Refactor high-complexity React components in Dify frontend. Use when `pnpm analyze-component...
npx skills add ngxtm/devkit --skill "python-development"
Install specific skill from multi-skill repository
# Description
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.
# SKILL.md
name: python-development
description: 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.
source: wshobson/agents
license: MIT
Python Development
Project Setup
Modern Python Project Structure
my-project/
βββ src/
β βββ my_project/
β βββ __init__.py
β βββ main.py
β βββ utils.py
βββ tests/
β βββ __init__.py
β βββ test_main.py
βββ pyproject.toml
βββ README.md
βββ .gitignore
pyproject.toml
[project]
name = "my-project"
version = "0.1.0"
requires-python = ">=3.12"
dependencies = [
"fastapi>=0.100.0",
"pydantic>=2.0",
]
[project.optional-dependencies]
dev = [
"pytest>=7.0",
"ruff>=0.1.0",
"mypy>=1.0",
]
[tool.ruff]
line-length = 88
select = ["E", "F", "I", "N", "W"]
[tool.mypy]
strict = true
Type Hints
from typing import TypeVar, Generic
from collections.abc import Sequence
T = TypeVar('T')
def process_items(items: Sequence[str]) -> list[str]:
return [item.upper() for item in items]
class Repository(Generic[T]):
def get(self, id: int) -> T | None: ...
def save(self, item: T) -> T: ...
Async Patterns
import asyncio
from collections.abc import AsyncIterator
async def fetch_all(urls: list[str]) -> list[dict]:
async with aiohttp.ClientSession() as session:
tasks = [fetch_one(session, url) for url in urls]
return await asyncio.gather(*tasks)
async def stream_data() -> AsyncIterator[bytes]:
async with aiofiles.open('large_file.txt', 'rb') as f:
async for chunk in f:
yield chunk
FastAPI Patterns
from fastapi import FastAPI, Depends, HTTPException
from pydantic import BaseModel
app = FastAPI()
class UserCreate(BaseModel):
email: str
name: str
class UserResponse(BaseModel):
id: int
email: str
name: str
@app.post("/users", response_model=UserResponse)
async def create_user(
user: UserCreate,
db: Database = Depends(get_db)
) -> UserResponse:
result = await db.users.create(user.model_dump())
return UserResponse(**result)
Testing
import pytest
from unittest.mock import AsyncMock, patch
@pytest.fixture
def mock_db():
db = AsyncMock()
db.users.get.return_value = {"id": 1, "name": "Test"}
return db
@pytest.mark.asyncio
async def test_get_user(mock_db):
result = await get_user(1, db=mock_db)
assert result["name"] == "Test"
mock_db.users.get.assert_called_once_with(1)
Best Practices
- Use
rufffor linting and formatting - Use
mypywith strict mode - Prefer
pathlib.Pathoveros.path - Use dataclasses or Pydantic for data structures
- Use
asynciofor I/O-bound operations - Use
contextlib.asynccontextmanagerfor async resources
# Supported AI Coding Agents
This skill is compatible with the SKILL.md standard and works with all major AI coding agents:
Learn more about the SKILL.md standard and how to use these skills with your preferred AI coding agent.