Reliability & rate limiting
Retries, exponential backoff, circuit breakers, token buckets, and idempotent handlers.
How to Cap Retry Attempts in Python with a Decorator
Build a reusable retry decorator that caps attempts, adds delays, and lets flaky services fail fast instead of hanging.
import random
from functools import wraps
from time import sleep
def retry(max_attempts, delay=0.1):
def decorator(func):
@wraps(func)
def wrapper(*args, **kwargs):
attempts = 0
while attempts < max_attempts:
try:
return func(*args, **kw…How to Implement an Adaptive Rate Limiter in Python
Build an adaptive rate limiter that adjusts request intervals dynamically based on recent error rates, slowing down when failures spike.
import time
import random
class AdaptiveRateLimiter:
"""Simple adaptive rate limiter that reduces requests when error rate is high."""
def __init__(self, min_interval=0.1, max_interval=2.0, error_threshold=0.3):
self.min_interval = min_interval
self.max_interval = max_interval
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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.