Reliability & rate limiting
Retries, exponential backoff, circuit breakers, token buckets, and idempotent handlers.
How to Mock Fault Injection Percentage in Python
Simulate a service with a 30% failure rate using random.random to test error handling and retries.
import random
class Service:
def call(self):
if random.random() < 0.3: # 30% failure rate
raise ConnectionError("Simulated network fault")
return "ok"
def main():
svc = Service()
random.seed(42) # deterministic for demonstration
results = []
for _ in range(10):
…How to Retry on Specific Exception Tuples in Python
A decorator-based retry pattern that retries a function only when it raises exceptions specified in a tuple, with configurable retries and delay.
import time
import random
from unittest.mock import patch
def retry_on_exceptions(retries=3, exceptions=(ValueError,), delay=0.1):
def decorator(func):
def wrapper(*args, **kwargs):
for attempt in range(retries):
try:
return func(*args, **kwargs)
…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…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.
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"…How to implement an idempotency key store in Python
Build an in-memory idempotency key store with TTL that processes a request once and reuses the cached result for duplicate calls.
import hashlib
import time
from typing import Dict, Optional
class IdempotencyStore:
"""Simple in-memory idempotency key store with mock processing."""
def __init__(self, ttl_seconds: int = 3600) -> None:
self.ttl = ttl_seconds
self._store: Dict[str, tuple[str, float]] = {}
def _is_expi…How to implement rate limiting in Python
A beginner-friendly Python rate limiter that throttles API calls and retries parsing tasks with exponential backoff.
import time
import random
class RateLimiter:
def __init__(self, max_calls, per_seconds):
self.max_calls = max_calls
self.per_seconds = per_seconds
self.timestamps = []
def allow(self):
now = time.time()
self.timestamps = [t for t in self.timestamps if now - t < sel…Retry with Exponential Backoff and Jitter in Python
A decorator-style retry wrapper that retries a flaky function with exponential backoff plus random jitter, then raises after the last attempt fails.
import random
import time
def retry_with_backoff(func, max_retries=3, base_delay=0.5, max_jitter=0.1):
for attempt in range(max_retries + 1):
try:
return func()
except Exception as e:
if attempt == max_retries:
raise
delay = base_delay * (2 ** at…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.