Python Projects & Utilities

Project-oriented Python posts that sit between fundamentals and advanced AI engineering.

Series Progress

All Posts in This Series

Part 1: Loop like a Pro with Python Iterators 18 May, 2023 This post explains the basics of Python iterators and their successful alternatives, such as list comprehension. While these alternatives use more memory, they are still useful in practice. The post also covers advanced techniques for working with iterators, including using the itertools module and creating generators with the yield keyword. By mastering iterators, readers can create elegant and efficient code and become better Python programmers.
Part 2: Joking Flask App 10 Dec, 2023 Build a joke-serving web app with Flask from scratch. We cover routing, Jinja2 templates, static files, form handling, and how to avoid the classic "request is not defined" trap.
Part 3: What is Docker? 11 Feb, 2024 Docker lets you quickly deploy microservices, cloud-native architectures, or web apps. In this post, we will use Docker to create a reliable environment for Flask applications that efficiently manages dependencies and deployment intricacies.
Part 4: Logging in Python 27 Jul, 2024 In this post, I cover everything from the basics of logging to configuring logging to output messages to different destinations. I also included some examples of logging levels and how to log messages at different levels based on the severity of the issue.
Part 5: Python Virtual Environments 24 Jan, 2025 If you are working on multiple Python projects, you will eventually run into a dependency nightmare. Virtual environments solve this by isolating packages per project. Here is my practical guide to creating, managing, and safely deleting Python virtual environments.
Part 6: Python Flask TODO App 11 Feb, 2025 Ready to build your first web application? In this tutorial, we will construct a fully functional TODO app using Python, Flask, and SQLite. You will learn how to route requests, manage a database, and render HTML templates.
Part 7: Anaconda Environments 5 Apr, 2022 It might be challenging to manage different projects and their requirements when we do Python coding with loads of varying package versions and intricate setups. Luckily, we have a secret tool for managing and switching between different setups or environments. Conda is a package manager allowing us to work with different environments from a command line. Please do not mix it up with the Anaconda, which is helpful in scientific computing and includes a set of packages including NumPy, Scipy, Jupiter notebooks, and Conda.
Part 8: Brewing with Homebrew 11 Aug, 2025 Manually compiling software from source or navigating dependency hell on macOS is inefficient. Homebrew solves this by providing a robust package management layer. Here is a complete setup guide, command cheat sheet, and a list of essential developer tools.

Getting Started

New to this series? Start with Part 1: Loop like a Pro with Python Iterators.

Each post builds on the previous one, so reading them in order is recommended. Each post also works on its own if you need to jump to a specific topic.