TypeError:无法腌制“weakref"对象

TypeError: cannot pickle #39;weakref#39; object(TypeError:无法腌制“weakref对象)

问题描述

这里是多处理的新手.我有一个运行两个进程的代码.一个是不断地从服务器接收数据块并将其放入队列中，另一个是从队列中取出数据块并进行处理.

Quite new to multiprocessing here. I have a code that runs two processes. One to continuously receive data blocks from the server and put it inside a queue and the other to remove the data blocks from the queue and process it.

下面是我的客户端代码:

Below is my client code:

import socket
import turtle
import multiprocessing
from multiprocessing import Process, Queue
from tkinter import *


class GUI:

    def __init__(self, master):
        rec_data = recv_data()
        self.master = master
        master.title("Collision Detection")

        self.input_label = Label(root, text="Input all the gratings set straight wavelength values in nm")
        self.input_label.grid(row=0)

        self.core_string = "Core "
        self.entries = []


        self.label_col_inc = 0
        self.entry_col_inc = 1
        self.core_range = range(1, 5)

        for y in self.core_range:
            self.core_text = self.core_string + str(y) + '_' + '25'
            self.core_label = Label(root, text=self.core_text)
            self.entry = Entry(root)
            self.core_label.grid(row=1, column=self.label_col_inc, sticky=E)
            self.entry.grid(row=1, column=self.entry_col_inc)
            self.entries.append(self.entry)
            self.label_col_inc += 2
            self.entry_col_inc += 2

        self.threshold_label = Label(root, text="Threshold in nm")
        self.entry_threshold = Entry(root)

        self.threshold_label.grid(row=2, sticky=E)
        self.entry_threshold.grid(row=2, column=1)

        self.light_label = Label(root, text='Status')
        self.light_label.grid(row=3, column=3)

        self.canvas = Canvas(root, width=150, height=50)
        self.canvas.grid(row=4, column=3)

        # Green light
        self.green_light = turtle.RawTurtle(self.canvas)
        self.green_light.shape('circle')
        self.green_light.color('grey')
        self.green_light.penup()
        self.green_light.goto(0, 0)

        # Red light
        self.red_light = turtle.RawTurtle(self.canvas)
        self.red_light.shape('circle')
        self.red_light.color('grey')
        self.red_light.penup()
        self.red_light.goto(40, 0)

        self.data_button = Button(root, text="Get data above threshold", command=rec_data.getData)
        self.data_button.grid(row=5, column=0)


class recv_data:
    def __init__(self):
        self.buff_data = multiprocessing.Queue()
        self.p1 = multiprocessing.Process(target=self.recvData)
        self.p2 = multiprocessing.Process(target=self.calculate_threshold)
        self.host = '127.0.0.1'
        self.port = 5001
        self.s = socket.socket()
        self.s.connect((self.host, self.port))

    # function to receive TCP data blocks
    def getData(self):
        len_message = self.s.recv(4)
        bytes_length = int(len_message.decode('utf-8'))  # for the self-made server
        recvd_data = self.s.recv(bytes_length)
        self.buff_data.put(recvd_data)
        self.p1.start()
        self.p2.start()

        self.p1.join()
        self.p2.join()

    def recvData(self):
        len_message = self.s.recv(4)
        while len_message:
            bytes_length = int(len_message.decode('utf-8'))  # for the self-made server
            recvd_data = self.s.recv(bytes_length)
            self.buff_data.put(recvd_data)
            len_message = self.s.recv(4)

        else:
            print('out of loop')
        self.s.close()

    def calculate_threshold(self):
        rmv_data = self.buff_data.get()
        stringdata = rmv_data.decode('utf-8')
        rep_str = stringdata.replace(",", ".")
        splitstr = rep_str.split()

        # received wavelength values
        inc = 34
        wav_threshold = []
        for y in gui.entries:
            straight_wav = float(y.get())
            wav = float(splitstr[inc])
            wav_diff = wav - straight_wav
            if wav_diff < 0:
                wav_diff = wav_diff * (-1)
            wav_threshold.append(wav_diff)
            inc += 56

        threshold = float(gui.entry_threshold.get())

        for x in wav_threshold:
            if (x > threshold):
                gui.red_light.color('red')
                gui.green_light.color('grey')

            else:
                gui.red_light.color('grey')
                gui.green_light.color('green')
    

        # function to write into the file

    def write_file(self, data):
        with open("Output.txt", "a") as text_file:
            text_file.write('	'.join(data[0:]))
            text_file.write('
')

if __name__ == '__main__':
    root = Tk()
    gui1 = GUI(root)

    root.mainloop()

我得到的错误如下所示:

The error I get is shown below:

Exception in Tkinter callback
Traceback (most recent call last):
  File "C:UsersAppDataLocalProgramsPythonPython38-32lib	kinter\__init__.py", line 1883, in __call__
    return self.func(*args)
  File "C:/Users/PycharmProjects/GUI/GUI_multiprocess.py", line 85, in getData
    self.p2.start()
  File "C:UsersAppDataLocalProgramsPythonPython38-32libmultiprocessingprocess.py", line 121, in start
    self._popen = self._Popen(self)
  File "C:UsersAppDataLocalProgramsPythonPython38-32libmultiprocessingcontext.py", line 224, in _Popen
    return _default_context.get_context().Process._Popen(process_obj)
  File "C:UsersAppDataLocalProgramsPythonPython38-32libmultiprocessingcontext.py", line 326, in _Popen
    return Popen(process_obj)
  File "C:UsersAppDataLocalProgramsPythonPython38-32libmultiprocessingpopen_spawn_win32.py", line 93, in __init__
    reduction.dump(process_obj, to_child)
  File "C:UsersAppDataLocalProgramsPythonPython38-32libmultiprocessing
eduction.py", line 60, in dump
    ForkingPickler(file, protocol).dump(obj)
TypeError: cannot pickle 'weakref' object
Traceback (most recent call last):
  File "<string>", line 1, in <module>
  File "C:UsersAppDataLocalProgramsPythonPython38-32libmultiprocessingspawn.py", line 116, in spawn_main
    exitcode = _main(fd, parent_sentinel)
  File "C:UsersAppDataLocalProgramsPythonPython38-32libmultiprocessingspawn.py", line 126, in _main
    self = reduction.pickle.load(from_parent)
EOFError: Ran out of input

我在这里做错了什么，我该如何解决?任何帮助表示赞赏.谢谢！

What am I doing wrong here and how can I fix it? Any help is appreciated. Thank you!

推荐答案

我刚刚遇到相同的回溯并设法解决了它.这是因为一个对象有一个正在运行或退出的进程作为变量，并且它正在使用该对象启动另一个进程.

I just came to the same traceback and managed to solve it. It was due to that an object had a running or exited Process as a variable and it was starting another Process using that object.

问题

这是产生错误的最少代码:

This is a minimal code to produce your error:

import multiprocessing

class Foo:
    def __init__(self):
        self.process_1 = multiprocessing.Process(target=self.do_stuff1)
        self.process_2 = multiprocessing.Process(target=self.do_stuff2)

    def do_multiprocessing(self):
        self.process_1.start()
        self.process_2.start()

    def do_stuff1(self):
        print("Doing 1")

    def do_stuff2(self):
        print("Doing 2")

if __name__ == '__main__':
    foo = Foo()
    foo.do_multiprocessing()

[out]:
Traceback (most recent call last):
  File "myfile.py", line 21, in <module>
    foo.do_multiprocessing()
  File "myfile.py", line 11, in do_multiprocessing
    self.process_2.start()
  File "...libmultiprocessingprocess.py", line 121, in start
    self._popen = self._Popen(self)
  File "...libmultiprocessingcontext.py", line 224, in _Popen
    return _default_context.get_context().Process._Popen(process_obj)
  File "...libmultiprocessingcontext.py", line 327, in _Popen
    return Popen(process_obj)
  File "...libmultiprocessingpopen_spawn_win32.py", line 93, in __init__
    reduction.dump(process_obj, to_child)
  File "...libmultiprocessing
eduction.py", line 60, in dump
    ForkingPickler(file, protocol).dump(obj)
TypeError: cannot pickle 'weakref' object
Doing 1
Traceback (most recent call last):
  File "<string>", line 1, in <module>
  File "...libmultiprocessingspawn.py", line 116, in spawn_main
    exitcode = _main(fd, parent_sentinel)
  File "...libmultiprocessingspawn.py", line 126, in _main
    self = reduction.pickle.load(from_parent)
EOFError: Ran out of input

所以问题是 Foo 在启动 foo.process_2 时还包含正在运行/退出的进程 foo.process_1.

So the issue is that Foo contains also the running/exited process foo.process_1 when it starts foo.process_2.

解决方案 1

将 foo.process_1 设置为 None 或其他.或者将进程存储在 foo 以外的其他位置，以防止在启动 process_2 时被传递.

Set foo.process_1 to None or something else. Or store the Processes somewhere else than in foo to prevent being passed when starting process_2.

...
def do_multiprocessing(self):
    self.process_1.start()
    self.process_1 = None # Remove exited process
    self.process_2.start()
...

解决方案 2

从酸洗中删除有问题的变量(process_1):

Remove the problematic variable (process_1) from pickling:

class Foo:
    def __getstate__(self):
        # capture what is normally pickled
        state = self.__dict__.copy()

        # remove unpicklable/problematic variables 
        state['process_1'] = None
        return state
...

这在较新的 Python 版本中似乎是个问题.我自己的代码在 3.7 中运行良好，但在 3.9 中由于这个问题而失败.

This seems to be problem in newer Python versions. My own code worked fine for 3.7 but failed due to this issue in 3.9.

我测试了您的代码(来自 recv_data).由于您加入流程并需要它们，因此您应该执行解决方案 2 或将流程存储在 recv_data 之外的其他位置.不确定您的代码还有什么其他问题.

I tested your code (from recv_data). Since you join the processes and need them, you should do the solution 2 or store the processes somewhere else than in recv_data. Not sure what other problems your code has.

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