我偶然发现了一个需要手动更新tqdm条的案例。具体来说，我试图跟踪一个由Fortran库启动的进程。在下面的代码中，我复制了行为，保留了面向案例的细节。当一个过程完成时，问题就出现了。具体地，当过程完成时，光标位置改变，并且因此条相对于它们的初始位置移动，从而留下先前的迭代。此外，它发生，如果一个酒吧试图更新自己，当另一个酒吧正在改变，它的位置是重新计算从那里留下一个混乱。我相信这种行为与没有锁定有关，或者是锁定条形图中更改的方法。我没有在网上找到任何东西，所以我在这里发布。应该可以用队列来解决这个问题，但我不希望传递tqdm对象，因为它们是不可拾取的。

from concurrent.futures import ThreadPoolExecutor, as_completed
import random
from tqdm.auto import tqdm
from time import sleep 
from threading import Thread

def latest_time(dir:str):
    return random.randint(0,100), 'a', False
    
def monitor_run(
        dir:str,
        name: str,
        position: int,
        max_iter: int,
        refresh_progress: float=2,
) -> None:
    sleep(1 + (position+1)/10)
    with tqdm(
        total = max_iter,
        bar_format="{l_bar}{bar:30}{r_bar}",
        desc=f"\t\t{name}: 0.0 Progress",
        position= position,
        ncols = 100,
        leave = True,
        ascii= True,
        colour ='#00ff00',

    ) as pbar:
        desc_prev: float = 0
        while True:
            sleep(refresh_progress)
            time, desc, error = latest_time(dir)
            
            if desc is None:
                desc: float | None = desc_prev
            else:
                desc_prev = desc
                pbar.desc = f"\t\t {name}: {desc} Progress"
            
            if error:
                pbar.write(f"Encountered Error at {desc}")
                break
            
            if time is None:
                continue

            pbar.n = int(time)
            pbar.refresh(nolock=True)

            if time>=max_iter:
                pbar.close()
                break

def serial_monitor(
    dir:str,
    position: int,
    max_iter: int,
    refresh_progress: float = 2,
)-> None:
    monitor_run(dir,str(position), position ,max_iter, refresh_progress)

def serial_monitor_star(args)-> None:
    serial_monitor(*args)

def parallel_monitor(
        dirs: list[str],
        max_iter: int,
        refresh_progress: float =2,
) -> None:
    args_list = [
        [
            dir, position+1, max_iter, refresh_progress
        ] for position, dir in enumerate(dirs)
    ]
    # tqdm.write("\t\tStarting:")
    # thread_map(
    #     serial_monitor_star, args_list, tqdm_class = tqdm ,max_workers = len(reynolds)
    # )
    # tqdm.write("\t\tCompleted")
    with tqdm(total=2*len(dirs)):
        with ThreadPoolExecutor(max_workers= len(dirs)) as ex:
            futures = [
                ex.submit(
                    serial_monitor_star,
                    args
                ) for args in args_list
            ]
            for future in as_completed(futures):
                result = future.result()

if __name__ =="__main__":
    parallel_monitor(
        ['','','','','','',''],
        100,
        2
    )

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