📚 核心概念

GIL（全局解释器锁）

• 确保同一时间只有一个线程执行Python字节码
• 保护Python内部数据结构不受并发访问影响
• 只适用于CPython解释器

协程（Coroutine）

• 轻量级并发解决方案
• 在单个线程中实现多个任务切换
• 用户空间切换，无需内核级上下文切换

线程（Thread）

• 操作系统级别的并发
• 共享进程内存空间
• 受GIL限制

进程（Process）

• 独立的执行环境
• 拥有独立内存空间
• 可以真正并行执行

🎯 协程示例

import asyncio
import random

async def coroutine(id):
    delay = random.randint(1, 3)
    print(f"Coroutine {id} starting, will run for {delay} seconds")
    await asyncio.sleep(delay)
    print(f"Coroutine {id} finished")

async def main():
    coroutines = []
    for i in range(5):
        coroutines.append(coroutine(i))
    await asyncio.gather(*coroutines)

if __name__ == "__main__":
    asyncio.run(main())

🧵 多线程示例

import threading

def print_numbers():
    for i in range(10):
        print(i)

threads = [threading.Thread(target=print_numbers) for _ in range(3)]
for thread in threads:
    thread.start()
for thread in threads:
    thread.join()

🖥️ 多进程示例

import multiprocessing

def print_numbers():
    for i in range(10):
        print(i)

processes = [multiprocessing.Process(target=print_numbers) for _ in range(3)]
for process in processes:
    process.start()
for process in processes:
    process.join()

⚡ 并行计算

import multiprocessing

def calculate(number):
    return number ** 2

if __name__ == '__main__':
    pool = multiprocessing.Pool(processes=4)
    results = pool.map(calculate, [1, 2, 3, 4, 5, 6, 7, 8, 9, 10])
    print(results)