Python中多进程处理的Process和Pool的用法详解

import multiprocessing
import time
 
def worker(name):
    print(f"Worker {name} is starting.")
    time.sleep(2)
    print(f"Worker {name} is exiting.")
 
if __name__ == "__main__":
    p1 = multiprocessing.Process(target=worker, args=("A",))
    p2 = multiprocessing.Process(target=worker, args=("B",))
    
    p1.start()
    p2.start()
    
    p1.join()
    p2.join()

import multiprocessing
import time
 
def worker(name):
    print(f"Worker {name} is starting.")
    time.sleep(2)
    print(f"Worker {name} is exiting.")
 
if __name__ == "__main__":
    pool = multiprocessing.Pool(processes=2)
    pool.map(worker, ["A", "B"])
    pool.close()
    pool.join()

import multiprocessing
 
def square_sum(numbers):
    return sum(x ** 2 for x in numbers)
 
if __name__ == "__main__":
    numbers = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
    num_processes = 4
    pool = multiprocessing.Pool(processes=num_processes)
    chunk_size = len(numbers) // num_processes
    chunks = [numbers[i:i+chunk_size] for i in range(0, len(numbers), chunk_size)]
    results = pool.map(square_sum, chunks)
    total_sum = sum(results)
    print("Total square sum:", total_sum)
    pool.close()
    pool.join()

import multiprocessing
import requests
 
def download_file(url, filename):
    response = requests.get(url)
    with open(filename, 'wb') as f:
        f.write(response.content)
    print(f"Downloaded {filename} from {url}")
 
if __name__ == "__main__":
    urls = [
        ("https://example.com/file1.txt", "file1.txt"),
        ("https://example.com/file2.txt", "file2.txt"),
        ("https://example.com/file3.txt", "file3.txt")
    ]
    num_processes = len(urls)
    pool = multiprocessing.Pool(processes=num_processes)
    pool.starmap(download_file, urls)
    pool.close()
    pool.join()

import multiprocessing
from PIL import Image
 
def process_image(filename):
    img = Image.open(filename)
    # 进行图片处理操作，如压缩、调整大小、加水印等
    img.thumbnail((300, 300))
    img.save(f"processed_{filename}")
    print(f"Processed {filename}")
 
if __name__ == "__main__":
    filenames = ["image1.jpg", "image2.jpg", "image3.jpg"]
    num_processes = len(filenames)
    pool = multiprocessing.Pool(processes=num_processes)
    pool.map(process_image, filenames)
    pool.close()
    pool.join()