Reliability & rate limiting
Retries, exponential backoff, circuit breakers, token buckets, and idempotent handlers.
Build a Rate Limiter Decorator in Python
This code defines a reusable rate limiter decorator that caps function calls within a sliding time window using a deque and monotonic time.
import time
from collections import deque
def rate_limiter(max_calls: int, period: float):
calls = deque()
def decorator(func):
def wrapper(*args, **kwargs):
now = time.monotonic()
while calls and now - calls[0] >= period:
calls.popleft()
if len(ca…Build a queue-based admission control system in Python
Implement a simple bounded-queue admission controller that accepts or rejects incoming requests based on current queue capacity.
from collections import deque
import time
class AdmissionControl:
"""Simple admission control using a bounded queue.
Requests arrive at the queue; they are admitted in FIFO order.
If the queue is full, the incoming request is rejected.
"""
def __init__(self, capacity: int):
self.capacit…Exactly Once Processing Dedupe Mock in Python
Implements a streaming deduplicator using a set and queue to guarantee each item is processed exactly once while preserving insertion order.
from collections import deque
class DedupeStream:
def __init__(self):
self.seen = set()
self.queue = deque()
def add(self, item):
if item not in self.seen:
self.seen.add(item)
self.queue.append(item)
print(f"Processed: {item} (exactly once)")
…How to Implement Message Visibility Timeout Renewal in Python
Simulate queue message visibility control with timeout renewal using a simple Python class that tracks received time and visibility state.
import time
import uuid
class Message:
def __init__(self, body, visibility_timeout=30):
self.body = body
self.visibility_timeout = visibility_timeout
self.receipt_handle = str(uuid.uuid4())
self.received_at = time.time()
self.deleted = False
def is_visible(self):
…How to Implement a Dead Letter Queue Replay in Python
A mock Dead Letter Queue that stores failed messages with retry attempts and replays them with a simple retry counter.
import json
from collections import deque
class DeadLetterQueue:
def __init__(self):
self.messages = deque()
def add_message(self, message_id, payload, attempts=3):
"""Add a message to the DLQ with retry metadata."""
self.messages.append({
"id": message_id,
…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.
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…Rate Limiting with Queue Rejection in Python
Simulates a load shed pattern that rejects tasks when a queue fills up.
from collections import deque
import time
class RateLimiter:
def __init__(self, max_queue_size=3):
self.queue = deque()
self.max_queue_size = max_queue_size
self.rejected_count = 0
def submit(self, task_name):
if len(self.queue) >= self.max_queue_size:
self.reject…Browse by section
Each section groups closely related Python snippets.
Reliability & rate limiting — Python code examples
What you will find here
This page collects reliability & rate limiting snippets — short, copy-ready Python you can paste into our free online IDE and run without installing anything. Each sample includes a plain-English explanation and the full source code.
Samples vs tutorials and challenges
Samples are quick reference — one concept per page. For step-by-step teaching, use our Python tutorials. To test yourself, try quizzes or coding challenges. Clean up style with the Python formatter.