I was working on a specific type of application in Dash which required the action executed by pressing the button to be performed in a separate process. This process, in turn, was parallelizable, and in some cases spawned child processes for the efficient computation. The configuration given in this cases makes the child processes to get stuck. The code below reproduces the situation described as follows:
import multiprocessing
import time
import dash
from dash import html
from dash.dependencies import Input, Output
app = dash.Dash(__name__)
app.layout = html.Div([
html.Button(id='refresh-button', children='Button'),
html.Div(id='dynamic-container1')
])
def run_function(i):
print('hello')
time.sleep(15)
print(f'hello world {i}')
def run_process():
num = 1
print('hello world 00000')
process = multiprocessing.Process(target=run_function, args=(num,))
process.start()
process.join()
print('hello world')
@app.callback(Output('dynamic-container1', 'children'), Input('refresh-button', 'n_clicks'))
def refresh_state(click):
if click == 0 or click is None:
return None
p = multiprocessing.Process(target=run_process)
p.start()
p.join()
return None
if __name__ == '__main__':
app.run_server(debug=True)
The output of this application when pressing the button is always the following:
Connected to pydev debugger (build 172.3968.37)
Dash is running on http://127.0.0.1:8050/
* Serving Flask app 'main' (lazy loading)
* Environment: production
WARNING: This is a development server. Do not use it in a production deployment.
Use a production WSGI server instead.
* Debug mode: on
pydev debugger: process 6884 is connecting
hello world 00000
which means that the first process utilizing the function run_process() was launched, however, the child process run_function(i) was not even started. I was trying to find an explanation in popular books on multiprocessing in Python and any guidance to these "chaining" processes, but to no avail. From my understanding, the new child process run_function(i) should occupy a separate core (if there is any free core) and not to depend on the resources consumed by the parent process run_process(). Could you, please, explain to me the mechanics of this? I have a doubt that in this code run_function(i) might be coerced to consume the same resources as run_process() does, so the system basically is just restricting any new process from starting from the same resources, but I would like to confirm it from more expert users of Python. I used Python 3.7 and Pycharm Community 2017.2.3 on Win7 to reproduce this example
from Process getting stuck after being launched from another process
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