# Author: Miguel Martinez Lopez # # Uncomment the next line to see my email # print("Author's email: %s"%"61706c69636163696f6e616d656469646140676d61696c2e636f6d".decode("hex")) """ I provide in this module the function "tk_call_async". "tk_call_async" executes the function "computation" asyncronously with the provided "args" and "kwargs" without blocking the tkinter event loop. If "callback" is provided, it will be called with the result when the computation is finnished. If an exception is raised during computation, instead errback will be called. "Polling" will be the frequency to poll to check for results. There is two methods to execute the task: using multiprocessing or using threads. """ import traceback import threading # Python 3 support try: from Queue import Queue except ImportError: from queue import Queue MULTIPROCESSING = 0 THREADS = 1 def tk_call_async(window, computation, args=(), kwargs={}, callback=None, errback=None, polling=500, method=MULTIPROCESSING): if method == MULTIPROCESSING: # I use threads because on windows creating a new python process freezes a little the event loop. future_result= Queue() worker = threading.Thread(target=_request_result_using_multiprocessing, args=(computation, args, kwargs, future_result)) worker.daemon = True worker.start() elif method == THREADS: future_result = _request_result_using_threads(computation, args=args, kwargs=kwargs) else: raise ValueError("Not valid method") if callback is not None or errback is not None: _after_completion(window, future_result, callback, errback, polling) return future_result def _request_result_using_multiprocessing(func, args, kwargs, future_result): import multiprocessing queue= multiprocessing.Queue() worker = multiprocessing.Process(target=_compute_result, args=(func, args, kwargs, queue)) worker.daemon = True worker.start() return future_result.put(queue.get()) def _request_result_using_threads(func, args, kwargs): future_result= Queue() worker = threading.Thread(target=_compute_result, args=(func, args, kwargs, future_result)) worker.daemon = True worker.start() return future_result def _after_completion(window, future_result, callback, errback, polling): def check(): try: result = future_result.get(block=False) except: window.after(polling, check) else: if isinstance(result, Exception): if errback is not None: errback(result) else: if callback is not None: callback(result) window.after(0, check) def _compute_result(func, func_args, func_kwargs, future_result): try: _result = func(*func_args, **func_kwargs) except Exception as errmsg: _result = Exception(traceback.format_exc()) future_result.put(_result) # Multiprocessing uses pickle on windows. # A pickable function should be in top module or imported from another module. # This is requirement is not mandatory on Linux because python uses behind the scenes the fork operating system call. # But on Windows it uses named pipes and pickle. def _example_calculation(n): if n == 0: return 0 elif n == 1: return 1 else: return _example_calculation(n-1)+_example_calculation(n-2) if __name__ == "__main__": try: from Tkinter import Tk, Frame, Entry, Label, Button, IntVar, StringVar, LEFT import tkMessageBox as messagebox except ImportError: from tkinter import Tk, Frame, Entry, Label, Button, IntVar, StringVar, LEFT from tkinter import messagebox disabled = False def calculate_fibonacci(): global disabled if disabled: messagebox.showinfo("warning", "It's still calculating...") return def callback(result): global disabled disabled = False result_var.set(result) disabled = True tk_call_async(root, _example_calculation, args=(n.get(),), callback=callback, method =MULTIPROCESSING) root = Tk() n = IntVar(value=35) row = Frame(root) row.pack() Entry(row, textvariable=n).pack(side=LEFT) Button(row, text="Calculate fibonnaci", command =calculate_fibonacci).pack(side=LEFT) Button(row, text="It's responsive", command= lambda: messagebox.showinfo("info", "it's responsive")).pack(side=LEFT) result_var = StringVar() Label(root, textvariable=result_var).pack() root.mainloop()