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name: python description: Write idiomatic Python with advanced features. Use for Python development, refactoring, or optimization.

Python Development

Write clean, performant, idiomatic Python code.

When to Use

• Writing Python code
• Refactoring Python projects
• Performance optimization
• Setting up Python tooling
• Code review for Python

Python Best Practices

Code Style

• Follow PEP 8
• Use type hints (Python 3.9+)
• Prefer f-strings over .format()
• Use pathlib over os.path

Modern Features

Copy# Type hints
def process(data: list[dict]) -> dict[str, int]:
    ...

# Dataclasses
from dataclasses import dataclass

@dataclass
class User:
    name: str
    email: str
    active: bool = True

# Context managers
from contextlib import contextmanager

@contextmanager
def timer():
    start = time.time()
    yield
    print(f"Elapsed: {time.time() - start:.2f}s")

# Generators for memory efficiency
def read_large_file(path):
    with open(path) as f:
        yield from f

Error Handling

Copy# Custom exceptions
class ValidationError(Exception):
    def __init__(self, field: str, message: str):
        self.field = field
        self.message = message
        super().__init__(f"{field}: {message}")

# Proper exception chaining
try:
    process()
except ValueError as e:
    raise ProcessingError("Failed to process") from e

Project Structure

Copyproject/
├── src/
│   └── package/
│       ├── __init__.py
│       └── module.py
├── tests/
│   └── test_module.py
├── pyproject.toml
└── README.md

Tooling Setup

Copy# pyproject.toml
[tool.ruff]
line-length = 88
select = ["E", "F", "I", "UP"]

[tool.mypy]
strict = true

[tool.pytest.ini_options]
testpaths = ["tests"]

Testing Pattern

Copyimport pytest

@pytest.fixture
def sample_data():
    return {"key": "value"}

def test_process(sample_data):
    result = process(sample_data)
    assert result["status"] == "success"

Examples

Input: "Refactor this Python code" Action: Apply PEP 8, add type hints, simplify logic, improve error handling

Input: "Make this faster" Action: Profile, identify bottlenecks, use generators/caching, verify improvement