Reliability & rate limiting
Retries, exponential backoff, circuit breakers, token buckets, and idempotent handlers.
How to Propagate Context Variables with asyncio in Python
Use Python's ContextVar with asyncio to carry deadline information across concurrent tasks and propagate context automatically.
import asyncio
from contextvars import ContextVar
from datetime import datetime
deadline = ContextVar("deadline", default=None)
async def worker(name):
current = deadline.get()
if current:
print(f"{name} sees deadline: {current}")
else:
print(f"{name} sees no deadline")
await asyncio.…How to implement rate limiting in Python
Build a simple sliding-window rate limiter in Python that enforces a max number of calls per time period and formats data with timestamps.
import time
class RateLimiter:
def __init__(self, max_calls, period):
self.max_calls = max_calls
self.period = period
self.calls = []
def allow(self):
now = time.time()
# Remove calls older than the period window
self.calls = [t for t in self.calls if now -…Browse by section
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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.