Language Mastery
The language's deep end, used deliberately: model your data precisely, define contracts with protocols and ABCs, and let the type system catch mistakes before your users do.
Most bugs in a growing codebase are not logic errors. They are states that should never have been constructible: an order with a delivery date and no address, a config half-populated because a caller passed the dict directly, an object that satisfies an interface everywhere except the one call site nobody tested. This domain is about making those states impossible to express rather than remembering to check for them.
It has two halves that meet in the middle. The first is modelling the data itself — dataclasses used deliberately rather than as terser tuples, immutability where mutation buys you nothing, and validation placed at construction so an object that exists is an object that is valid. The second is the contract between components: Python offers both structural typing, where anything with the right shape qualifies, and nominal typing, where a class must declare its intent by inheriting — Protocols and abstract base classes respectively — and choosing between them is a design decision with real consequences for testing, for extension by code you do not control, and for what the type checker can prove.