1. 使用多进程执行函数
以下代码没有使用多进程。
python
import time
start = time.perf_counter()
def do_something():
print('Sleeping 1 second...')
time.sleep(1)
print('Done Sleep...')
do_something()
do_something()
finish = time.perf_counter()
print(f'Finished in {round(finish-start, 2)} second(s)')输出为：
Sleeping 1 second...
Done Sleep...
Sleeping 1 second...
Done Sleep...
Finished in 2.03 second(s)
以下代码使用了多进程。
python
import time
import multiprocessing
def do_something():
print('Sleeping 1 second...')
time.sleep(1)
print('Done Sleep...')
if __name__ == '__main__':
start = time.perf_counter()
p1 = multiprocessing.Process(target=do_something)
p2 = multiprocessing.Process(target=do_something)
p1.start()
p2.start()
p1.join()
p2.join()
finish = time.perf_counter()
print(f'Finished in {round(finish-start, 2)} second(s)')输出为：
Sleeping 1 second...
Sleeping 1 second...
Done Sleep...
Done Sleep...
Finished in 1.07 second(s)
2. 使用loop创建多个进程，并在函数中传入参数。
python
import time
import multiprocessing
def do_something(seconds):
print(f'Sleeping {seconds} second(s)...')
time.sleep(seconds)
print('Done Sleep...')
if __name__ == '__main__':
start = time.perf_counter()
processes = []
for _ in range(10):
p = multiprocessing.Process(target=do_something, args=[1.5])
p.start()
processes.append(p)
for process in processes:
process.join()
finish = time.perf_counter()
print(f'Finished in {round(finish-start, 2)} second(s)')输出为：
Sleeping 1.5 second(s)...
Sleeping 1.5 second(s)...
Sleeping 1.5 second(s)...
Sleeping 1.5 second(s)...
Sleeping 1.5 second(s)...
Sleeping 1.5 second(s)...
Sleeping 1.5 second(s)...
Sleeping 1.5 second(s)...
Sleeping 1.5 second(s)...
Sleeping 1.5 second(s)...
Done Sleep...
Done Sleep...
Done Sleep...
Done Sleep...
Done Sleep...
Done Sleep...
Done Sleep...
Done Sleep...
Done Sleep...
Done Sleep...
Finished in 1.62 second(s)
3. 使用进程池实现多进程
python
import time
import concurrent.futures
def do_something(seconds):
print(f'Sleeping {seconds} second(s)...')
time.sleep(seconds)
return f'Done Sleep...{seconds}'
if __name__ == '__main__':
start = time.perf_counter()
with concurrent.futures.ProcessPoolExecutor() as executor:
secs = [5, 4, 3, 2, 1]
results = executor.map(do_something, secs)
for result in results:
print(result)
finish = time.perf_counter()
print(f'Finished in {round(finish-start, 2)} second(s)')输出为：
Sleeping 5 second(s)...
Sleeping 4 second(s)...
Sleeping 3 second(s)...
Sleeping 2 second(s)...
Sleeping 1 second(s)...
Done Sleep...5
Done Sleep...4
Done Sleep...3
Done Sleep...2
Done Sleep...1
Finished in 5.14 second(s)
4. 使用多进程处理图片
以下代码展示了没有使用多进程处理图片
python
import time
from PIL import Image, ImageFilter
img_names = [
'photo-1516117172878-fd2c41f4a759.jpg',
'photo-1532009324734-20a7a5813719.jpg',
'photo-1524429656589-6633a470097c.jpg',
'photo-1530224264768-7ff8c1789d79.jpg',
'photo-1564135624576-c5c88640f235.jpg',
'photo-1541698444083-023c97d3f4b6.jpg',
'photo-1522364723953-452d3431c267.jpg',
'photo-1493976040374-85c8e12f0c0e.jpg',
'photo-1504198453319-5ce911bafcde.jpg',
'photo-1530122037265-a5f1f91d3b99.jpg',
'photo-1516972810927-80185027ca84.jpg',
'photo-1550439062-609e1531270e.jpg',
'photo-1549692520-acc6669e2f0c.jpg'
]
t1 = time.perf_counter()
size = (1200, 1200)
for img_name in img_names:
img = Image.open(img_name)
img = img.filter(ImageFilter.GaussianBlur(15))
img.thumbnail(size)
img.save(f'processed/{img_name}')
print(f'{img_name} was processed...')
t2 = time.perf_counter()
print(f'Finished in {t2-t1} seconds')输出为：
photo-1516117172878-fd2c41f4a759.jpg was processed...
photo-1532009324734-20a7a5813719.jpg was processed...
photo-1524429656589-6633a470097c.jpg was processed...
photo-1530224264768-7ff8c1789d79.jpg was processed...
photo-1564135624576-c5c88640f235.jpg was processed...
photo-1541698444083-023c97d3f4b6.jpg was processed...
photo-1522364723953-452d3431c267.jpg was processed...
photo-1493976040374-85c8e12f0c0e.jpg was processed...
photo-1504198453319-5ce911bafcde.jpg was processed...
photo-1530122037265-a5f1f91d3b99.jpg was processed...
photo-1516972810927-80185027ca84.jpg was processed...
photo-1550439062-609e1531270e.jpg was processed...
photo-1549692520-acc6669e2f0c.jpg was processed...
Finished in 13.196055100299418 seconds
使用多进程的方式处理图片
python
import time
import concurrent.futures
from PIL import Image, ImageFilter
img_names = [
'photo-1516117172878-fd2c41f4a759.jpg',
'photo-1532009324734-20a7a5813719.jpg',
'photo-1524429656589-6633a470097c.jpg',
'photo-1530224264768-7ff8c1789d79.jpg',
'photo-1564135624576-c5c88640f235.jpg',
'photo-1541698444083-023c97d3f4b6.jpg',
'photo-1522364723953-452d3431c267.jpg',
'photo-1493976040374-85c8e12f0c0e.jpg',
'photo-1504198453319-5ce911bafcde.jpg',
'photo-1530122037265-a5f1f91d3b99.jpg',
'photo-1516972810927-80185027ca84.jpg',
'photo-1550439062-609e1531270e.jpg',
'photo-1549692520-acc6669e2f0c.jpg'
]
def process_image(img_name):
img = Image.open(img_name)
img = img.filter(ImageFilter.GaussianBlur(15))
img.thumbnail((1200, 1200))
img.save(f'processed/{img_name}')
print(f'{img_name} was processed...')
if __name__ == '__main__':
t1 = time.perf_counter()
with concurrent.futures.ProcessPoolExecutor() as executor:
executor.map(process_image, img_names)
t2 = time.perf_counter()
print(f'Finished in {t2-t1} seconds')输出为：
photo-1516117172878-fd2c41f4a759.jpg was processed...
photo-1516972810927-80185027ca84.jpg was processed...
photo-1524429656589-6633a470097c.jpg was processed...
photo-1522364723953-452d3431c267.jpg was processed...
photo-1532009324734-20a7a5813719.jpg was processed...
photo-1530122037265-a5f1f91d3b99.jpg was processed...
photo-1530224264768-7ff8c1789d79.jpg was processed...
photo-1564135624576-c5c88640f235.jpg was processed...
photo-1550439062-609e1531270e.jpg was processed...
photo-1541698444083-023c97d3f4b6.jpg was processed...
photo-1549692520-acc6669e2f0c.jpg was processed...
photo-1504198453319-5ce911bafcde.jpg was processed...
photo-1493976040374-85c8e12f0c0e.jpg was processed...
Finished in 2.651644399855286 seconds