I have a program that runs a long process after you click an action button. As the process is running the root window will say that it is not responding even though I know the program is running in the background. This program is going to be released to a few people that I work with and I want to make sure they don't freak out and close the window when they see this. The solution I have is sitting a root.update in the loop of the process that is running but I am not sure this was the best fix.
Using the python 3.3
Here is a sample of the code so you get an idea of what I am doing, this is called from the main loop:
def combine(boxes_to, boxes_from, frame):
to_value,to_pos = gui.checkBoxes(boxes_to)
from_value,from_pos = gui.checkBoxes(boxes_from)
frame.destroy()
running = Label(root,text="Running please do not close..",font = (16))
running.pack()
root.update()
map_to = open("map_to",'r')
for line in map_to:
root.update()
process(line)
running.destroy()
map_to.close()
finish = Button(root, text="Done",command=gui.stop)
finish.pack()
Running python -m tkinter from the command line should open a window demonstrating a simple Tk interface, letting you know that tkinter is properly installed on your system, and also showing what version of Tcl/Tk is installed, so you can read the Tcl/Tk documentation specific to that version.
mainloop() tells Python to run the Tkinter event loop. This method listens for events, such as button clicks or keypresses, and blocks any code that comes after it from running until you close the window where you called the method.
The answer to your question is a resounding yes.
While you can call root.update() in your loop, this will still produce some (potentially) undesirable side-effects.
As an alternative I would suggest that you implement simple multi-threading. Python multithreading is pretty simple, and will prevent both of these drawbacks. You will be able to execute your long running code, while still providing a clean and responsive UI.
If your application is trivially parallelizable, you could use multiple threads to decrease running time. Ex. Thread 1 handles entries 1-100, while thread 2 handles entries 101-200.
The best you can do here is to use multithreading in Python. Here's how to do this:
Let's say you have a function named combine()
due to which the window is freezing, which is being used as a command for a button named 'btn' as shown here:
btn = Button(root, text="Click Me", command=combine)
Now, when btn
is pressed you might be getting the 'not responding' problem. To fix this, edit the code as shown below:
import threading
btn = Button(root, text="Click Me", command=threading.Thread(target=combine).start)
Here threading.Thread
creates a separate thread in which the combine()
method is executed, so the GUI can continue to keep responding while the command is being executed.
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