Reference library

Reliability & rate limiting

Retries, exponential backoff, circuit breakers, token buckets, and idempotent handlers.

3 matches

At Least Once with Idempotent Consumer in Python

Implements a thread-safe idempotent consumer that processes each unique message exactly once, even when a producer sends duplicates under an at-least-once delivery model.

idempotency at-least-once threading

Python

import threading
import time
import uuid
from collections import Counter


class IdempotentConsumer:
    def __init__(self):
        self.processed = set()
        self._lock = threading.Lock()

    def consume(self, message_id, payload):
        with self._lock:
            if message_id in self.processed:
          …

16 0 Open

Reliability & rate limiting medium

How to Send Messages to a Dead Letter Queue in Python

Simulates a poison message queue that retries failed messages up to a limit before moving them to a dead letter queue.

dlq message queue retries

Python

import json

class PoisonMessageQueue:
    def __init__(self, max_retries=3):
        self.dlq = []
        self.max_retries = max_retries
        self.processed_count = 0
        self.failed_count = 0

    def process_message(self, message_body):
        if "poison" in message_body:
            self.failed_count += 1…

15 0 Open

Reliability & rate limiting medium

How to Simulate an Outbox Pattern with Reliable Retry in Python

This code implements a mock outbox pattern with records, delivery attempts, and retries to simulate reliable message publishing.

outbox retry messaging

Python

import time
import itertools

class Outbox:
    def __init__(self):
        self._records = []
        self._seq = itertools.count(1)

    def publish(self, topic, payload):
        record = {
            "id": next(self._seq),
            "topic": topic,
            "payload": payload,
            "status": "pending"…

14 0 Open

Browse by section

Each section groups closely related Python snippets.