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concurrent-progressbar
Advanced tools
This package is used to track the processes executed in the program. It will show individual progress bar for each task alloted using this package. It runs each task in separate process.
This package is used to track the processes executed in the program. It will show individual progress bar for each task alloted using this package. It runs each task in separate process.
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.
pip install concurrent-progressbar
import os
from concurrent_progressbar.concurrent import Multithreading, MultiProcessing
def target_1(i):
pass
def target_2(j):
pass
pool = Multithreading(
num_workers=os.cpu_count(),
target=[target_1, target_2],
args=[[(i,) for i in range(1000)], [(j,) for j in range(100)]]
)
pool.run()
# OR
pool = Multiprocessing(
num_workers=os.cpu_count(),
target=[target_1, target_2],
args=[[(i,) for i in range(1000)], [(j,) for j in range(100)]]
)
pool.run()
pool = Multiprocessing(
num_workers=os.cpu_count(),
target=[target_1, target_2],
args=[[(i,) for i in range(1000)], [(j,) for j in range(100)]],
task_desc=["my-task-1", "my-task-2"],
tasks_at_a_time=1
)
# tasks_at_a_time=1 will run one task, when this task completed
# then next task will be executed. It is independent from num_workers argument.
pool.run()
FAQs
This package is used to track the processes executed in the program. It will show individual progress bar for each task alloted using this package. It runs each task in separate process.
We found that concurrent-progressbar demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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