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Python Code Samples

Copy-ready Python snippets by topic and difficulty — short, focused, and runnable in the browser editor.

36 matches
AI & LLM integration patterns medium

How to Retry LLM Calls on Rate Limit Errors in Python

Implement a retry mechanism with exponential backoff for LLM API calls that raises a custom RateLimitError, using a mock function to demonstrate the pattern.

llm retry rate-limit
Python
import time
import random


def mock_llm_call():
    """Simulates an LLM API call that may raise a rate limit error."""
    if random.random() < 0.4:  # 40% chance of rate limit
        raise RateLimitError("Rate limit exceeded. Try again later.")
    return {"response": "Hello world from mock LLM"}


class RateLimitE…
16 0 Open
Cloud + Python easy

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.

retry backoff 429
Python
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 …
12 0 Open
Concurrency & performance medium

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.

asyncio rate-limiting token-bucket
Python
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…
14 0 Open
Concurrency & performance medium

Limit Concurrency with asyncio.Semaphore in Python

Use asyncio.Semaphore to cap how many async tasks run at once, throttling a batch of coroutines to a set concurrency limit.

asyncio concurrency semaphore
Python
import asyncio
import random


async def fetch_data(i: int, semaphore: asyncio.Semaphore) -> str:
    async with semaphore:
        print(f"Task {i} starts")
        await asyncio.sleep(random.uniform(0.1, 0.5))
        print(f"Task {i} finishes")
        return f"Result {i}"


async def main() -> None:
    semaphore …
13 0 Open
System design patterns medium

How to Limit Concurrent Requests with a Semaphore in Python

Use threading.Semaphore with a ThreadPoolExecutor to cap how many worker threads run simultaneously, preventing resource overload.

concurrency semaphore threading
Python
import threading
import time
from concurrent.futures import ThreadPoolExecutor

def worker(name, semaphore, results):
    with semaphore:
        results.append(f"start {name}")
        time.sleep(0.5)  # simulate async work
        results.append(f"done {name}")

def main():
    sem = threading.Semaphore(2)  # max 2 …
14 0 Open
API design & gRPC medium

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.

retry-after api rate-limiting
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 …
14 0 Open
API design & gRPC medium

How to Mock X-RateLimit Headers in Python

This code creates a local HTTP server that mimics rate limit headers (X-RateLimit-Limit, Remaining, Reset, Update) and returns 429 responses when the limit is exceeded.

http rate-limit server
Python
import time
import threading
from http.server import BaseHTTPRequestHandler, HTTPServer


class RateLimitHandler(BaseHTTPRequestHandler):
    RATE_LIMIT = 5          # max requests allowed
    WINDOW_SECONDS = 60     # per time window

    def __init__(self, *args, **kwargs):
        super().__init__(*args, **kwargs)
…
13 0 Open
Caching & Redis easy

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.

rate-limiting token-bucket threading
Python
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,…
12 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
Caching & Redis medium

Redis-inspired sliding window rate limiter in Python

A pure-Python sliding window rate limiter using a deque of timestamps, mock-ready for Redis-backed production limits.

redis rate-limit sliding-window
Python
import time
from collections import deque


class SlidingWindowRateLimiter:
    def __init__(self, max_requests: int, window_seconds: int) -> None:
        self.max_requests = max_requests
        self.window_seconds = window_seconds
        self.requests: dict[str, deque] = {}

    def is_allowed(self, client_id: str…
14 0 Open
Reliability & rate limiting easy

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.

rate-limiting decorator time
Python
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…
13 0 Open
Reliability & rate limiting easy

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.

admission-control queue rate-limiting
Python
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…
16 0 Open
Reliability & rate limiting easy

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.

rate-limiting fixed-window time
Python
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 >=…
13 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 easy

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.

rate-limiting token-bucket retry
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 …
15 0 Open
Reliability & rate limiting easy

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.

rate-limiting time sliding-window
Python
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…
14 0 Open
Reliability & rate limiting medium

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.

bulkhead threading semaphore
Python
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:
          …
13 0 Open
Reliability & rate limiting easy

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.

rate-limit deque time
Python
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…
16 0 Open
Reliability & rate limiting easy

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.

sliding-window rate-limiting deque
Python
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…
13 0 Open
Reliability & rate limiting medium

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.

rate-limiting sliding-window deque
Python
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_…
15 0 Open
Reliability & rate limiting easy

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.

rate-limiting penalty-box lockout
Python
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…
14 0 Open
Reliability & rate limiting medium

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.

rate-limiting sliding-window ip
Python
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…
13 0 Open
Reliability & rate limiting medium

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.

rate-limiting backoff adaptive
Python
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…
12 0 Open
Reliability & rate limiting easy

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.

quota rate-limiting class
Python
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…
17 0 Open

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Samples are quick reference — one concept per page. For step-by-step teaching, use our Python tutorials. To test yourself, try quizzes or coding challenges. Clean up style with the Python formatter.