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.

tarball.tar.gz

POSTGRES_USER

POSTGRES_PASSWORD

POSTGRES_HOSTNAME

APPLICATION_DB

POSTGRES_PORT

POSTGRES_DB

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

Before we move on to implementation, we always test the system to see if it will work with all of its components. To do this, we need to label the integration tests, exclude them by default, and create a way to run them. Since pytest supports labels, called **marks**, we can use this feature to add a global mark to an entire module.

# Update the test cases

Let’s put the following code into the `tests/repository/postgres/test_postgresrepo.py` file.

import pytest

pytestmark = pytest.mark.integration

def test_dummy():
    pass

The module attribute `pytestmark` labels every test in the module with the `integration` tag. To verify that this works, we add a `test_dummy` test function, which always passes.

# Update the pytest configuration

The marker needs to be registered in `pytest.ini`, as in the following code:

[pytest]
minversion = 2.0
norecursedirs = .git .tox requirements*
python_files = test*.py
markers = integration: integration tests

# Perform the integration testing

We can now run `pytest -svv -m integration` to ask pytest to run only the tests marked with that label. The `-m` option supports a rich syntax that we can learn more about from the [documentation](https://docs.pytest.org/en/latest/example/markers.html).

```
$ pytest -svv -m integration
/*Output
========================= test session starts ===========================
platform linux -- Python XXXX, pytest-XXXX, py-XXXX, pluggy-XXXX --
cabook/venv3/bin/python3
cachedir: .cache
rootdir: cabook/code/calc, inifile: pytest.ini
plugins: cov-XXXX
collected 36 items / 35 deselected / 1 selected

tests/repository/postgres/test_postgresrepo.py::test_dummy PASSED

=================== 1 passed, 35 deselected in 0.20s ====================
*/
```

While this is enough to run our integration tests selectively, it’s not enough to skip them by default. To do this, we can alter the pytest setup to label all the tests as ones that need to be skipped, but then we’ll no longer be able to run them. The standard way to implement this is to define a new command-line option and to process each marked test according to the value of this option.

# Update the test configuration

We’ve already updated the file `tests/conftest.py` with the following code, which will update the test configuration:

Let’s learn about how to label integration tests with the pytest library.

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

Label Integration Tests

Update the test cases

Update the pytest