Python Passport

Standard Library

Python threading Module

Python Threading Basics

Python threading module manages threads, with Thread class.

Introduction to Python threading Module

The threading module in Python is a powerful tool for concurrent execution of code. It allows developers to run multiple threads (smaller units of a process) at the same time, which can be beneficial for I/O-bound tasks and achieving parallelism in your applications.

Creating a Thread

The core of the threading module is the Thread class. To create a new thread, you simply instantiate the Thread class and pass a target function that the thread will execute. Below is a simple example of creating and starting a thread:

Using Threads with Arguments

Threads can also take arguments, allowing you to pass data to the target function. You can use the args parameter when creating a thread to pass these arguments:

Thread Synchronization

When working with threads, synchronization is crucial to prevent race conditions. The threading module provides several synchronization primitives such as Lock, RLock, Semaphore, and Event. Here's how you can use a Lock to ensure that only one thread can access a shared resource at a time:

Daemon Threads

In Python, threads can be marked as daemon threads. A daemon thread will shut down immediately when the program exits, meaning it does not prevent the program from terminating. This is useful for background tasks. To set a thread as a daemon, use the daemon attribute:

Conclusion

The Python threading module provides a simple yet effective way to perform concurrent execution in your programs. While threads can greatly improve performance for I/O-bound tasks, it's important to manage them carefully to avoid common pitfalls such as race conditions and deadlocks. By understanding and utilizing synchronization primitives and thread properties like daemon, you can harness the full power of threads in Python.

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