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

## Overview

Let's start with a repository based on the popular SQL database [PostgreSQL](https://www.postgresql.org/). It can be accessed from Python in many ways, but one of the best ways is through the SQLAlchemy interface. [SQLAlchemy](https://www.sqlalchemy.org/) is an #key# ORM: A package that maps objects (as in object-oriented) to a relational database. #key#s and can normally be found in a web framework such as Django. It can also be found in stand-alone packages, such as in our case.

## Learning about ORMs

The important thing about #key# ORMs: A package that maps objects (as in object-oriented) to a relational database. #key#is that they're very good examples of something we shouldn't try to mock. If we properly mock the SQLAlchemy structures used when we query the database, then the code will become very complex. This isn't easy to write and maintain. This is because every single change in a query (or queries) results in the need to write another series of mocks.


# Overview

Let's start with a repository based on the popular SQL database [PostgreSQL](https://www.postgresql.org/). It can be accessed from Python in many ways, but one of the best ways is through the SQLAlchemy interface. [SQLAlchemy](https://www.sqlalchemy.org/) is an #key# ORM: A package that maps objects (as in object-oriented) to a relational database. #key#s and can normally be found in a web framework such as Django. It can also be found in stand-alone packages, such as in our case.

# Learning about ORMs

The important thing about #key# ORMs: A package that maps objects (as in object-oriented) to a relational database. #key#is that they're very good examples of something we shouldn't try to mock. If we properly mock the SQLAlchemy structures used when we query the database, then the code will become very complex. This isn't easy to write and maintain. This is because every single change in a query (or queries) results in the need to write another series of mocks.


Let’s learn about the vital role of PostgreSQL in a Python application.

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

A Repository Based on PostgreSQL

Overview