Type annotations

Notes in the code saying what type each parameter, return value or name is meant to have, so that people and tools know what a function wants and gives back.

Depth 1 · Foundation

You can read and write a function's signature with types (`rate: float`, `-> str`, `-> None`), and you know Python stores annotations but doesn't check them while it runs.

Depths of understanding

1
Foundation
You can read and write a function's signature with types (`rate: float`, `-> str`, `-> None`), and you know Python stores annotations but doesn't check them while it runs.
Opens after
NoneA function annotated `-> None` gives nothing back, and a missing result is a `None` that a type has to admit to.DictionariesReal programs pass dictionaries and lists around, and a type is most useful when it says what's inside them.
2
Deeper
You can describe the shape of collections in a type (`list[int]`, `dict[str, list[int]]`, `tuple[int, int]`) and use a union like `int | None` for a value that may be missing, so a checker makes every caller handle it.
Master depth 1 first