Reliability & rate limiting
Retries, exponential backoff, circuit breakers, token buckets, and idempotent handlers.
Build a queue-based admission control system in Python
Implement a simple bounded-queue admission controller that accepts or rejects incoming requests based on current queue capacity.
from collections import deque
import time
class AdmissionControl:
"""Simple admission control using a bounded queue.
Requests arrive at the queue; they are admitted in FIFO order.
If the queue is full, the incoming request is rejected.
"""
def __init__(self, capacity: int):
self.capacit…Fixed Window Counter Rate Limiting in Python
A simple fixed window counter rate limiter that allows a maximum number of requests per 60-second window, with a mock time simulation.
from collections import deque
from time import time
class FixedWindowCounter:
def __init__(self, max_requests):
self.max_requests = max_requests
self.window_start = int(time())
self.window_count = 0
def allow_request(self):
current_time = int(time())
if current_time >=…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 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 Stop Receiving Requests Until Ready in Python
A mock server that refuses requests until a readiness gate is passed, simulating fail-stop behavior for production reliability.
import random
import time
class MockServer:
def __init__(self):
self.ready = False
self.requests_received = 0
def readiness_check(self):
"""Simulates a readiness probe. Returns True only when ready."""
if not self.ready:
return False
return True
def r…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):
…How to mock a fallback return value in Python
Test a function that returns a default value on failure by mocking requests.get and its side effects.
from unittest.mock import Mock, patch
import requests
def fetch_data(url, default=None):
try:
response = requests.get(url)
response.raise_for_status()
return response.json()
except (requests.RequestException, ValueError):
return default
with patch("requests.get") as mock_get:
…Rate Limit per User ID in Python with a Dict Mock
Implements a simple sliding window rate limiter using a defaultdict of timestamps per user ID, blocking requests that exceed a max count within a time window.
import time
from collections import defaultdict
class RateLimiter:
def __init__(self, max_requests, window_seconds):
self.max_requests = max_requests
self.window_seconds = window_seconds
self.user_timestamps = defaultdict(list)
def allow_request(self, user_id):
now = time.tim…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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