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Designs and implements pytest test suites for Python libraries with fixtures, parametrization, mocking, Hypothesis property-based testing, and CI configuration. Use when creating tests, improving coverage, setting up testing infrastructure, or implementing property-based testing.
Comprehensive Python testing with pytest framework, including test creation, fixtures, parameterized tests, and test execution. Use when Claude needs to work with Python testing for creating new tests, modifying existing tests, working with fixtures and test configuration, running tests with specific options, or debugging test failures.
Implement comprehensive testing strategies with pytest, fixtures, mocking, and test-driven development. Use when writing Python tests, setting up test suites, or implementing testing best practices.
Use when writing pytest tests, creating fixtures, mocking dependencies, or testing async code - provides patterns that verify actual behavior with proper fixtures and parametrization; prevents testing mocks instead of code (plugin:python@dot-claude)
Pytest test development for Python microservices. Use when writing unit tests, integration tests, fixtures, mocking external services, or setting up test infrastructure. Triggers on requests to create tests, debug failing tests, test organization, factory fixtures, parametrization, or testcontainers.
Strategy and patterns for designing and implementing End-to-End scenario tests using the Python SDK. Focuses on full-stack verification and SDK usability.
Python testing with pytest framework for unit, integration, and API tests. Use when: (1) Writing test cases for Python code, (2) Setting up pytest fixtures, (3) Testing async functions with pytest-asyncio, (4) Mocking dependencies, (5) Parameterizing tests, (6) Testing FastAPI/Flask endpoints, (7) Setting up test coverage, (8) Creating test factories with factory_boy, (9) Configuring CI/CD test pipelines.
Automatically generates comprehensive unit tests for Python, TypeScript, and JavaScript codebases. Analyzes function signatures, docstrings, and implementation patterns to produce tests covering happy paths, edge cases, error conditions, and boundary values. Supports pytest, Jest, and Vitest.
Python testing best practices with pytest. Covers unit, integration, async tests, mocking, fixtures. Triggers: "write tests", "add tests", "test coverage", "pytest", "tests"
Comprehensive pytest testing strategies with fixtures, mocking, and TDD patterns. WHEN: Writing pytest tests, creating fixtures, mocking with unittest.mock/pytest-mock, implementing TDD, setting up test configuration (conftest.py, pytest.ini). WHEN NOT: JavaScript tests (use Jest), PHP tests (use PHPUnit), running existing tests without modification.
Comprehensive BDD testing with Cucumber and Gherkin syntax. Use when writing feature files (.feature), step definitions, hooks, or implementing Behaviour-Driven Development. Covers Gherkin keywords (Feature, Scenario, Given/When/Then, Background, Scenario Outline, Rule), step definition patterns for Ruby/JavaScript/Java/Python, hooks (Before/After/BeforeAll/AfterAll), tags, data tables, doc strings, and best practices. Triggers on cucumber, gherkin, BDD, feature files, step definitions, acceptance testing, executable specifications.
Auto-generates Python step definition stubs from Gherkin feature files for BDD testing with Behave. Uses Behave's parser for accurate Gherkin parsing, intelligently infers parameter types, detects existing step definitions to suggest reuse, and supports data tables and doc strings. Creates ready-to-implement step definitions with proper type hints.
Standard procedure for running pytest tests in the airline-discount-ml project with proper Python environment configuration.
Use when writing pytest tests, creating fixtures, mocking dependencies, or testing async code - provides patterns that verify actual behavior with proper fixtures and parametrization; prevents testing mocks instead of code (plugin:dev-python@pproenca)
Run Python pytest suites and capture reproducible evidence (command, environment, output) into agent-output artifacts. Use for QA verification, debugging, and pre-release confidence.
Guide for writing pytest unit tests for the airline-discount-ml project. Use when asked to create, run, or debug Python unit tests for models, data access, or agents.
Backend testing with pytest including fixtures, mocking, async tests, and database testing. Use for FastAPI/Python test implementation.
Backend testing with pytest including fixtures, mocking, async tests, and database testing. Use for FastAPI/Python test implementation.
