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How to Implement a Token Bucket Rate Limiter with asyncio in Python
This code implements a thread-safe token bucket rate limiter for asyncio, allowing you to limit the rate of async tasks or API calls.
import asyncio
import time
class TokenBucket:
def __init__(self, rate_per_second, capacity):
self.rate = rate_per_second
self.capacity = capacity
self.tokens = capacity
self.last_refill = time.monotonic()
self.lock = asyncio.Lock()
async def acquire(self):
asy…How to Handle Retry-After Header in Python
Parse the Retry-After header from rate-limited API responses and implement retry logic with proper delays in Python.
```python
import time
from datetime import datetime, timedelta
class RetryAfterHandler:
def __init__(self, max_retries=3):
self.max_retries = max_retries
def get_retry_after_seconds(self, response_headers):
retry_after_value = response_headers.get("Retry-After")
if retry_after_value …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,…Redis Leaky Bucket Rate Limiting Mock in Python
Simulates a Redis-backed leaky bucket rate limiter using a local class with continuous leaking and token capacity checks.
import time
from collections import deque
class LeakyBucket:
def __init__(self, capacity, leak_rate):
self.capacity = capacity
self.leak_rate = leak_rate
self.water = 0.0
self.timestamp = time.time()
self.history = deque()
def allow(self):
current = time.time(…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 >=…GCRA generic cell rate algorithm in Python
Mock implementation of the Generic Cell Rate Algorithm (GCRA) for traffic shaping and rate limiting.
from collections import deque
import time
class GCRA:
def __init__(self, rate, burst):
self.tau = burst
self.T = rate
self.t = 0
self.LCT = 0
def add_cell(self, arrival_time):
if arrival_time <= self.t:
return False
arrived_early = (arrival_time - s…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 Bulkhead Pattern with Threading in Python
Implement a bulkhead pattern in Python that isolates concurrent tasks with a bounded semaphore, limiting active workers to prevent resource exhaustion.
import threading
import time
import random
class Bulkhead:
def __init__(self, workers: int):
self._semaphore = threading.BoundedSemaphore(workers)
self._lock = threading.Lock()
self._active = 0
def run(self, task):
with self._semaphore:
with self._lock:
…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 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 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 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 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 a rate-limited shared counter in Python
Implements a thread-safe global counter that allows a maximum number of increments per second using a lock and time-based refill.
import threading
import time
import random
counter = 0
lock = threading.Lock()
MAX_CALLS_PER_SECOND = 3
last_refill = time.time()
def rate_limited_increment():
global counter, last_refill
with lock:
now = time.time()
if now - last_refill >= 1.0:
last_refill = now
count…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…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):
…Leaky Bucket Rate Limiter in Python: Smooth Burst Traffic
Implements a token-bucket-style leaky bucket rate limiter that smooths bursty traffic by draining at a fixed rate and dropping excess packets.
import time
import random
class LeakyBucket:
def __init__(self, capacity, drain_rate):
self.capacity = capacity
self.drain_rate = drain_rate
self.water = 0.0
self.last_time = time.time()
def allow(self, packet_size=1.0):
now = time.time()
elapsed = now - self.…Mock Distributed Rate Limiter with Dict in Python
Simulates a distributed token-bucket rate limiter with a thread-safe dict, useful for testing before moving to Redis.
import time
import threading
from collections import defaultdict
class DistributedRateLimiter:
"""
A mock distributed rate limiter using a dict with thread-safe access.
Implements a token bucket algorithm per user.
"""
def __init__(self, rate_per_second=5, burst_capacity=10):
self.rate_p…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…Browse by section
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