Executor
Success	execute() returns	results published, then acknowledged	continues
Deterministic failure	missing body, undecodable body (not a JSON object, missing or unexpected fields, no valid message_id), or MalformedMessageError raised by execute()	rejected with basic_nack(requeue=False), so RabbitMQ routes it to the dead-letter exchange	continues
Transient failure	TransientProcessingError raised by execute()	retried in-process; if every attempt fails, requeued with basic_nack(requeue=True)	continues
Unexpected failure	any other exception from execute(), or results that are not KicakMessages, cannot be serialized, or are returned by a terminator	dead-lettered as above	logs the error and raises it, stopping
Results refused by RabbitMQ	UnroutableError (no queue bound to the destination exchange) or NackError while publishing results	requeued with basic_nack(requeue=True); the message is not at fault	logs the error and raises it, stopping
Connection lost while publishing results	a transient connection error from a result publish	already requeued by RabbitMQ when the connection dropped; the results are discarded, not re-sent	reconnects and receives the message again

execute() is called up to max_processing_attempts times (default 3) while it raises TransientProcessingError, with 0.5- and 1.0-second delays that double up to a 30-second cap. A requeued message is delivered again later. With a classic queue, a failure that never clears keeps being retried; a quorum queue dead-letters the message once it reaches its delivery limit (see Queue type).

Dead-lettered messages keep their original body. RabbitMQ adds an x-death header recording the source queue and the reason: rejected when the Executor rejected the message, which it logs at ERROR level, or delivery_limit when a quorum queue's delivery limit was reached.

Results are published before the delivery is acknowledged, so no result is lost. If the process stops between the two, RabbitMQ redelivers the message and its results are published again; this is one of the reasons agents must be idempotent (see Requirement: idempotent processing).

The Executor never re-sends a result on a new connection. An acknowledgement can only be sent on the channel that delivered the message, and RabbitMQ requeues the delivery as soon as that connection is lost. Re-sending the results would therefore always duplicate them once the message is executed again. Instead, the Executor discards the results, reconnects, and executes the redelivered message, publishing its results once. Results that RabbitMQ had already confirmed before the connection was lost are published again with the rest.

Running and stopping an Executor

The Executor takes one message at a time: it sets a prefetch count of 1, so RabbitMQ delivers the next message only after the previous one has been acknowledged or rejected. Messages waiting in the queue are therefore never held, unprocessed, by the Executor, and their RabbitMQ delivery timeout does not start early.

run() consumes until you call stop(), and then returns normally.

Graceful stop

stop() asks the Executor to finish its current work and then return from run() without taking another message:

• While a message is being processed, the Executor finishes it: execute() completes, its results are published, and the message is acknowledged (or requeued or dead-lettered, as usual). run() then returns instead of waiting for the next message.
• While waiting for a message, run() returns within about a second, without taking one.
• While reconnecting after a lost connection, run() stops retrying and returns within about a second.
• A message delivered after the stop request, before the Executor notices it, is not processed; RabbitMQ returns it to the queue when the connection closes.

stop() only sets a flag, so it is safe to call from any thread and from a signal handler. Connect it to the signals your process supervisor sends, for example:

import signal

executor = ClassifyingExecutor(config, ...)  # topology arguments as above
for stop_signal in (signal.SIGINT, signal.SIGTERM):
    signal.signal(stop_signal, lambda _signum, _frame: executor.stop())
executor.run()  # returns after the message in progress, once a signal arrives

The stop request is permanent: calling run() on a stopped Executor returns immediately. Create a new instance to consume again.

Give your supervisor's shutdown timeout (for example Kubernetes' terminationGracePeriodSeconds) at least the longest execute() plus a few seconds; otherwise it kills the process in the middle of a message.

Other ways run() ends

Without a stop request, run() ends only by raising:

• a failure, as described above;
• RuntimeError if RabbitMQ cancels the consumer, which happens when the queue is deleted while the Executor runs. The Executor does not recreate the queue; under the permanent-topology model this is an error for an operator to investigate;
• a BaseException such as SystemExit or KeyboardInterrupt, for example Python's default reaction to Ctrl+C when no signal handler calls stop(). This is a hard stop: the exception passes through unchanged, even in the middle of execute(), the connection is closed, and RabbitMQ requeues the message being processed, which is then executed again.

Status and timestamp

An Executor reports its lifecycle status, for example to a health check or a monitoring thread:

get_status()	Meaning
"RUNNING"	Set when the Executor is created; stays while run() consumes, until stop() is called.
"STOPPING"	stop() was called; run() finishes the message in progress, then returns.
"STOPPED"	run() returned after a graceful stop.
"CRASHED"	run() ended by raising an exception: a failure or a hard stop.

get_status() returns a plain string. The values are also available as the ExecutorStatus string enum, so executor.get_status() == ExecutorStatus.STOPPED works too. "STOPPED" and "CRASHED" are final: a later stop() does not change them. Calling run() again after "CRASHED", without a stop request, makes the Executor "RUNNING" again.

get_timestamp() returns when the status last changed or was last read by get_status(), as an ISO 8601 string in UTC, for example "2026-10-01T17:05:42.123456+00:00". Calling get_timestamp() does not update it, so a monitor that calls get_status() regularly can tell when it last checked.

status = executor.get_status()        # "RUNNING"; also updates the timestamp
checked_at = executor.get_timestamp() # e.g. "2026-10-01T17:05:42.123456+00:00"

Both methods are safe to call from any thread while run() is running, and neither uses the RabbitMQ connection.

Long-running execute()

RabbitMQ uses heartbeats to detect dead connections, and pika can answer them only between messages, never while execute() runs. If one execute() call lasts longer than the connection's heartbeat timeout, RabbitMQ closes the connection and requeues the message while it is still being processed. The work is wasted and the message is executed again, so an execute() that always takes that long never completes. An Executor that publishes results discards them and reconnects; a terminator's acknowledgement fails on the closed connection, which stops it.

Only the application knows how long its processing takes, so each Executor type sets its own timeout with heartbeat_seconds, in seconds. It defaults to 600 (10 minutes), sized for LLM calls and heavy computation, and RabbitMQ uses the requested value even when its own default is lower. Choose a value comfortably above the longest execute() you expect for that Executor type:

executor = ClassifyingExecutor(
    config,
    source_queue="classifier",
    source_exchange="items.inbox",
    dead_letter_exchange="classifier.dlx",
    dead_letter_queue="classifier.dlq",
    destination_exchange="items.classified",
    heartbeat_seconds=1800,  # this classifier can take up to 20 minutes per item
)

Consider these when choosing the value:

• A larger value detects dead connections later. If an Executor's host or network disappears without closing the connection, RabbitMQ redelivers its in-flight message only after up to heartbeat_seconds.
• RabbitMQ has a separate limit on unacknowledged messages. The broker's consumer_timeout (30 minutes by default) closes the channel of a consumer that holds a message unacknowledged for longer, and requeues the message. If execute() can take longer than that, raise consumer_timeout on the broker as well; heartbeat_seconds alone is not enough.
• AMQP limits the value to 1–65535 seconds. Injectors keep the broker's default: they hold a connection only while publishing one message, so heartbeats do not limit them.

Scaling an Executor

To process a queue faster, run several instances of the same Executor. Give every instance the same configuration (source_queue, source_exchange, dead_letter_exchange, dead_letter_queue, destination_exchange, queue_type, max_processing_attempts, and heartbeat_seconds), and start them as independent processes:

                                      ┌──► classifier instance 1 ──┐
items.inbox ──► classifier (queue) ───┼──► classifier instance 2 ──┼──► items.classified
                                      └──► classifier instance 3 ──┘

• All instances declare the same queue, binding, and dead-letter route; RabbitMQ treats identical declarations as no-ops. An instance configured differently, for example with another dead_letter_exchange or queue_type, fails to connect with 406 PRECONDITION_FAILED.
• RabbitMQ delivers each message to one instance only. With the prefetch count of 1, each instance holds only the message it is processing, so the next message goes to whichever instance is free.
• Each instance acknowledges, requeues, and dead-letters its own deliveries; no coordination is needed. A requeued message may be delivered to any instance.
• Messages are processed in parallel, so they complete, and their results are published, in no particular order.

This is different from fan-out: Executors with their own queues bound to the same exchange each receive every message.

Things to plan for when running several instances:

• The same message can be executed by two instances at the same time. When RabbitMQ redelivers a message, for example after a lost connection, another instance can receive it while the first is still running execute(). Results are still published only by the instance whose connection is intact, but side effects inside execute(), such as database writes, can happen twice concurrently. The idempotency that pykicak requires must therefore be enforced by the database (see Requirement: idempotent processing).
• An execute() longer than heartbeat_seconds causes such redeliveries. RabbitMQ closes the connection and redelivers the message while it is still being processed (see Long-running execute()). With several instances, another instance picks it up immediately.
• An unexpected error stops only the instance that hit it. Each instance dead-letters the message and stops on its own, so a bug that fails every message dead-letters one message per instance before all have stopped.

Delivery guarantees

Every channel is in publisher-confirm mode, and every message is published as mandatory and persistent (delivery_mode=2), with the content type application/json and its message_id as the AMQP message_id property. A publish returns only after RabbitMQ has taken responsibility for the message: for persistent messages in durable queues, after writing it to disk. RabbitMQ refusing a message raises one of these errors, which are not retried:

• pika.exceptions.UnroutableError: no queue is bound to the exchange, so RabbitMQ would have discarded the message. For an Injector this means the first Executor's topology is not installed.
• pika.exceptions.NackError: RabbitMQ could not take responsibility for the message.

An Injector raises InjectionError to its caller, with one of these errors as its __cause__. An Executor requeues the input message and stops (see Error handling and dead-lettering), so no message is lost between two stages of a pipeline.

A mandatory message counts as routed if at least one queue is bound to the exchange. A fanout exchange whose other bound queues are missing is not detected.

Retries and logging

Injectors retry transient RabbitMQ connection and publish failures up to three attempts, with 1- and 2-second delays between attempts; each retry publishes the message again on a new connection, and after the third failed attempt the error is raised. Executors reconnect indefinitely after transient failures, using exponential full jitter with a 0.5-second initial delay and a 30-second maximum, but never retry a result publish (see Error handling and dead-lettering). Authentication and access-denied failures are not retried. Application processing is retried only for TransientProcessingError (see Error handling and dead-lettering). Message acknowledgements are not retried; a failed connection can cause an unacknowledged message to be delivered again by RabbitMQ.

Publishing is at-least-once: if the connection is lost before RabbitMQ's confirmation arrives, RabbitMQ may already have accepted the message. The Injector then publishes it again, and the Executor executes the redelivered input again. pykicak does not provide exactly-once delivery, which is why it requires idempotent agents (see Requirement: idempotent processing).

The library emits standard Python logging records through module loggers. Applications configure handlers and levels, for example:

import logging

logging.basicConfig(level=logging.INFO)

Public API

pykicak exports ExecutorStatus, InjectionError, KicakConfig, KicakConfigError, KicakExecutorAbstract, KicakInjectorAbstract, KicakMessage, MalformedMessageError, QueueType, TransientProcessingError, and __version__. Build agents by subclassing KicakInjectorAbstract or KicakExecutorAbstract; their shared base class is internal.

Proof of concept

examples/poc/ in the repository contains a runnable example (examples are not part of the installed package): an injector that publishes a heartbeat message, an executor that publishes it to a fan-out exchange, and two terminator executors that each declare their own queue and bind it to that exchange. Each executor also declares a dead-letter exchange and queue for its input queue (for example poc.heartbeat.source.dlx → poc.heartbeat.source.dlq). Start all three executors (at least once) before running the injector: until the fan-out executor has declared its queue, the injector fails with UnroutableError, and until a terminator has declared its queue, the fan-out executor requeues the message and stops. The queue/exchange topology is defined once in examples/poc/messaging/ (queues.py, exchanges.py, bindings.py) and imported by every agent — none of it lives in .kicak.

Each process reads its .kicak file (connection details only) from the path in the KICAK_CONFIG_PATH environment variable (defaulting to .kicak). The executor's role is selected via POC_EXECUTOR_ROLE (fanout, terminator1, or terminator2). Ctrl+C or SIGTERM stops an executor gracefully through stop(). Run the commands from the repository root:

KICAK_CONFIG_PATH=.kicak.injector python -m examples.poc.injector_agent
KICAK_CONFIG_PATH=.kicak.executor POC_EXECUTOR_ROLE=fanout python -m examples.poc.executor_agent
KICAK_CONFIG_PATH=.kicak.terminator1 POC_EXECUTOR_ROLE=terminator1 python -m examples.poc.executor_agent
KICAK_CONFIG_PATH=.kicak.terminator2 POC_EXECUTOR_ROLE=terminator2 python -m examples.poc.executor_agent

Development

Install the package in editable mode with the development tools (pytest, ruff, mypy, build, and twine), then run the test suite and the checks:

pip install -e . --group dev   # pip 25.1 or newer
pytest
ruff check .
mypy

This excludes integration tests, which require a live RabbitMQ broker (e.g. docker run -p 5672:5672 rabbitmq). They connect with the .kicak file in the working directory, or the one whose path is in the KICAK_CONFIG_PATH environment variable; with the container above, a copy of .kicak.example works as it is. Run them explicitly with:

pytest -m integration

License

pykicak is released under the MIT License.