Python Interfaces Tutorial

This project is all about showing how to create and use interfaces in Python using Protocols, which were added in Python 3.8.

If you want to use Protocols before Python 3.8 you can use typing_extensions

I'm a big fan of Clean Architecture, which was described in the book with the same name and in Clean Architectures for Python. I wanted to apply this architecture in this project.

I could have gone much further with some concepts, but I wanted to keep things as simple as I could.

Entities

I created a BaseEntity which only has an id property which is immutable once it has a value. The id is supposed to be set on saving the entity.

The Person entity can be found in people.entities.py. As you can see it is a very simple entity with a name and a date_of_birth.

Repositories

Repositories take care of persisting and retrieving data to some kind of storage. Usually I would also include a Unit of Work mechanism but I left that out for the sake of simplicity.

PersonRepositoryProtocol is the interface. It only contains two abstract methods that defines how a class that implements this interface should behave.

As an example I created two implementations, one for a SQLite database and one for json files. Again, I would usually use a framework like Django or SQLAlchemy, but I wanted to keep this example simple.

Repository Tests

The repository tests check whether the classes have correctly implemented the interface. They actually use the database and a json file, which makes them integration tests.

A proper application design makes sure that only the repositories have to use the actual storage. All other tests can use a Mock of the PersonRepositoryProtocol which you can read next.

Use Cases

Use cases handle the business logic of the application. The use cases in this application are very simple, since the business logic is very simple. But you might imagine that they can be a lot more complicated.

Each use case uses dependency injection to get a PersonRepositoryProtocol, which it will use during execution.

Use Case Tests

The use case tests use a mock object created from the PersonRepositoryProtocol. We don't need to talk to the actual storage. All we need to know is whether the use case calls the correct methods on the repository.

How to use this?

Now you might ask yourself how to use this in practice. Let's take a simple example:

In this example we'll use the PersonJsonRepository and we'll save people.json in the home directory.

if __name__ == "__main__":
    people_file = Path() / "people.json"
    repo = PersonJsonRepository(people_file)

    person = Person("Johan Vergeer", date(1980, 1, 1))

    add_person_use_case = AddPersonUseCase(repo)

    add_person_use_case.execute(person)

And that's it. This is a very simple example, but you can also use this in a CLI app using Click or in a webapp using Flask. When you want to use another storage, just implement the PersonRepositoryProtocol and inject it into the use cases.

So what's next?

As I stated in the example above, you can use the use cases in any framework. Just be sure you keep the entities and use cases separated from the frameworks.

If you still want to take it up a notch you can take a look at a dependency injection framework. I listed a few in my article on dependency injection frameworks.

Contribute

If you have any ideas feel free to create an issue or a pull request.

After cloning the repository you can install the dependencies with poetry install

Next you need to install pre-commit with pre-commit install.

johanvergeer / python-interfaces