Reliability & rate limiting
Retries, exponential backoff, circuit breakers, token buckets, and idempotent handlers.
Rate Limiting in Python with a Sliding Window
A beginner-friendly dataclass-based sliding window rate limiter that controls how many calls are allowed per time window.
import time
from dataclasses import dataclass
@dataclass
class RateLimiter:
max_calls: int
window_seconds: float = 1.0
def __post_init__(self):
self.calls = []
self._start = time.monotonic()
def _update(self, now):
self.calls = [t for t in self.calls if now - t < self.window…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
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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.