GitHub
testing
Best practices for writing Python tests - use when creating or improving test coverage
Résultats pour « Python »
Skills correspondant au nom, à la description ou à l’auteur GitHub.
Catégories: data ai testing
Explorer
GitHub
generate-step-stubs
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...
GitHub
race-condition-audit
Systematic identification of race conditions, concurrency bugs, and thread-safety issues across codebases. Use when asked to find race conditions, audit concurrent code, debug non-deterministic behavior, review...
GitHub
unit-test-generator
Automatically generates comprehensive unit tests for Python, TypeScript, and JavaScript codebases. Analyzes function signatures, docstrings, and implementation patterns to produce tests covering happy paths, ed...
GitHub
pytest
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)...
GitHub
pytest
Python testing with pytest framework. This skill should be used when user asks to write tests, create test files, run tests, fix failing tests, add test coverage, set up fixtures, mock dependencies, or do any t...
GitHub
pytest
Comprehensive Python testing skill using pytest framework. Use when writing, running, or debugging Python tests, creating fixtures, parametrizing tests, mocking dependencies, measuring coverage, or any pytest-r...
GitHub
pytest
Comprehensive pytest testing skill for Python projects with specialized FastAPI support. Use when: (1) User wants to generate test files for existing code, (2) User asks about pytest patterns, best practices, f...
GitHub
test-modules
Test script creation and execution for Python modules, focusing on functional testing, unit testing, and integration testing. Use when creating test scripts for software modules, running tests to verify functio...
GitHub
code-testing
Generate and run unit and integration tests using pytest (Python) or Jest (JavaScript) with fixtures, mocks, and async support. Use for test-driven development, code review validation, coverage verification, an...
GitHub
python-best-practices
Type hints, dataclasses, async patterns, testing with pytest, and modern Python tooling
GitHub
sdk-e2e-testing
Strategy and patterns for designing and implementing End-to-End scenario tests using the Python SDK. Focuses on full-stack verification and SDK usability.
GitHub
pytest-backend-patterns
Backend testing with pytest including fixtures, mocking, async tests, and database testing. Use for FastAPI/Python test implementation.
GitHub
pytest-backend-patterns
Backend testing with pytest including fixtures, mocking, async tests, and database testing. Use for FastAPI/Python test implementation.
GitHub
pytests
Create comprehensive Python test suites with pytest. Supports unit, integration, e2e, and user flow tests. Dual-mode testing for FastAPI (direct code + live API). Uses functional style (no test classes). File n...
GitHub
unit-test-generator
Generate pytest unit tests for Python functions and classes with fixtures, parametrization, and edge cases. This skill should be used when creating test coverage for modules, especially during refactoring to en...
GitHub
temporal-python-testing
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 o...
GitHub
python-testing-patterns
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.
GitHub
python-testing
Generate pytest tests for Python modules with parametrization, shared fixtures in conftest.py, and minimal mocking. Use when creating unit tests, test suites, or improving test coverage. Follows 1-1 file corres...
GitHub
test-generator
Universal test generation skill that works with any language or framework. Detects project conventions, generates unit/integration/API/validation tests, and evolves through learning. Use when user asks to "writ...
GitHub
pytest-patterns
Advanced Python testing strategies with Pytest, covering fixtures, matrix testing with parametrization, and async test architecture. Triggers: pytest, fixtures, parametrize, pytest-asyncio, matrix-testing, yiel...
GitHub
cli-testing-patterns
CLI testing strategies and patterns for Node.js (Jest) and Python (pytest, Click.testing.CliRunner). Use when writing tests for CLI tools, testing command execution, validating exit codes, testing output, imple...
GitHub
test-data-generation
Provides patterns and examples for generating test data using factory libraries. Use this skill when you need to create realistic and maintainable test data for your application. It covers factory patterns (e.g...
GitHub
test-coverage-analyst
Guides on analyzing and improving test coverage for Python (pytest-cov) and JavaScript (c8) projects. Use when a user asks to set up test coverage, generate coverage reports, understand why coverage is low, or...
Catégories populaires
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.