Things to pay attention to when using locks in Python threads

The content of this article is about what you should pay attention to when using locks in Python threads. It has certain reference value. Friends in need can refer to it. I hope it will be helpful to you.

When using lock primitives such as Lock, RLock, and Semphore, you must be more careful. The incorrect use of locks can easily lead to deadlock or mutual competition. Code that relies on locks should ensure that the lock can be released normally when an exception occurs.

Typical code is as follows:

try:
    lock.acquire()
    #关键部分
    ...
finally:
    lock.release()

In addition, all types of locks also support context management protocols (more concise to write):

The with statement automatically acquires the lock and controls it The lock is automatically released when the stream leaves the context.

with lock:
    #关键部分
    ...

In addition, when writing code, you should generally avoid acquiring multiple locks at the same time. For example, you should try to avoid the following:

This notification is very uniform and leads to mysterious deadlocks in the application, although it can be solved with the centralized strategy Avoid situations like this (like hierarchical locking), but it's best to avoid such nested locks when writing your code.

with lock_A:
    #关键部分
    ...
    with lock_B:
        #B的关键部分
        ...

Although it is possible to write very traditional multithreaded programs in Python using various combinations of locks and synchronization primitives, there is one preferred way of programming that trumps all others: multithreaded programs Organized into a collection of multiple independent tasks, these tasks communicate through message queues, such as the queue module to be discussed below.

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