Sometimes even the simplest programs deserve solid testing—especially when you're working in a team or trying to set strong standards for code quality. In this note, we'll take the most basic example—"Hello, World!"—and build out everything around it to demonstrate how doctests can be used effectively, even for something so trivial. The goal is to build intuition for testing, not just solve a toy problem.
So I’ve been thinking lately about testing strategies again, and one question came up that I kept circling back to: does every function in my Python codebase need to have a doctest?
If you're writing doctests in Python using Gitpod or VS Code, you don’t need much to get started. Python’s built-in doctest module lets you write examples in your function’s docstring using the familiar >>> prompt, and then run those examples as tests. This is great for small, focused functions or when you want your documentation to double as lightweight tests.
Testing Python Apps with Pytest and Doctest: A Symbiotic Approach
How to test an app using both pytest and doctest in a complementary (symbiotic) way:
Writing tests in Python helps ensure that your code works correctly. In this guide, we'll use two popular testing tools: the built-in unittest module and the third-party library pytest. We'll walk through both using examples related to vegetables and AI model names.
As a senior or Python developer, refining your team's pre-commit setup can drastically improve code quality, consistency, and onboarding speed. Below are key tips and techniques to supercharge your pre-commit experience.
Tools like pre-commit help ensure all checks (type checking, linting, formatting, etc.) are run before code is committed. It integrates easily with Git and runs defined hooks automatically when git commit is executed.
Before diving into Shift Left, which emphasizes catching bugs, performance, and security issues early in the software development lifecycle, it’s important for new programmers to learn the foundational paradigms that support this philosophy.
These paradigms teach early thinking, good code hygiene, and automation — all of which are building blocks of effective software engineering.