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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 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 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…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 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:
…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()
…How to implement round-robin load balancing in Python
Implement a client-side round-robin load balancer that distributes requests sequentially across a list of mock servers using itertools.cycle.
import itertools
import random
class MockServer:
def __init__(self, name):
self.name = name
def handle_request(self, request_id):
return f"Server {self.name} handled request #{request_id}"
class RoundRobinLoadBalancer:
def __init__(self, servers):
self.servers = servers
…How to Broadcast a Small Lookup Table in Python
Simulates broadcasting a small lookup table by iterating key-value pairs and emitting packed rows to subscribers with deterministic output.
import random
# Generate a deterministic mock broadcast of a small lookup table
# with 5 keys and random integer values (seeded for reproducibility)
data = {
"sensor_a": 22,
"sensor_b": 87,
"sensor_c": 43,
"sensor_d": 65,
"sensor_e": 31,
}
# Simulate a broadcast to subscribers by iterating and p…Grid Search Hyperparameters in Python
Perform exhaustive grid search over hyperparameter combinations using itertools.product and a scoring function.
import itertools
def grid_search(param_grid, score_fn):
"""Perform exhaustive grid search over hyperparameter combinations."""
keys = param_grid.keys()
names = list(keys)
values = [param_grid[name] for name in names]
results = []
for combination in itertools.product(*values):
params =…How to mock batch commit of transactions in Python
Simulate a transaction batch writer with commit, rollback, and summary logic to test database write patterns without a real database.
import json
from datetime import datetime, timezone
class TransactionBatch:
def __init__(self):
self.pending = []
self.committed = []
self._log = []
def add(self, operation):
self.pending.append(operation)
def commit(self):
if not self.pending:
return …How to mock Argon2 password hashing in Python
This code demonstrates a mock Argon2 password hasher using HMAC-SHA256 iterations, providing hash and verify methods that mimic Argon2's salted, iterated derivation.
import hashlib
import hmac
import os
class Argon2Mock:
def __init__(self, salt_size=16, hash_len=32):
self.salt_size = salt_size
self.hash_len = hash_len
def hash(self, password: str, salt: bytes = None) -> str:
if salt is None:
salt = os.urandom(self.salt_size)
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