Gain insights into clean architecture using Python. Delve into layered systems, design efficient applications, and integrate web components, error handling, and databases with test-driven development practices.

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Python Execution

Flask

Flask + Postgres

Python Test

Clean architecture is a software design methodology that separates the processes of an application into discrete steps instead of presenting them as “spaghetti code.” With the versatility of Python, software engineers can build performant, modular applications quickly using the Flask framework.

This course will help you build better applications using the principles of clean architecture. You’ll start with an introduction to data flow in clean systems and learn about the advantages of layered architectures. Next, you’ll learn system components and the connections between application layers. You’ll then design and build a clean system using Python by layering components in guided coding exercises. Finally, you’ll learn how to add functional components for the web, handle errors, and work with external databases using both Postgres and MongoDB. At each step, you’ll use test-driven development practices to ensure robust functionality.

Clean Architecture in Python

Now that our implementation of requests and responses is complete, we can implement the final version of our use case. In our program, a proper validation of the incoming request for the `room_list_use_case` function is still missing. So, it doesn’t yet return a suitable response when something goes wrong.

# Update test case

The `test_room_list_without_parameters` test must match the new API, so we add `filters=None` to `assert_called_with` in the code below:

def test_room_list_without_parameters(domain_rooms):
    repo = mock.Mock()
    repo.list.return_value = domain_rooms

    request = build_room_list_request()

    response = room_list_use_case(repo, request)

    assert bool(response) is True
    repo.list.assert_called_with(filters=None)
    assert response.value == domain_rooms

There are three new tests that we can add to check the behavior of the use case when `filters` are not `None`. The first test checks if the values of the key `filters` in the dictionary that are used to create the request are actually used when calling the repository.


Let’s learn about error management in use cases and internal systems.


Get Started

A Day in the Life of a Clean System

Components of Clean Architecture

A Simple Coding Example

Add a Web Application

Error Management

Integration with a Real External System Postgres

Integration with a Real External System MongoDB

Run a Production-ready System

Appendix

Error Management in a Use Case

Update test case