my code became much easier to maintain once i stopped thinking of it as writing "algorithms" and "processes" and started thinking of it as a series of type conversions. structuring what lives where became easier, naming things became systematic and consistent, and writing unit tests became simple.
This resonates strongly! In Python, I often now find myself declaring Pydantic data structures, and then adding classmethods and regular methods on them to facilitate converting between them. It makes for great APIs (dot-chaining from one type to another), well-defined types (parse, don’t validate) and keeps the code associated with the type.
class Profile:
...
class User:
@classmethod
def from_profile(cls, profile: Profile) -> 'User':
...
def to_profile(self) -> Profile:
...
1. Keep isomorphisms to one class only: Don't put two def to_${OTHER_MODEL_NAME} in each class, instead (like you said) create one static mapping (@classmethod) and one instance mapping
2. Add a mapping to the one class that feels more generalized out of the two: A more generalized data model will probably be used a lot more throughout the application
3. The creation of instances should be pure: If a mapping has side effects and needs to await something then it isn't just a mapping - first resolve all necessary dependencies, then do the mapping