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How to Implement Retry with Exponential Backoff for Cloud API 429 Errors in Python
Implement a retry-with-backoff loop in Python to handle 429 throttling errors from cloud APIs, using exponential delay between attempts.
import time
import random
import requests
def api_call(attempt):
"""Mock cloud API that returns 429 for the first two attempts."""
if attempt < 2:
return 429, "Too Many Requests"
return 200, {"data": "success"}
def retry_with_backoff(api_func, max_retries=3, base_delay=0.1):
for attempt in …
How to implement a token bucket rate limiter in Python
A thread-safe in-memory token bucket rate limiter that tracks per-key tokens with refill logic, including a usage example after a timed refill.
import time
import threading
class TokenBucketRateLimiter:
def __init__(self, capacity, refill_rate):
self.capacity = capacity
self.refill_rate = refill_rate
self.tokens = capacity
self.last_refill_time = time.time()
self.lock = threading.Lock()
def allow_request(self,…
Build a Rate Limiter Decorator in Python
This code defines a reusable rate limiter decorator that caps function calls within a sliding time window using a deque and monotonic time.
import time
from collections import deque
def rate_limiter(max_calls: int, period: float):
calls = deque()
def decorator(func):
def wrapper(*args, **kwargs):
now = time.monotonic()
while calls and now - calls[0] >= period:
calls.popleft()
if len(ca…
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 Build a Rate Limiter in Python
A beginner-friendly token bucket rate limiter with retry logic for handling API rate limits in Python.
import time
import random
class RateLimiter:
"""Simple token bucket rate limiter for beginners."""
def __init__(self, max_tokens=5, refill_rate=1.0):
self.max_tokens = max_tokens
self.tokens = max_tokens
self.refill_rate = refill_rate # tokens per second
self.last_refill …
How to Build a Rate Limiter in Python
Implements a simple sliding-window rate limiter that caps the number of calls per period, used to throttle processing of a data list.
import time
class RateLimiter:
def __init__(self, max_calls, period):
self.max_calls = max_calls
self.period = period
self.timestamps = []
def allow(self):
now = time.time()
self.timestamps = [t for t in self.timestamps if now - t < self.period]
if len(self.tim…
How to Implement a Rate Limiter in Python
A beginner-friendly Python class that tracks call timestamps with a deque to allow or block calls based on a max rate per time period.
import time
from collections import deque
class RateLimiter:
"""Simple rate limiter for beginners."""
def __init__(self, max_calls: int, period_seconds: float):
self.max_calls = max_calls
self.period = period_seconds
self.calls = deque()
def allow(self) -> bool:
"""Retur…
How to Implement a Sliding Window Counter in Python
This code implements an approximate sliding window counter using a deque of time-based buckets to track event counts within a recent time window.
from collections import deque
from time import time
class SlidingWindowCounter:
def __init__(self, window_size, bucket_size=1):
self.window_size = window_size
self.bucket_size = bucket_size
self.buckets = deque()
def _evict_expired(self, now):
while self.buckets and self.buck…
How to Implement a Temporary Block in Python
Build a reusable PenaltyBox class that temporarily blocks access after a failure and reports remaining lockout time.
class PenaltyBox:
def __init__(self, block_seconds: int = 30):
self.block_seconds = block_seconds
self._blocked_until = 0.0
self._attempts = 0
def try_access(self, current_time: float) -> bool:
if self._blocked_until and current_time < self._blocked_until:
return Fa…
How to Mock Daily and Monthly Quota Counters in Python
Track daily and monthly API call usage with automatic resets, quota checks, and limits using a Python class.
import random
from datetime import datetime, timedelta
class QuotaCounter:
def __init__(self, daily_limit=1000, monthly_limit=20000):
self.daily_limit = daily_limit
self.monthly_limit = monthly_limit
self.daily_usage = 0
self.monthly_usage = 0
self.current_day = datetime.n…
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 -…
How to implement rate limiting in Python
A beginner-friendly Python rate limiter that throttles API calls and retries parsing tasks with exponential backoff.
import time
import random
class RateLimiter:
def __init__(self, max_calls, per_seconds):
self.max_calls = max_calls
self.per_seconds = per_seconds
self.timestamps = []
def allow(self):
now = time.time()
self.timestamps = [t for t in self.timestamps if now - t < sel…
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…
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…
Rate Limiting with a Simple Python RateLimiter Class
A beginner-friendly Python rate limiter that tracks call timestamps and enforces a maximum number of calls within a rolling time window, with a helper to validate positive integers.
import time
class RateLimiter:
def __init__(self, max_calls, period_seconds):
self.max_calls = max_calls
self.period_seconds = period_seconds
self.calls = []
def is_allowed(self):
now = time.time()
while self.calls and now - self.calls[0] >= self.period_seconds:
…
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