Python中的并行编程问题及解决方案

import threading

# 定义线程锁
lock = threading.Lock()

# 共享资源
count = 0

def increment():
    global count
    for _ in range(1000000):
        # 加锁
        lock.acquire()
        count += 1
        # 释放锁
        lock.release()

# 创建多个线程
threads = []
for _ in range(5):
    t = threading.Thread(target=increment)
    threads.append(t)

# 启动线程
for t in threads:
    t.start()

# 等待所有线程执行完毕
for t in threads:
    t.join()

print(count)

import concurrent.futures

# 共享资源
count = 0

def increment():
    global count
    for _ in range(1000000):
        count += 1

# 创建线程池
pool = concurrent.futures.ThreadPoolExecutor(max_workers=5)

# 提交任务
futures = [pool.submit(increment) for _ in range(5)]

# 等待所有任务执行完毕
concurrent.futures.wait(futures)

# 关闭线程池
pool.shutdown()

print(count)

import concurrent.futures

# 任务列表
tasks = [1, 2, 3, 4, 5]

def process_task(task):
    return task * 2

# 创建线程池
pool = concurrent.futures.ThreadPoolExecutor(max_workers=5)

# 提交任务
futures = [pool.submit(process_task, task) for task in tasks]

# 获取结果
results = [future.result() for future in concurrent.futures.as_completed(futures)]

# 关闭线程池
pool.shutdown()

print(results)

import concurrent.futures

# 任务列表
tasks = [1, 2, 3, 4, 5]

def process_task(task):
    return task * 2

# 创建线程池
pool = concurrent.futures.ThreadPoolExecutor(max_workers=5)

# 提交任务
futures = [pool.submit(process_task, task) for task in tasks]

# 等待所有任务执行完毕
concurrent.futures.wait(futures)

# 获取结果
results = [future.result() for future in futures]

# 关闭线程池
pool.shutdown()

print(results)