Reference library

Python Code Samples

Medium snippets you can copy, study, and run in the browser editor.

4 matches
System design patterns medium

Simulate a Leaky Bucket Rate Limiter in Python

This code implements a leaky bucket rate limiter that drains at a fixed rate and accepts or rejects incoming requests based on capacity.

rate limiting leaky bucket simulation
Python
import time
from collections import deque


class LeakyBucket:
    """Simulates a leaky bucket rate limiter with a fixed drain rate."""
    def __init__(self, capacity, drain_rate_per_sec):
        self.capacity = capacity
        self.drain_rate = drain_rate_per_sec
        self.water = 0.0
        self.last_refill =…
13 0 Open
Caching & Redis medium

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.

rate-limiting redis algorithms
Python
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(…
14 0 Open
Reliability & rate limiting medium

GCRA generic cell rate algorithm in Python

Mock implementation of the Generic Cell Rate Algorithm (GCRA) for traffic shaping and rate limiting.

gcra rate-limiting traffic-shaping
Python
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…
14 0 Open
Reliability & rate limiting medium

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.

rate-limiting api time-window
Python
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):
       …
13 0 Open

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