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System design patterns

Sharding, load balancing, CAP tradeoffs, and scaling patterns — interview and production ready.

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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 …
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