Threading is a fundamental concept in concurrent programming, allowing multiple threads to run simultaneously within a single process. Here's a quick guide to get started:

1. Basic Concepts

  • Thread Safety: Ensure shared resources are accessed safely using locks or semaphores.
  • Thread Lifecycle: Threads go through states like new, running, waiting, and terminated.
  • Global Interpreter Lock (GIL): Python’s GIL ensures only one thread executes at a time in a single process.
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2. Using Threads in Python

To create threads, use the threading module: 

import threading  

def my_function():  
    print("Thread is running...")  

thread = threading.Thread(target=my_function)  
thread.start()
  • Daemon Threads: Background threads that don’t prevent the program from exiting.
  • Joining Threads: Use join() to wait for a thread to complete before proceeding.
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3. Best Practices

  • Avoid excessive thread creation; use thread pools for efficiency.
  • Prefer concurrent.futures for higher-level thread management.
  • Always handle exceptions in threads to prevent crashes.

For deeper insights into concurrency models, check our Python Concurrency Guide.

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4. Common Use Cases

  • I/O-bound tasks (e.g., file reading, network requests).
  • Parallel processing of independent data chunks.
  • GUI applications to keep the interface responsive.

Expand your knowledge with Python Async Programming for asynchronous task handling.