python-testing
Python testing strategies using pytest, TDD methodology, fixtures, mocking, parametrization, and coverage requirements.
- License 许可
- MIT
- 最近更新
- 2026-11-02
- Stars
- ★ 0
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- 0
01 前言 Front Matter
- name
- python-testing
- origin
- ECC
- description
- Python testing strategies using pytest, TDD methodology, fixtures, mocking, parametrization, and coverage requirements.
03 SKILL.md 正文
Python Testing Patterns
Comprehensive testing strategies for Python applications using pytest, TDD methodology, and best practices.
When to Activate
- Writing new Python code (follow TDD: red, green, refactor)
- Designing test suites for Python projects
- Reviewing Python test coverage
- Setting up testing infrastructure
Core Testing Philosophy
Test-Driven Development (TDD)
Always follow the TDD cycle:
- RED: Write a failing test for the desired behavior
- GREEN: Write minimal code to make the test pass
- REFACTOR: Improve code while keeping tests green
# Step 1: Write failing test (RED)
def test_add_numbers():
result = add(2, 3)
assert result == 5
# Step 2: Write minimal implementation (GREEN)
def add(a, b):
return a + b
# Step 3: Refactor if needed (REFACTOR)
Coverage Requirements
- Target: 80%+ code coverage
- Critical paths: 100% coverage required
- Use
pytest --covto measure coverage
pytest --cov=mypackage --cov-report=term-missing --cov-report=html
pytest Fundamentals
Basic Test Structure
import pytest
def test_addition():
"""Test basic addition."""
assert 2 + 2 == 4
def test_string_uppercase():
"""Test string uppercasing."""
text = "hello"
assert text.upper() == "HELLO"
def test_list_append():
"""Test list append."""
items = [1, 2, 3]
items.append(4)
assert 4 in items
assert len(items) == 4
Assertions
### Equality
### Inequality
### Truthiness
04 同仓库更多 Skills
clarify-requirements
Resolve genuine pre-execution ambiguity by scanning repo context, generating 1-6 grounded options, and asking 1-3 focused questions via AskUserQuestion. NOT for mid-task use (injection risk); NOT when the goal is already unambiguous; use to disambiguate vague prompts before any file edits.
openmm-md
Run FREE, open-source, Windows-native GPU molecular dynamics via the openmm-md MCP (OpenMM + CUDA on the local NVIDIA GPU). Use for protein / protein-ligand MD when you want a free stack or are on Windows without a Schrodinger license. Covers the full workflow (prepare, solvate, minimize, equilibrate, production, analyze, mmgbsa) AND an honest decision guide vs Schrodinger Desmond, including how to run Desmond legitimately on Linux or a cloud GPU with a real license. This is a deliberately LESSER free alternative and does NOT replace the schrodinger MCP tools. Do NOT use it to pick a free tool when a validated FEP+, WaterMap, IFD-MD, or Prime MM-GBSA result is actually required.
visual-review
Take screenshots of web pages and UI using Playwright for visual review and iteration
status
Diagnostic status report — shows metaswarm installation state, project setup, and potential issues
start
Use when starting work on any task, when the user mentions metaswarm, or when the user wants to begin tracked development work
setup
Interactive project setup — detects your project, configures metaswarm, writes project-local files