Use type hints to communicate intent and catch mismatches before they become runtime bugs.
The core idea
Type hints describe the expected types of variables, function arguments, and return values. Python does not automatically enforce all annotations at runtime, but editors, linters, and type checkers can use them to find inconsistencies.
A practical way to approach it
Start with public functions and data structures. Add clear parameter and return types, use Optional or union types where values may be absent, and represent structured records with dataclasses or typed models when appropriate. Avoid adding complicated annotations that make a simple function harder to read.
Try it in a small project
Take a function that processes a list of scores and annotate its input and output. Run a type checker and deliberately pass a string where a number is expected to see how the feedback helps.
Common mistakes to avoid
Hints do not replace input validation. Data arriving from a form, file, or network should still be checked at runtime.
Key takeaway
Keep the first version small, make your assumptions explicit, and verify the result with a repeatable test. For production use, check the current official documentation for the tools and versions you choose.