Decorators 101: How Do Python Decorators "Add Functionality" to Functions?

Python decorators leverage the "first-class citizen" nature of functions to dynamically add functionality (e.g., logging) without modifying the original function's code, solving the problem of duplicate code. Essentially, they are functions that take the original function and return a "wrapper" function, simplified by the @ syntactic sugar for calling. Key details: *args and **kwargs adapt to arbitrary parameters, while functools.wraps preserves the original function's metadata. Parameterized decorators require nesting two layers of functions (outer for parameter passing, inner for wrapping). Application scenarios include logging, performance testing, permission verification, caching, etc. The execution order of multiple decorators is "bottom-up". Through closures and function nesting, decorators achieve code decoupling and maintainability.