如何获得Python中特定代码的内存以及我们的PC中可用的内存

发布于 2025-01-22 12:03:12 字数 996 浏览 0 评论 0原文

我想知道该代码消耗多少内存。也使用Python代码在我的PC中可用的内存。该怎么办？

这是我的代码：

from moviepy.editor import *
import os
import glob
from natsort import natsorted
import datetime
import time
import shutil
from concurrent.futures import ThreadPoolExecutor

def fast(path, thread_name):
if os.path.splitext(path)[1] == '.mp4':
    print("Start : " + str(thread_name) + "  -  " + str(datetime.datetime.now()))
    clip = (VideoFileClip(path).fx(vfx.speedx, 5))
    clip.to_videofile('G:/Ocsid Technologies/BUILDERS/Builder-1/Project-1/Converted Videos/' + 
    thread_name + '.mp4', codec='libx264')
    time.sleep(3)
    shutil.move(path, "G:/Ocsid Technologies/BUILDERS/Builder-1/Project-1/Original Videos/")
    print("End : " + str(thread_name) + "  -  " + str(datetime.datetime.now()))

with ThreadPoolExecutor(5) as pool:
      for i, filename in enumerate(glob.glob("G:/Ocsid Technologies/BUILDERS/Builder-1/Project-1/Raw 
 Videos/*.mp4"), 1):
    pool.submit(fast, filename, f"t{i}")

原文

I want to know how much memory this code consumes . Also available memory in my pc using a python code. What has to be done?

Here is my code :

from moviepy.editor import *
import os
import glob
from natsort import natsorted
import datetime
import time
import shutil
from concurrent.futures import ThreadPoolExecutor

def fast(path, thread_name):
if os.path.splitext(path)[1] == '.mp4':
    print("Start : " + str(thread_name) + "  -  " + str(datetime.datetime.now()))
    clip = (VideoFileClip(path).fx(vfx.speedx, 5))
    clip.to_videofile('G:/Ocsid Technologies/BUILDERS/Builder-1/Project-1/Converted Videos/' + 
    thread_name + '.mp4', codec='libx264')
    time.sleep(3)
    shutil.move(path, "G:/Ocsid Technologies/BUILDERS/Builder-1/Project-1/Original Videos/")
    print("End : " + str(thread_name) + "  -  " + str(datetime.datetime.now()))

with ThreadPoolExecutor(5) as pool:
      for i, filename in enumerate(glob.glob("G:/Ocsid Technologies/BUILDERS/Builder-1/Project-1/Raw 
 Videos/*.mp4"), 1):
    pool.submit(fast, filename, f"t{i}")

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