Synchronous programming executes tasks sequentially, blocking the execution until a task is complete. Asynchronous programming allows multiple tasks to run concurrently, improving performance for I/O-bound operations.

The differences between synchronous and asynchronous programming in Python are fundamental to how applications manage tasks and resources. Synchronous programming is the traditional model where tasks are executed sequentially, meaning that each task must complete before the next one begins. This approach can lead to inefficiencies, particularly in scenarios involving I/O-bound operations, such as network requests or file reading, where the program spends a lot of time waiting. On the other hand, asynchronous programming allows for concurrent execution of tasks. This is achieved through the use of asynchronous functions and the await keyword, enabling the program to perform other operations while waiting for I/O tasks to complete. This concurrency significantly improves performance, especially in applications that handle multiple requests or tasks simultaneously, like web servers or APIs. Frameworks like FastAPI and libraries like asyncio in Python provide robust support for asynchronous programming, making it easier for developers to build high-performance applications. By understanding these differences, developers can choose the most suitable approach based on their application requirements.