Phase 0: The AI Code Quality Crisis · 40 min · Python · pytest · Hypothesis

Setting Up Your Testing Environment

Every tool in this course runs locally. Set them up once, use them for 55 labs.

Real-world application: Engineers who can set up and configure a complete AI code testing toolchain demonstrate practical readiness -- they can start testing AI code on day one, not just talk about it theoretically. This is the minimum viable setup for the role.

What you will learn

Install and configure pytest, Hypothesis, mutmut, Semgrep, Ruff, and mypy
Set up pre-commit hooks for AI-generated code verification
Create the project scaffold that all 55 labs in this course depend on
Run a smoke test that verifies the entire toolchain is working

Introduction

Setting Up Your Testing Environment

Objective

Run the environment setup script to verify the toolchain and generate the project scaffold, then run the smoke test to confirm everything works.

Every tool in this course runs locally. Set them up once, use them for 55 labs.

Unlock the full lesson

You've read the first 2 sections. The rest of this lesson covers The Problem, The Concept, Build, Check Yourself, Key Terms & Next — plus a hands-on lab, quiz, and project artifact.

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