progressbar方法 frommultiprocessing import Poolfromprogress bar import ProgressBar,Bar,ETAfromtimeimport sleepdef fcn(n):sleep(0.1)return n*nfeed =range(256)if __name__ =="__main__":withPool(10) as p:widgets = [Bar(),ETA()]pbar =ProgressBar(widgets=widgets,maxval=len(feed))return =...
方法2 from multiprocessing import Pool from progressbar import ProgressBar,Bar,ETA from time import sleep def myadd(n): add = n + n time.sleep(0.1) return add feed = range(256) with Pool(10) as p: widgets = [Bar(left="myadd: "),ETA()] pbar = ProgressBar(widgets=widgets,maxval=...
pool = multiprocessing.Pool() # 创建进程池 with tqdm(total=len(data), ncols=80) as pbar: for _ in tqdm(pool.imap_unordered(process_data, data)): pbar.update() 在上述代码中,pool.imap_unordered方法用于将任务函数应用到数据列表的每个元素上,同时使用tqdm库来实现进度条的显示。total参数指定总...
tqdmfrommultiprocessingimportPool,LockL=list(range(9))defprogresser(n):interval=0.001/(n+2)total...
frommultiprocessingimportProcess, Pool, QueuefromthreadingimportThread, Lockimporttimeimportprogressbarimportmath g_var=0 lock=Lock()defthread_tasks(q):for_inrange(100000): q.put(1)defconsumer_q(q):globalg_var p=progressbar.ProgressBar() ...
from multiprocessing importProcess, Pool, Queuefrom threading importThread, Lockimporttimeimportprogressbarimportmath g_var=0 lock=Lock()defthread_tasks(q):for _ in range(100000): q.put(1)defconsumer_q(q):globalg_var p=progressbar.ProgressBar() ...
我正在创建一个爬虫作为我的第一个项目,以了解如何在Python中工作,但到目前为止,这是我的主要问题。。。了解使用requests和pathos.multiprocessing时在终端中“如何获得多个进度条”。在 我尝试了所有的东西,我只想有更漂亮的输出,所以我决定添加progressbars。我使用tqdm,因为我喜欢它的外观,而且它似乎最容易实现。在...
from tqdm import tqdmimport multiprocessingdef worker(num):for i in tqdm(range(1000000), desc=f'Worker {num}'):passif __name__ == '__main__':with multiprocessing.Pool(4) as p:p.map(worker, [1, 2, 3, 4]) 这样就会在每个进程的进度条上显示进度,并显示进程的名称。
from time import sleep from tqdm import trange, tqdm from multiprocessing import Pool, RLock, freeze_support L = list(range(9)) def progresser(n): interval = 0.001 / (n + 2) total = 5000 text = f"#{n}, est. {interval * total:<04.2}s" for _ in trange(total, desc=text, ...
import osimport requestsfrom time import timefrom multiprocessing.pool import ThreadPool我们导入了操作系统和时间模块,以检查下载文件所需的时间。模块ThreadPool 允许您使用池运行多个线程或进程。让我们创建一个简单的函数,将响应以块的形式发送到文件:def url_response(url):path, url = urlr = requests.get(...