Feb 27 2020 — Decorators can be a daunting topic when first encountered. While the Zen of Python states “There should be one– and preferably only one –obvious way to do it”, there are many, equally valid ways to implement the same decorator. These different methods can be categorized as either function-based, class-based, or a hybrid of both. In this post I will explain the design and behavior of Python decorators and provide examples of decorators that I frequently use in my own code.
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).