Multithreading in Python is a programming technique that allows multiple threads to run concurrently, enabling a program to perform multiple tasks simultaneously. This can lead to improved performance, especially for tasks that are I/O-bound, such as reading files or handling user input, as it allows the program to remain responsive while executing long-running operations ⁴.

In Python, the threading module provides the necessary tools to create and manage threads. Each thread operates independently, with its own program counter and stack, which allows for parallel processing. However, it’s important to note that Python’s Global Interpreter Lock (GIL) can limit the performance benefits of multithreading for CPU-bound tasks, as it restricts the execution of multiple threads in a single process ⁴⁵.

While multithreading can enhance performance, it can also introduce complexity into the code, making it harder to debug. Proper synchronization techniques, such as using locks, are essential to prevent race conditions when multiple threads access shared resources ⁴.