使用多处理模块更新Tkinter GUI

时间:2012-11-05 08:56:44

标签: python tkinter multiprocessing

我一直在尝试使用Multiprocessing模块来更新Tkinter GUI,但是当我运行此代码时,它会给出Pickling错误。

# Test Code for Tkinter with threads
import Tkinter
from multiprocessing import Queue
import multiprocessing
import time

# Data Generator which will generate Data
def GenerateData():
    global q
    for i in range(10):
        print "Generating Some Data, Iteration %s" %(i)
        time.sleep(2)
        q.put("Some Data from iteration %s \n" %(i))

def QueueHandler():
    global q, text_wid
    while True:
        if not q.empty():
            str = q.get()
            text_wid.insert("end", str)

# Main Tkinter Application
def GUI():
    global text_wid
    tk = Tkinter.Tk()
    text_wid = Tkinter.Text(tk)
    text_wid.pack()
    tk.mainloop()

if __name__ == '__main__':
# Queue which will be used for storing Data
    tk = Tkinter.Tk()
    text_wid = Tkinter.Text(tk)
    q = multiprocessing .Queue()
    t1 = multiprocessing.Process(target=GenerateData,args=(q,))
    t2 = multiprocessing.Process(target=QueueHandler,args=(q,text_wid))
    t1.start()
    t2.start()
    text_wid.pack()
    tk.mainloop()

错误:

PicklingError: Can't pickle <type 'thread.lock'>: it's not found as thread.lock

如果删除参数text_wid,则不会报告错误,但文本小部件不会使用来自队列中的数据进行更新。

更新:

我修改了代码,以便在队列中有值时调用该函数来更新GUI,从而防止Tkinter小部件被传递到单独的进程。现在,我没有收到任何错误,但是小部件没有更新数据。但是,如果我使用ThreadingMultiprocessing模块的混合,即创建一个单独的线程来处理队列中的数据,那么它可以正常工作。我的问题为什么当我在单独的进程中运行处理程序代码时它不起作用。我没有正确传递数据。以下是修改后的代码:

# Test Code for Tkinter with threads
import Tkinter
import multiprocessing
from multiprocessing import Queue
import time
import threading

# Data Generator which will generate Data
def GenerateData(q):
    for i in range(10):
        print "Generating Some Data, Iteration %s" %(i)
        time.sleep(2)
        q.put("Some Data from iteration %s \n" %(i))

def QueueHandler(q):
    while True:
        if not q.empty():
            str = q.get()
            update_gui(str)
            #text_wid.insert("end", str)

# Main Tkinter Application
def GUI():
    global text_wid
    tk = Tkinter.Tk()
    text_wid = Tkinter.Text(tk)
    text_wid.pack()
    tk.mainloop()

def update_gui(str):
    global text_wid
    text_wid.insert("end", str)

if __name__ == '__main__':
# Queue which will be used for storing Data
    tk = Tkinter.Tk()
    text_wid = Tkinter.Text(tk)
    q = multiprocessing.Queue()
    t1 = multiprocessing.Process(target=GenerateData,args=(q,))
    t2 = multiprocessing.Process(target=QueueHandler,args=(q,))
    t1.start()
    t2.start()
    text_wid.pack()
    tk.mainloop()

2 个答案:

答案 0 :(得分:2)

# Test Code for Tkinter with threads
import Tkinter as Tk
import multiprocessing
from Queue import Empty, Full
import time

class GuiApp(object):
   def __init__(self,q):
      self.root = Tk.Tk()
      self.root.geometry('300x100')
      self.text_wid = Tk.Text(self.root,height=100,width=100)
      self.text_wid.pack(expand=1,fill=Tk.BOTH)
      self.root.after(100,self.CheckQueuePoll,q)

   def CheckQueuePoll(self,c_queue):
      try:
         str = c_queue.get(0)
         self.text_wid.insert('end',str)
      except Empty:
         pass
      finally:
         self.root.after(100, self.CheckQueuePoll, c_queue)

# Data Generator which will generate Data
def GenerateData(q):
   for i in range(10):
      print "Generating Some Data, Iteration %s" %(i)
      time.sleep(2)
      q.put("Some Data from iteration %s \n" %(i))


if __name__ == '__main__':
# Queue which will be used for storing Data

   q = multiprocessing.Queue()
   q.cancel_join_thread() # or else thread that puts data will not term
   gui = GuiApp(q)
   t1 = multiprocessing.Process(target=GenerateData,args=(q,))
   t1.start()
   gui.root.mainloop()

   t1.join()
   t2.join()

答案 1 :(得分:0)

你错过了一个重要的部分,你应该使用__main__陷阱来保护你的电话:

if __name__ == '__main__': 
    q = Queue.Queue()
    # Create a thread and run GUI & QueueHadnler in it
    t1 = multiprocessing.Process(target=GenerateData,args=(q,))
    t2 = multiprocessing.Process(target=QueueHandler,args=(q,))

    ....

请注意,Queue作为参数传递,而不是使用全局。

修改:刚发现另一个问题,您应该使用Queue模块中的multiprocessing,而不是来自Queue

from multiprocessing import Queue