在修饰器内部运行多进程

Running multiprocessing inside decorator(在修饰器内部运行多进程)

本文介绍了在修饰器内部运行多进程的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!

问题描述

我想更新一下关于装饰器内部多进程的问题(我之前的问题对我来说似乎已经死了:)。我偶然发现了这个问题,不幸的是,我不知道如何解决这个问题。为了我的应用程序的需要,我不得不在装饰器中使用多进程,但是...当我在修饰器内部使用多进程时,我收到错误: Can't pickle <function run_testcase at 0x00000000027789C8>: it's not found as __main__.run_testcase。 另一方面,当我像调用正常函数wrapper(function,*arg)那样调用我的多处理函数时,它起作用了。这是非常棘手的,但我不知道我做错了什么。我几乎可以得出这样的结论:这是python错误:)。也许有人知道这个问题的解决方法,只保留相同的语法。我在Windows上运行此代码(不幸的是)。

上一个问题:Using multiprocessing inside decorator generates error: can't pickle function...it's not found as

模拟此错误的最简单代码:

from multiprocessing import Process,Event

class ExtProcess(Process):
    def __init__(self, event,*args,**kwargs):
        self.event=event
        Process.__init__(self,*args,**kwargs)

    def run(self):
        Process.run(self)
        self.event.set()

class PythonHelper(object):

    @staticmethod
    def run_in_parallel(*functions):
        event=Event()
        processes=dict()
        for function in functions:
            fname=function[0]
            try:fargs=function[1]
            except:fargs=list()
            try:fproc=function[2]
            except:fproc=1
            for i in range(fproc):
                process=ExtProcess(event,target=fname,args=fargs)
                process.start()
                processes[process.pid]=process
        event.wait()
        for process in processes.values():
            process.terminate()
        for process in processes.values():
            process.join()
class Recorder(object):
    def capture(self):
        while True:print("recording")
from z_helper import PythonHelper
from z_recorder import Recorder

def wrapper(fname,*args):
    try:
        PythonHelper.run_in_parallel([fname,args],[Recorder().capture])
        print("success")
    except Exception as e:
        print("failure: {}".format(e))
from z_wrapper import wrapper
from functools import wraps

class Report(object):
    @staticmethod
    def debug(fname):
        @wraps(fname)
        def function(*args):
            wrapper(fname,args)
        return function

正在执行:

from z_report import Report
import time

class Test(object):
    @Report.debug
    def print_x(self,x):
        for index,data in enumerate(range(x)):
            print(index,data); time.sleep(1)

if __name__=="__main__":
    Test().print_x(10)

我将@Wraps添加到以前的版本

我的回溯:

Traceback (most recent call last):
  File "C:InterpretersPython32libpickle.py", line 679, in save_global
    klass = getattr(mod, name)
AttributeError: 'module' object has no attribute 'run_testcase'

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "C:EskyTestsw_Logger.py", line 19, in <module>
    logger.run_logger()
  File "C:EskyTestsw_Logger.py", line 14, in run_logger
    self.run_testcase()
  File "C:EskyTestsw_Decorators.py", line 14, in wrapper
    PythonHelper.run_in_parallel([function,args],[recorder.capture])
  File "C:EskyTestsw_PythonHelper.py", line 25, in run_in_parallel
    process.start()
  File "C:InterpretersPython32libmultiprocessingprocess.py", line 130, in start
    self._popen = Popen(self)
  File "C:InterpretersPython32libmultiprocessingforking.py", line 267, in __init__
    dump(process_obj, to_child, HIGHEST_PROTOCOL)
  File "C:InterpretersPython32libmultiprocessingforking.py", line 190, in dump
    ForkingPickler(file, protocol).dump(obj)
  File "C:InterpretersPython32libpickle.py", line 237, in dump
    self.save(obj)
  File "C:InterpretersPython32libpickle.py", line 344, in save
    self.save_reduce(obj=obj, *rv)
  File "C:InterpretersPython32libpickle.py", line 432, in save_reduce
    save(state)
  File "C:InterpretersPython32libpickle.py", line 299, in save
    f(self, obj) # Call unbound method with explicit self
  File "C:InterpretersPython32libpickle.py", line 623, in save_dict
    self._batch_setitems(obj.items())
  File "C:InterpretersPython32libpickle.py", line 656, in _batch_setitems
    save(v)
  File "C:InterpretersPython32libpickle.py", line 299, in save
    f(self, obj) # Call unbound method with explicit self
  File "C:InterpretersPython32libpickle.py", line 683, in save_global
    (obj, module, name))
_pickle.PicklingError: Can't pickle <function run_testcase at 0x00000000027725C8>: it's not found as __main__.run_testcase

推荐答案

multiprocessing模块通过调用从进程上的选取器来"调用"从进程中的函数。这是因为它必须通过它创建的IPC接口将函数的名称发送到从进程。Pickler找出要使用的正确名称并将其发送,然后在另一端UnPickler将该名称转换回函数。

如果函数是类成员,则在没有帮助的情况下不能正确地对其进行酸洗。@staticmethod成员的情况更糟,因为它们的类型是function,而不是instancemethod类型,这会愚弄Pickler。无需使用multiprocessing

就可以很容易地看到这一点
import pickle

class Klass(object):
    @staticmethod
    def func():
        print 'func()'
    def __init__(self):
        print 'Klass()'

obj = Klass()
obj.func()
print pickle.dumps(obj.func)

生产:

Klass()
func()
Traceback (most recent call last):
 ...
pickle.PicklingError: Can't pickle <function func at 0x8017e17d0>: it's not found as __main__.func

当您尝试Pickle像obj.__init__这样的常规非静态方法时,问题会更加明显,因为Pickler会意识到它实际上是一个实例方法:

TypeError: can't pickle instancemethod objects
然而,

并不是一切都完了。您只需要添加一个间接级别。您可以提供一个在目标进程中创建实例绑定的普通函数,向它发送至少两个参数:(Pickle-able)类实例和函数的名称。我还添加了在调用函数时要使用的任何参数,以确保完整性。然后在目标流程中调用这个普通函数,它调用类的成员函数:

def call_name(instance, name, *args = (), **kwargs = None):
    "helper function for multiprocessing: call instance.getattr(name)"
    if kwargs is None:
        kwargs = {}
    getattr(instance, name)(*args, **kwargs)

现在不是(这是从您的链接帖子复制的):

PythonHelper.run_in_parallel([self.run_testcase],[recorder.capture])

您应该这样做(您可能想要在调用序列上做文章):

PythonHelper.run_in_parallel([call_name, (self, 'run_testcase')],
    [recorder.capture])

(注意:这都是未经测试的,可能存在各种错误)。


更新

我使用了您发布的新代码并进行了试用。

首先,我必须修复z_report.py中的缩进(取消缩进所有class Report)。

完成后,运行它会产生与您显示的错误完全不同的错误:

Process ExtProcess-1:
Traceback (most recent call last):
  File "/usr/local/lib/python2.7/multiprocessing/process.py", line 258, in _bootstrap
    self.run()
  File "/tmp/t/marcin/z_helper.py", line 9, in run
    Process.run(self)
  File "/usr/local/lib/python2.7/multiprocessing/process.py", line 114, in run
recording
[infinite spew of "recording" messages]

修复无休止的"录制"消息:

diff --git a/z_recorder.py b/z_recorder.py
index 6163a87..a482268 100644
--- a/z_recorder.py
+++ b/z_recorder.py
@@ -1,4 +1,6 @@
+import time
 class Recorder(object):
     def capture(self):
-        while True:print("recording")
-
+        while True:
+            print("recording")
+            time.sleep(5)

剩下一个问题:print_x的错误参数:

TypeError: print_x() takes exactly 2 arguments (1 given)

在这一点上,Python实际上为您做了所有正确的事情,只是z_wrapper.wrapper有点过分了:

diff --git a/z_wrapper.py b/z_wrapper.py
index a0c32bf..abb1299 100644
--- a/z_wrapper.py
+++ b/z_wrapper.py
@@ -1,7 +1,7 @@
 from z_helper import PythonHelper
 from z_recorder import Recorder

-def wrapper(fname,*args):
+def wrapper(fname,args):
     try:
         PythonHelper.run_in_parallel([fname,args],[Recorder().capture])
         print("success")
这里的问题是,当您读到z_wrapper.wrapper时,函数参数已经全部捆绑到一个元组中。z_report.Report.debug已有:

    def function(*args):

以便将两个参数(在本例中为main.Test的实例和值10)制成一个元组。您只希望z_wrapper.wrapper将该(单个)元组传递给PythonHelper.run_in_parallel,以提供参数。如果添加另一个*args,该元组将被包装到另一个元组中(这次是一个元素)。(您可以通过在z_wrapper.wrapper中添加print "args:", args来查看这一点。)

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