Python threading allows you to run multiple threads (smaller independent processes) within a program to improve performance and handle concurrency. Here's a quick guide to get started:

🧩 Basic Concepts

  • Thread is a lightweight sub-process that can run concurrently with others
  • GIL (Global Interpreter Lock) ensures only one thread executes Python bytecode at a time
  • Thread pooling manages a group of ready-to-use threads efficiently
Python Threading Concepts

🛠️ Core Implementation

Use the threading module to create threads:

import threading

def worker():
    print("Thread is running")

thread = threading.Thread(target=worker)
thread.start()

🔒 Advanced Topics

  • Locks prevent race conditions with threading.Lock()
  • Semaphores control access to resources using threading.Semaphore()
  • Thread synchronization with threading.Condition() or threading.Event()
Thread Synchronization

⚠️ Best Practices

  • Avoid shared state between threads when possible
  • Use concurrent.futures for more advanced thread management
  • Be aware of the GIL limitations for CPU-bound tasks

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