Reference library

Reliability & rate limiting

Retries, exponential backoff, circuit breakers, token buckets, and idempotent handlers.

6 matches
Reliability & rate limiting medium

Circuit breaker failure threshold count in Python

Track consecutive or time-windowed failures with a deque to open a circuit breaker and auto-recover to half-open after a cooldown.

circuit-breaker resilience deque
Python
from collections import deque
from time import time, sleep


class CircuitBreaker:
    def __init__(self, failure_threshold: int = 5, recovery_time: float = 10.0):
        self.failure_threshold = failure_threshold
        self.recovery_time = recovery_time
        self.failures: deque[float] = deque()
        self.st…
16 0 Open
Reliability & rate limiting medium

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.

retry decorator resilience
Python
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…
13 0 Open
Reliability & rate limiting medium

How to Implement a Circuit Breaker in Python

A Python dataclass that provides circuit breaker logic with closed, open, and half-open states to fail fast on repeated errors.

circuit-breaker resilience fault-tolerance
Python
from dataclasses import dataclass
from datetime import datetime, timedelta
import time


@dataclass
class CircuitBreaker:
    failure_threshold: int = 3
    timeout_seconds: float = 5.0
    failures: int = 0
    state: str = "closed"
    last_failure: datetime = None

    def call(self, func):
        if self.state ==…
15 0 Open
Reliability & rate limiting medium

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.

rate-limiting backoff adaptive
Python
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
        sel…
12 0 Open
Reliability & rate limiting medium

How to Mock a Circuit Breaker Reset Timeout in Python

This code implements a simple circuit breaker with a reset timeout test, simulating a flaky service to show half-open state transitions.

circuit-breaker reliability mock-testing
Python
import time
import random


class CircuitBreaker:
    def __init__(self, failure_threshold=3, reset_timeout=5):
        self.failure_threshold = failure_threshold
        self.reset_timeout = reset_timeout
        self.failure_count = 0
        self.last_failure_time = None
        self.state = "CLOSED"  # CLOSED (nor…
15 0 Open
Reliability & rate limiting medium

Implement a Circuit Breaker Pattern in Python

This code implements a simple circuit breaker that opens after a threshold of consecutive failures, causing subsequent calls to fail fast without invoking the underlying function.

circuit-breaker reliability resilience
Python
class CircuitBreaker:
    def __init__(self, failure_threshold=3):
        self.failure_threshold = failure_threshold
        self.failure_count = 0
        self.open = False

    def call(self, func, *args, **kwargs):
        if self.open:
            raise RuntimeError("Circuit is open - failing fast")
        try:
…
15 0 Open

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.