python的调用堆栈是否分别在多线程和多处理的线程或进程之间共享？
[英]Does the calling stack in python's shared between the threads or the processes in multithreading and multiprocessing respectively?
问题描述
I am writing a code in python which includes some multiprocessing and multithreading . 
我正在用python写代码，其中包括一些multiprocessing和multithreading 。
My question is: Does the threads or the processes share the same call stack? 我的问题是： 线程或进程共享相同的调用堆栈吗？
I am using the inspect module and I'm afraid that it will return me the wrong value in inspect.stack() . 我正在使用inspect模块，恐怕它将在inspect.stack()返回错误的值。
1 个解决方案
解决方案1
2 已采纳 2017-06-15 16:00:28
No they don't, subprocesses get forked/spawned as separate entities so each Process starts off effectively as a completely new Python instance. 不，它们不是，子流程作为单独的实体被派生/生成，因此每个流程都作为一个全新的Python实例有效地启动。
Python hides away some of the nastiness of that by transparently pickling/unpickling data to be transferred between processes but they all get their own stack, their own GIL and all that goes with it. Python通过透明地腌制/取消腌制要在进程之间传输的数据来掩盖其中的某些麻烦，但是它们都拥有自己的堆栈，自己的GIL以及随之而来的所有内容。
Multithreading is a different story - threads do share the underlying stack but Python partitions them to appear as each has their own stack so inspect.stack() results can be confusing/unpredictable.. 多线程是另一inspect.stack() -线程确实共享底层堆栈，但是Python对它们进行分区以使其显示为每个都有自己的堆栈，因此inspect.stack()结果可能令人困惑/无法预测。
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