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在本文中，咱们将学习如何应用多解决模块中的特定 Python 类（过程类）。我将通过示例为您提供疾速概述。
什么是多解决模块？
还有什么比从官网文档中提取模块更好的形式来形容模块呢？Multiprocessing 是一个应用相似于线程模块的 API 反对生成过程的包。多解决包提供本地和近程并发，通过应用子过程而不是线程无效地回避全局解释器锁。
线程模块不是本文的重点，但总而言之，线程模块将解决一小段代码执行（轻量级且具备共享内存），而多解决模块将处理程序执行（较重且齐全隔离）。
一般来说，多解决模块提供了各种其余类、函数和实用程序，可用于处理程序执行期间执行的多个过程。如果程序须要在其工作流程中利用并行性，该模块专门设计为交互的次要点。咱们不会探讨多解决模块中的所有类和实用程序，而是将重点关注一个十分具体的类，即过程类。
什么是过程类？
在本节中，咱们将尝试更好地介绍过程是什么，以及如何在 Python 中辨认、应用和治理过程。正如 GNU C 库中所解释的：“过程是调配系统资源的根本单位。每个过程都有本人的地址空间和（通常）一个控制线程。一个过程执行一个程序；能够让多个过程执行雷同的程序程序，但每个过程在其本人的地址空间内都有本人的程序正本，并独立于其余正本执行它。”
但这在 Python 中是什么样子的呢？到目前为止，咱们曾经设法对过程是什么、过程和线程之间的区别进行了一些形容和参考，但到目前为止咱们还没有涉及任何代码。好吧，让咱们扭转一下，用 Python 做一个非常简单的流程示例：
#!/usr/bin/env python
import os
# A very, very simple process.
if __name__ == "__main__":
print(f"Hi! I'm process {os.getpid()}")这将产生以下输入：
[r0x0d@fedora ~]$ python /tmp/tmp.iuW2VAurGG/scratch.py
Hi! I'm process 144112正如您所看到的，任何正在运行的 Python 脚本或程序都是它本人的一个过程。
创立子过程
那么在父过程中生成不同的子过程又如何呢？好吧，要做到这一点，咱们须要多解决模块中的 Process 类的帮忙，它看起来像这样：
#!/usr/bin/env python
import os
import multiprocessing
def child_process():
print(f"Hi! I'm a child process {os.getpid()}")
if __name__ == "__main__":
print(f"Hi! I'm process {os.getpid()}")
# Here we create a new instance of the Process class and assign our
# `child_process` function to be executed.
process = multiprocessing.Process(target=child_process)
# We then start the process
process.start()
# And finally, we join the process. This will make our script to hang and
# wait until the child process is done.
process.join()这将产生以下输入：
[r0x0d@fedora ~]$ python /tmp/tmp.iuW2VAurGG/scratch.py
Hi! I'm process 144078
Hi! I'm a child process 144079对于上一个脚本的一个十分重要的注意事项：如果您不应用 process.join() 来期待子过程执行并实现，那么该点的任何其余后续代码将理论执行，并且可能会变得有点难以同步您的工作流程。
思考以下示例：
#!/usr/bin/env python
import os
import multiprocessing
def child_process():
print(f"Hi! I'm a child process {os.getpid()}")
if __name__ == "__main__":
print(f"Hi! I'm process {os.getpid()}")
# Here we create a new instance of the Process class and assign our
# `child_process` function to be executed.
process = multiprocessing.Process(target=child_process)
# We then start the process
process.start()
# And finally, we join the process. This will make our script to hang and
# wait until the child process is done.
#process.join()
print("AFTER CHILD EXECUTION! RIGHT?!")该代码片段将产生以下输入：
[r0x0d@fedora ~]$ python /tmp/tmp.iuW2VAurGG/scratch.py
Hi! I'm process 145489
AFTER CHILD EXECUTION! RIGHT?!
Hi! I'm a child process 145490当然，断言下面的代码片段是谬误的也是不正确的。这齐全取决于您想要如何应用该模块以及您的子过程将如何执行。所以要明智地应用它。
创立各种子过程
如果要生成多个过程，能够利用 for 循环（或任何其余类型的循环）。它们将容许您创立对所需流程的尽可能多的援用，并在稍后阶段启动 / 退出它们。
#!/usr/bin/env python
import os
import multiprocessing
def child_process(id):
print(f"Hi! I'm a child process {os.getpid()} with id#{id}")
if __name__ == "__main__":
print(f"Hi! I'm process {os.getpid()}")
list_of_processes = []
# Loop through the number 0 to 10 and create processes for each one of
# them.
for i in range(0, 10):
# Here we create a new instance of the Process class and assign our
# `child_process` function to be executed. Note the difference now that
# we are using the `args` parameter now, this means that we can pass
# down parameters to the function being executed as a child process.
process = multiprocessing.Process(target=child_process, args=(i,))
list_of_processes.append(process)
for process in list_of_processes:
# We then start the process
process.start()
# And finally, we join the process. This will make our script to hang
# and wait until the child process is done.
process.join()这将产生以下输入：
[r0x0d@fedora ~]$ python /tmp/tmp.iuW2VAurGG/scratch.py
Hi! I'm process 146056
Hi! I'm a child process 146057 with id#0
Hi! I'm a child process 146058 with id#1
Hi! I'm a child process 146059 with id#2
Hi! I'm a child process 146060 with id#3
Hi! I'm a child process 146061 with id#4
Hi! I'm a child process 146062 with id#5
Hi! I'm a child process 146063 with id#6
Hi! I'm a child process 146064 with id#7
Hi! I'm a child process 146065 with id#8
Hi! I'm a child process 146066 with id#9数据通信
在上一节中，我形容了向 multiprocessing.Process 类构造函数增加一个新参数 args。此参数容许您将值传递给子过程以在函数外部应用。但你晓得如何从子过程返回数据吗？
您可能会认为，要从子级返回数据，必须应用其中的 return 语句能力真正检索数据。过程非常适合以隔离的形式执行函数，而不会烦扰共享资源，这意味着咱们晓得从函数返回数据的失常且罕用的形式。在这里，因为其隔离而不容许。
相同，咱们能够应用队列类，它将为咱们提供一个在父过程与其子过程之间通信数据的接口。在这种状况下，队列是一个一般的 FIFO（先进先出），具备用于解决多解决的内置机制。
思考以下示例：
#!/usr/bin/env python
import os
import multiprocessing
def child_process(queue, number1, number2):
print(f"Hi! I'm a child process {os.getpid()}. I do calculations.")
sum = number1 + number2
# Putting data into the queue
queue.put(sum)
if __name__ == "__main__":
print(f"Hi! I'm process {os.getpid()}")
# Defining a new Queue()
queue = multiprocessing.Queue()
# Here we create a new instance of the Process class and assign our
# `child_process` function to be executed. Note the difference now that
# we are using the `args` parameter now, this means that we can pass
# down parameters to the function being executed as a child process.
process = multiprocessing.Process(target=child_process, args=(queue,1, 2))
# We then start the process
process.start()
# And finally, we join the process. This will make our script to hang and
# wait until the child process is done.
process.join()
# Accessing the result from the queue.
print(f"Got the result from child process as {queue.get()}")它将给出以下输入：
[r0x0d@fedora ~]$ python /tmp/tmp.iuW2VAurGG/scratch.py
Hi! I'm process 149002
Hi! I'm a child process 149003. I do calculations.
Got the result from child process as 3异样解决
解决异样是一项非凡且有些艰难的工作，咱们在应用流程模块时必须不断地实现它。起因是，默认状况下，子过程内产生的任何异样将始终由生成它的 Process 类解决。
上面的代码引发带有文本的异样：
#!/usr/bin/env python
import os
import multiprocessing
def child_process():
print(f"Hi! I'm a child process {os.getpid()}.")
raise Exception("Oh no! :(")
if __name__ == "__main__":
print(f"Hi! I'm process {os.getpid()}")
# Here we create a new instance of the Process class and assign our
# `child_process` function to be executed. Note the difference now that
# we are using the `args` parameter now, this means that we can pass
# down parameters to the function being executed as a child process.
process = multiprocessing.Process(target=child_process)
try:
# We then start the process
process.start()
# And finally, we join the process. This will make our script to hang and
# wait until the child process is done.
process.join()
print("AFTER CHILD EXECUTION! RIGHT?!")
except Exception:
print("Uhhh... It failed?")输入后果：
[r0x0d@fedora ~]$ python /tmp/tmp.iuW2VAurGG/scratch.py
Hi! I'm process 149505
Hi! I'm a child process 149506.
Process Process-1:
Traceback (most recent call last):
File "/usr/lib64/python3.11/multiprocessing/process.py", line 314, in _bootstrap
self.run()
File "/usr/lib64/python3.11/multiprocessing/process.py", line 108, in run
self._target(*self._args, **self._kwargs)
File "/tmp/tmp.iuW2VAurGG/scratch.py", line 7, in child_process
raise Exception("Oh no! :(")
Exception: Oh no! :(AFTER CHILD EXECUTION! RIGHT?! 如果您跟踪代码，您将可能留神到在 process.join() 调用之后认真搁置了一条 print 语句，以模仿父过程仍在运行，即便在子过程中引发了未解决的异样之后也是如此。
克服这种状况的一种办法是在子过程中理论解决异样，如下所示：
#!/usr/bin/env python
import os
import multiprocessing
def child_process():
try:
print(f"Hi! I'm a child process {os.getpid()}.")
raise Exception("Oh no! :(")
except Exception:
print("Uh, I think it's fine now...")
if __name__ == "__main__":
print(f"Hi! I'm process {os.getpid()}")
# Here we create a new instance of the Process class and assign our
# `child_process` function to be executed. Note the difference now that
# we are using the `args` parameter now, this means that we can pass
# down parameters to the function being executed as a child process.
process = multiprocessing.Process(target=child_process)
# We then start the process
process.start()
# And finally, we join the process. This will make our script to hang and
# wait until the child process is done.
process.join()
print("AFTER CHILD EXECUTION! RIGHT?!")当初，您的异样将在您的子过程内解决，这意味着您能够管制它会产生什么以及在这种状况下应该做什么。
总结
当工作和实现依赖于并行形式执行的解决方案时，多解决模块十分弱小，特地是与 Process 类一起应用时。这减少了在其本人的隔离过程中执行任何函数的惊人可能性。
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