This article delves into several underutilized yet powerful Python features that enhance code performance, clarity, and maintainability, particularly within the context of the Dagster library. It highlights function overloading using the `typing.overload` decorator, which allows multiple variations of a function with different signatures, and `cached_property` from `functools` for efficient caching of instance method results. It also discusses the use of `contextvars` for managing state across different execution contexts, `typing.get_origin` and `get_args` for runtime type introspection, and the strategic use of `TYPE_CHECKING` to optimize imports for static type checking without runtime overhead. Additionally, `ExitStack` from the `contextlib` library is presented as a versatile way to manage multiple context managers dynamically, ensuring clean and correct resource management. These features collectively empower developers to write more robust and elegant code, emphasizing the importance of mastering language capabilities in an increasingly AI-assisted programming landscape.