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开源软件名称：alphatwirl/atpbar开源软件地址：https://github.com/alphatwirl/atpbar开源编程语言：Python 100.0%开源软件介绍：
atpbarProgress bars for threading and multiprocessing tasks on terminal and Jupyter Notebook. atpbar can display multiple progress bars simultaneously growing to show the progresses of iterations of loops in threading or multiprocessing tasks. atpbar can display progress bars on terminal and Jupyter Notebook. atpbar can be used with Mantichora. atpbar started its development in 2015 as part of alphatwirl. atpbar prevented physicists from terminating their running analysis codes, which would take many hours to complete, by showing progress bars indicating their codes were actually running. The progress bars have saved the physicists countless hours total. atpbar had been the sub-package progressbar of alphatwirl until it became an independent package, with the name atpbar, in February 2019. You can try it on Jupyter Notebook online: Requirement
InstallYou can install with conda install -c conda-forge atpbaror with pip install -U atpbarUser guideQuick startI will show here how to use atpbar by simple examples. Import librariesTo create simple loops in the examples, we use two python standard
libraries, time and
random. Import the
two packages as well as import time, random
from atpbar import atpbarNote: import the object One loopThe object n = random.randint(1000, 10000)
for i in atpbar(range(n)):
time.sleep(0.0001)The task in the above code is to sleep for A progress bar will be shown by In order for Nested loops
for i in atpbar(range(4), name='outer'):
n = random.randint(1000, 10000)
for j in atpbar(range(n), name='inner {}'.format(i)):
time.sleep(0.0001)The outer loop iterates 4 times. The inner loop is similar to the loop
in the previous example---sleeps for In the snapshot of the progress bars above, the outer loop is in its 3rd iteration. The inner loop has 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. Threading
The function from atpbar import flush
import threading
def run_with_threading():
nthreads = 5
def task(n, name):
for i in atpbar(range(n), name=name):
time.sleep(0.0001)
threads = [ ]
for i in range(nthreads):
name = 'thread {}'.format(i)
n = random.randint(5, 100000)
t = threading.Thread(target=task, args=(n, name))
t.start()
threads.append(t)
for t in threads:
t.join()
flush()
run_with_threading()The task to sleep for As a task completes, the progress bar for the task moves up. The progress bars for active tasks are at the bottom. Multiprocessing
The function import multiprocessing
multiprocessing.set_start_method('fork', force=True)
from atpbar import register_reporter, find_reporter, flush
def run_with_multiprocessing():
def task(n, name):
for i in atpbar(range(n), name=name):
time.sleep(0.0001)
def worker(reporter, task, queue):
register_reporter(reporter)
while True:
args = queue.get()
if args is None:
queue.task_done()
break
task(*args)
queue.task_done()
nprocesses = 4
ntasks = 10
reporter = find_reporter()
queue = multiprocessing.JoinableQueue()
for i in range(nprocesses):
p = multiprocessing.Process(target=worker, args=(reporter, task, queue))
p.start()
for i in range(ntasks):
name = 'task {}'.format(i)
n = random.randint(5, 100000)
queue.put((n, name))
for i in range(nprocesses):
queue.put(None)
queue.join()
flush()
run_with_multiprocessing()It starts four workers in subprocesses with In order to use Simultaneously growing progress bars will be shown. Multiprocessing.PoolTo use See the example code in the issue. With MantichoraMantichora provides a simple interface to multiprocessing and threading. With Mantichora, from mantichora import mantichora
def task(name):
n = random.randint(1000, 10000)
for i in atpbar(range(n), name=name):
time.sleep(0.0001)
with mantichora() as mcore:
mcore.run(task, 'task 1')
mcore.run(task, 'task 2')
mcore.run(task, 'task 3')
mcore.run(task, 'task 4')
mcore.run(task, 'task 5')
returns = mcore.returns()This example uses multiprocessing. To use threading, set the option
FeaturesA
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