Python code review and best practices validation. Comprehensive analysis including type hints, testing, linting, and package management.
Scanned 6/6/2026
Install via CLI
openskills install excatt/superclaude-plusplus---
name: python-best-practices
description: Python code review and best practices validation. Comprehensive analysis including type hints, testing, linting, and package management.
---
# Python Best Practices Skill
## Purpose
Comprehensively analyze Python code quality, type safety, test coverage, and linting compliance.
## When to Use
- **Auto-execute** when Python code review requested
- When analyzing `.py` files
- When reviewing FastAPI, Django, Flask projects
- When inspecting package dependencies
## Analysis Categories
### 1. Type Hints (25%)
**Check Items**:
- Function parameter type hints
- Return type annotations
- Complex types (Generic, Union, Optional)
- TypedDict, Protocol usage
```python
# ❌ Bad
def get_user(id):
return db.query(id)
# ✅ Good
def get_user(id: int) -> User | None:
return db.query(id)
```
**Verification Tool**: `mypy --strict`
### 2. Code Quality (25%)
**Check Items**:
- PEP 8 style compliance
- Function/class complexity
- Import organization
- Docstring presence
```python
# ❌ Bad
def f(x,y,z): return x+y+z
# ✅ Good
def calculate_sum(a: int, b: int, c: int) -> int:
"""Calculate the sum of three integers."""
return a + b + c
```
**Verification Tool**: `ruff check`, `ruff format --check`
### 3. Testing (20%)
**Check Items**:
- Test files exist (`tests/`, `*_test.py`)
- Test coverage (≥80% recommended)
- Fixture usage
- Mocking patterns
```python
# ✅ Good test structure
def test_get_user_returns_user(db_session: Session):
user = create_user(db_session, name="test")
result = get_user(user.id)
assert result.name == "test"
def test_get_user_returns_none_for_invalid_id():
result = get_user(999999)
assert result is None
```
**Verification Tool**: `pytest --cov`
### 4. Security (15%)
**Check Items**:
- SQL Injection prevention
- Hardcoded secrets
- Unsafe deserialization
- Input validation
```python
# ❌ Bad
query = f"SELECT * FROM users WHERE id = {user_id}"
# ✅ Good
query = "SELECT * FROM users WHERE id = :id"
result = db.execute(query, {"id": user_id})
```
**Verification Tool**: `bandit`
### 5. Dependencies (15%)
**Required Rule**: **Use uv** (pip, poetry, pipenv prohibited)
**Check Items**:
- `pyproject.toml` (PEP 621 standard) exists
- `uv.lock` exists and committed
- Version ranges properly specified (`^`, `~`)
- Development dependency groups separated
```toml
# ✅ Good pyproject.toml (PEP 621 / uv)
[project]
name = "my-project"
version = "0.1.0"
requires-python = ">=3.11"
dependencies = []
[dependency-groups]
dev = [
"pytest>=8.0",
"mypy>=1.8",
"ruff>=0.1",
]
```
```toml
# ❌ Bad - Using requirements.txt or Poetry format
[tool.poetry]
dependencies = {python = "^3.11"}
# ❌ Bad - Using poetry.lock
```
**Verification Tool**: `uv lock --check`, `uv sync --frozen`
**Docker Pattern**:
```dockerfile
COPY --from=ghcr.io/astral-sh/uv:latest /uv /uvx /bin/
COPY pyproject.toml uv.lock ./
RUN uv sync --frozen --no-dev
```
---
## Output Format
### High Quality (≥90%)
```
📋 Python Best Practices Check:
✅ Type Hints: 95% coverage (mypy strict pass)
✅ Code Quality: A (ruff 0 errors)
✅ Testing: 87% coverage (42 tests)
✅ Security: No issues (bandit clean)
✅ Dependencies: All pinned, no vulnerabilities
📊 Score: 0.94 (94%)
✅ Production Ready
```
### Needs Improvement (70-89%)
```
📋 Python Best Practices Check:
✅ Type Hints: 78% coverage
⚠️ Code Quality: B (12 ruff warnings)
✅ Testing: 72% coverage
⚠️ Security: 2 low-severity issues
✅ Dependencies: OK
📊 Score: 0.76 (76%)
⚠️ Review Recommended
💡 Improvements Needed:
1. src/utils.py:45 - Missing type hints
2. src/api.py:120 - High complexity (refactor recommended)
3. src/db.py:67 - Caution with SQL string formatting
```
### Poor Quality (<70%)
```
📋 Python Best Practices Check:
❌ Type Hints: 32% coverage
❌ Code Quality: D (47 errors)
❌ Testing: 15% coverage (3 tests)
⚠️ Security: 5 issues
❌ Dependencies: Unpinned versions
📊 Score: 0.42 (42%)
❌ Not Ready for Review
🚨 Critical Issues:
1. Insufficient type safety - mypy cannot run
2. Test coverage critically low
3. requirements.txt versions not pinned
```
---
## Verification Commands
```bash
# Run in uv environment
# Type checking
uv run mypy --strict src/
# Linting & formatting
uv run ruff check src/
uv run ruff format --check src/
# Testing
uv run pytest --cov=src --cov-report=term-missing
# Security
uv run bandit -r src/
# Dependencies
uv lock --check # Check lock file sync
uv sync --frozen # Verify install from lock
uv pip list --outdated # List updatable packages
# Virtual environment management
uv venv # Show/create environment info
uv sync # Install dependencies
uv lock --upgrade # Upgrade dependencies
```
---
## Framework-Specific Checks
### FastAPI
```python
# ✅ Good patterns
from fastapi import Depends, HTTPException, status
from pydantic import BaseModel
class UserCreate(BaseModel):
name: str
email: EmailStr
@app.post("/users", response_model=UserResponse)
async def create_user(
user: UserCreate,
db: Session = Depends(get_db)
) -> UserResponse:
...
```
**Additional Checks**:
- Pydantic model usage
- Dependency injection pattern
- Async endpoints
- OpenAPI documentation
### Django
```python
# ✅ Good patterns
from django.db import models
from django.core.validators import MinLengthValidator
class User(models.Model):
name = models.CharField(max_length=100, validators=[MinLengthValidator(2)])
email = models.EmailField(unique=True)
class Meta:
indexes = [models.Index(fields=['email'])]
```
**Additional Checks**:
- Model indexes
- Migration state
- Security middleware
- CSRF protection
---
## Integration with Other Skills
```
/confidence-check → Verify Python project architecture
│
▼
/python-best-practices → Analyze code quality
│
▼
/verify → Verify build/tests
│
▼
/learn → Save patterns
```
---
## Commands
| Command | Description |
|---------|-------------|
| `/python-best-practices` | Full analysis |
| `/python-best-practices --quick` | Type/lint only |
| `/python-best-practices --security` | Security focus |
| `/python-best-practices --deps` | Dependencies focus |
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