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Found 29 Skills
Python testing strategies using pytest, TDD methodology, fixtures, mocking, parametrization, and coverage requirements.
Expert in Python testing with pytest and test-driven development
Python testing with pytest, coverage, fixtures, parametrization, and mocking. Covers test organization, conftest.py, markers, async testing, and TDD workflows. Use when user mentions pytest, unit tests, test coverage, fixtures, mocking, or writing Python tests.
Design comprehensive Python test suites including unit, integration, and E2E tests. Use when establishing testing patterns for new or existing Python applications.
Consult this skill for Python testing implementation and patterns. Use when writing unit tests, setting up test suites, implementing TDD, configuring pytest, creating fixtures, async testing, writing integration tests, mocking dependencies, parameterizing tests, setting up CI/CD testing. Do not use when evaluating test quality - use pensive:test-review instead. DO NOT use when: infrastructure test config - use leyline:pytest-config.
Use when writing or reviewing tests for Python behavior, contracts, async lifecycles, or reliability paths. Also use when tests are flaky, coupled to implementation details, missing regression coverage, slow to run, or when unclear what tests a change needs.
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.
Test Temporal workflows with pytest, time-skipping, and mocking strategies. Covers unit testing, integration testing, replay testing, and local development setup. Use when implementing Temporal workflow tests or debugging test failures.
Consult this skill for async Python patterns and concurrency. Use when building async APIs, concurrent systems, I/O-bound applications, implementing rate limiting, async context managers. Do not use when CPU-bound optimization - use python-performance instead. DO NOT use when: testing async code - use python-testing async module.
Modern Python development with Python 3.12+, Django, FastAPI, async patterns, and production best practices. Use for Python projects, APIs, data processing, or automation scripts.
Scaffold new modules and components for pplx-sdk following the layered architecture and established code patterns.
Write and evaluate effective Python tests using pytest. Use when writing tests, reviewing test code, debugging test failures, or improving test coverage. Covers test design, fixtures, parameterization, mocking, and async testing.