What problem does it solve? Python teams struggle to choose the right test distribution, configure modern tooling like pytest, Ruff, and mypy, and build reliable quality gates in Azure DevOps pipelines. This Skill provides a complete practitioner reference covering test strategy theory through production pipeline YAML. ## Core Features & Use Cases - Test Strategy & Design: Choose between Test Pyramid, Testing Trophy, and Honeycomb models, and apply black-box techniques like equivalence partitioning, boundary value analysis, decision tables, and state transition testing. - pytest Ecosystem Mastery: Configure fixtures, parametrize, conftest hierarchies, marks, coverage thresholds, TDD workflows, BDD with pytest-bdd, and contract testing with Pact. - Advanced Quality Techniques: Implement property-based testing with Hypothesis, mutation testing with mutmut or cosmic-ray, and strict static analysis with Ruff and mypy. - Azure Cloud-Native Testing: Use Azurite, Cosmos DB emulator, and testcontainers for integration tests, plus multi-stage Azure DevOps and GitHub Actions pipeline templates. - Use Case: A team building a FastAPI microservice on Azure uses this Skill to set up pytest with testcontainers for PostgreSQL, enforce 80% branch coverage in CI, and add Pact contract tests between services. ## Quick Start Ask the AI to help you set up a pytest test suite with coverage thresholds, Ruff linting, and an Azure DevOps pipeline for your Python project.
