Progress bars for threading and multiprocessing tasks on the terminal and Jupyter Notebook.
atpbar can display multiple progress bars simultaneously growing to show the progress of each iteration of loops in threading or multiprocessing tasks. atpbar can display progress bars on the terminal and Jupyter Notebook.
This short tutorial shows the basic usage of atpbar with simple examples.
You can use pip to install atpbar:
pip install atpbarYou can try the examples in this tutorial in the Python interactive shell.
$ python
Python 3.13.9 (...)
...
...
>>>Import atpbar and other objects that we will use in the examples.
from random import randint
from time import sleep
from atpbar import atpbarThe atpbar can wrap an iterable to show a progress bar for the iterations.
n = randint(1000, 10000) # Random number of iterations
for _ in atpbar(range(n)):
sleep(0.001)This example randomly selects the number of iterations and, in each iteration, sleeps for a short time.
The progress bar will be shown as the loop progresses.
51.25% :::::::::::::::::::: | 4132 / 8062 |: range(0, 8062)
Note: atpbar won't show a progress bar if the length of the iterable cannot be
obtained by len().
The atpbar can show progress bars for nested loops.
for i in atpbar(range(4), name='Outer'):
n = randint(1000, 10000)
for _ in atpbar(range(n), name=f'Inner {i}'):
sleep(0.001)This example iterates over an outer loop four times. In each iteration, it iterates over an inner loop. The progress bars for both the outer and inner loops are shown.
100.00% :::::::::::::::::::::::::::::::::::::::: | 3287 / 3287 |: Inner 0
100.00% :::::::::::::::::::::::::::::::::::::::: | 5850 / 5850 |: Inner 1
50.00% :::::::::::::::::::: | 2 / 4 |: Outer
34.42% ::::::::::::: | 1559 / 4529 |: Inner 2
In the snapshot of the progress bars above, the outer loop is in its third iteration. The inner loop has been completed twice and is running the third. The progress bars for the completed tasks move up. The progress bars for the active tasks are growing at the bottom.
As the last example, we show how to use atpbar with threading. We will use
the
ThreadPoolExecutor
from the
concurrent.futures
module.
Import ThreadPoolExecutor and also flushing from atpbar.
from concurrent.futures import ThreadPoolExecutor
from atpbar import flushingDefine a function that will be executed by the threads.
def func(n, name):
for _ in atpbar(range(n), name=name):
sleep(0.001)We will submit ten jobs each runs the func function to five threads.
n_workers = 5
n_jobs = 10
with flushing(), ThreadPoolExecutor(max_workers=n_workers) as executor:
for i in range(n_jobs):
n = randint(1000, 10000)
executor.submit(func, n, name=f'Job {i}')The context manager flushing() exits after the progress bars have finished
updating.
The progress bars will be simultaneously updated for concurrent jobs.
100.00% :::::::::::::::::::::::::::::::::::::::: | 2326 / 2326 |: Job 0
100.00% :::::::::::::::::::::::::::::::::::::::: | 2971 / 2971 |: Job 1
100.00% :::::::::::::::::::::::::::::::::::::::: | 1386 / 1386 |: Job 6
100.00% :::::::::::::::::::::::::::::::::::::::: | 5316 / 5316 |: Job 3
100.00% :::::::::::::::::::::::::::::::::::::::: | 7786 / 7786 |: Job 4
100.00% :::::::::::::::::::::::::::::::::::::::: | 5500 / 5500 |: Job 5
91.33% :::::::::::::::::::::::::::::::::::: | 8188 / 8965 |: Job 2
39.85% ::::::::::::::: | 3842 / 9642 |: Job 7
34.89% ::::::::::::: | 2882 / 8260 |: Job 8
29.11% ::::::::::: | 414 / 1422 |: Job 9
On Jupyter Notebook, progress bars based on ipywidgets are displayed.
You can try interactively online:
This is the end of the quick start tutorial. For more information, see the Users Guide.
