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.
Installation
Details
Usage
After installing, this skill will be available to your AI coding assistant.
Verify installation:
skills listSkill Instructions
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/
├── src/
│ └── my_project/
│ ├── __init__.py
│ ├── main.py
│ └── utils.py
├── tests/
│ ├── __init__.py
│ └── test_main.py
├── pyproject.toml
├── README.md
└── .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
More by skillcreatorai
View allCreate, update, and manage Jira issues from natural language. Use when the user wants to log bugs, create tickets, update issue status, or manage their Jira backlog.
Clarify requirements before implementing. Do not use automatically, only when invoked explicitly.
Comprehensive document creation, editing, and analysis with support for tracked changes, comments, formatting preservation, and text extraction. When Claude needs to work with professional documents (.docx files) for creating new documents, modifying content, working with tracked changes, or adding comments.
Backend API design, database architecture, microservices patterns, and test-driven development. Use for designing APIs, database schemas, or backend system architecture.