I want to update a progress bar from inside a spawned process as follows:
import multiprocessing as mp
import random
import time
from tqdm import tqdm
def test(queue, pbar, lock):
while True:
x = queue.get()
if x is None:
break
for i in range(x):
time.sleep(1)
lock.acquire()
pbar.update(1)
lock.release()
queue = mp.Queue()
lock = mp.Lock()
processes = []
pbar = tqdm(total=5050)
for rank in range(4):
p = mp.Process(target=test, args=(queue, pbar, lock))
p.start()
processes.append(p)
pbar.close()
for idx in range(100):
queue.put(idx)
for _ in range(4):
queue.put(None) # sentinel values to signal subprocesses to exit
for p in processes:
p.join() # wait for all subprocesses to finish
The above gives inconsistent updates (progess goes up and down).
I found this answer, but none of them work for me because I want to update the progress bar inside the test
function. How can I do this?
I'd slightly restructure the program:
1.) Create update_bar
process that creates a progress bar and reads from another queue values and updates the bar with these values
2.) This update process has daemon=True
parameter, so it won't block upon exit
3.) The test
processes receives upon start the bar_queue
and put values there if they want to update the progress bar.
import time
from tqdm import tqdm
import multiprocessing as mp
def test(queue, bar_queue):
while True:
x = queue.get()
if x is None:
break
for _ in range(x):
time.sleep(0.05)
bar_queue.put_nowait(1)
def update_bar(q):
pbar = tqdm(total=188)
while True:
x = q.get()
pbar.update(x)
if __name__ == "__main__":
queue = mp.Queue()
bar_queue = mp.Queue()
processes = [
mp.Process(target=test, args=(queue, bar_queue)) for _ in range(4)
]
# start update progress bar process
# daemon= parameter is set to True so this process won't block us upon exit
bar_process = mp.Process(target=update_bar, args=(bar_queue,), daemon=True)
bar_process.start()
for p in processes:
p.start()
for idx in range(20):
queue.put(idx)
for _ in range(4):
queue.put(None) # sentinel values to signal subprocesses to exit
for p in processes:
p.join() # wait for all subprocesses to finish
time.sleep(0.5)