Feb 06 2019 — In a previous post, I explained how concepts from functional programming can be incorporated with object-oriented code to improve the tedious and mandatory task of error handling and input validation through the use of the Result class. That post explained how to implement the Result class in C#. Since I have been writing mostly Python code lately, I created a new implementation and documented its use. Due to Python’s duck-typing, this implementation is (IMO) more natural and makes reasoning about the code it supports much easier.

This tutorial series provides step-by-step instructions and in-depth explanations to guide you through the process of creating a robust, production-quality REST API. The toolstack consists of Flask, Flask-RESTx, pyjwt, SQLAlchemy and other packages. Code quality is a major focus, with considerable time dedicated to testing (using pytest), logging and tools such as coverage, flake8 and mypy. The tutorial concludes by creating a process that continuously integrates (with tox, travis/circle CI, coveralls) and deploys the API (with either Github or Azure DevOps to Heroku).

In Part 1, the core concepts of REST and JWTs are introduced, project dependencies are described and installed, and the project is fully configured for prod/dev environments. The flask server and CLI are demonstrated to ensure the setup was performed correctly before moving on to Part 2.

Part 2 covers the basics of SQLAlchemy, the Flask-SQLAlchemy extension, and the Flask-Migrate extension. The process of creating a new database table to store user information by defining a class and “registering” it with SQLAlchemy is demonstrated. Next, setting up a system that manages changes to a database schema is thoroughly explained and demonstrated. After initializing the database, functions to encode and decode JSON Web Tokens (JWTs) are created. This section concludes with an introduction to pytest fixtures and examples of several test cases that verify the ability to encode/decode JWTs issued by our API.