It can be challenging to manage method overloading in Python, particularly when return types rely on an initialization variable. To provide better type inference, developers can use the @overload decorator or generics instead of a union type. This is particularly useful in scenarios like data modeling for construction materials, where selecting between WoodData and ConcreteData needs to be precise. Using advanced techniques such as type hints, dataclasses, and caching improves both performance and maintainability. These strategies help create cleaner, safer, and more scalable Python code.