A thread is the smallest unit of execution within a process. Multiple threads can run concurrently in the same process, sharing memory and resources but maintaining their own execution stacks and local variables. In Python, threads are particularly useful for I/O-bound tasks (e.g., file operations, network requests) where much time is spent waiting for external events.

Python’s built-in threading module provides tools to create and manage threads. However, due to the Global Interpreter Lock (GIL) in CPython, only one thread executes Python bytecode at a time, so threading doesn’t speed up CPU-bound tasks but is effective for concurrency in I/O-heavy programs.

Basic Example: Creating and Running Threads