Reliability & rate limiting
Retries, exponential backoff, circuit breakers, token buckets, and idempotent handlers.
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.
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…How to Implement Hedged Requests in Python
This code demonstrates a hedged request pattern using threading, which sends duplicate calls and returns the first result that arrives within a timeout.
import time
from unittest.mock import Mock
def hedged_request(call, timeout=0.05):
"""Execute two duplicate calls, return first result within timeout."""
result_container = {}
def run_and_store():
result_container['result'] = call()
result_container['done'] = True
# Simulate slow cal…How to Implement a Sliding Window Log Rate Limiter in Python
Implements a sliding window log rate limiter in Python using a deque of timestamps to enforce a maximum request count within a rolling time window.
from collections import deque
from datetime import datetime, timedelta
from time import sleep
class SlidingWindowLog:
def __init__(self, window_seconds: int, max_requests: int):
self.window_seconds = window_seconds
self.max_requests = max_requests
self.timestamps = deque()
def allow_…How to Implement a Token Bucket Rate Limiter per Client IP in Python
Implements a simple sliding-window rate limiter using a dictionary of timestamp lists per client IP to limit requests per window.
from time import time
from collections import defaultdict
class RateLimiter:
def __init__(self, max_requests: int, window_seconds: int):
self.max_requests = max_requests
self.window_seconds = window_seconds
self.clients = defaultdict(list)
def allow(self, ip: str) -> bool:
now…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
sel…How to implement rate limiting per API key in Python
A simple sliding-window rate limiter that tracks request timestamps per API key and rejects requests exceeding the configured limit.
import time
API_RATE_LIMITS = {"api_key_1": 5, "api_key_2": 3} # max requests per window
WINDOW_SECONDS = 10
class RateLimiter:
def __init__(self, limits, window):
self.limits = limits
self.window = window
self.requests = {key: [] for key in limits}
def allow(self, api_key):
…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.
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:
…Token bucket rate limiter in Python (in-memory)
Implement a thread-safe in-memory token bucket rate limiter that throttles requests based on a steady refill rate.
import time
import threading
class TokenBucket:
def __init__(self, capacity, refill_rate, refill_interval=1.0):
self.capacity = capacity
self.tokens = capacity
self.refill_rate = refill_rate
self.refill_interval = refill_interval
self.last_refill = time.monotonic()
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Reliability & rate limiting — Python code examples
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