Phase 3: Property-Based Testing for AI Code · 55 min · Python · Hypothesis · pytest

Hypothesis Python PBT

@given is the new @test. Strategies are the new fixtures.

Real-world application: Engineers who can write Hypothesis property tests with @given, strategies, and shrinking demonstrate practical PBT skills that catch AI logic errors at scale.

What you will learn

Write Hypothesis property tests using @given and strategies
Use built-in strategies: integers, text, lists, floats, dictionaries
Compose strategies using composite and one_of
Apply shrinking to find minimal counterexamples
Use the Hypothesis database to reproduce failures

Introduction

Hypothesis Python PBT

Objective

Run the Hypothesis PBT demo testing an AI-generated parse_date function with a leap year bug. Observe how @given, strategies, shrinking, and the counterexample database work together to find and minimize the bug.

@given is the new @test. Strategies are the new fixtures.

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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