
python-project
Modern Python project architecture guide for 2025. Use when creating Python projects (APIs, CLI, data pipelines). Covers uv, Ruff, Pydantic, FastAPI, and async patterns.
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/majiayu000/spellbook --skill python-project- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads python-project automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
Python Project Architecture
Core Principles
- Type hints everywhere — Pydantic for runtime, mypy for static
- uv for everything — Package management, virtualenv, Python version
- Ruff only — Replace Flake8 + Black + isort with single tool
- src layout — All code under
src/directory - pyproject.toml only — No setup.py, no requirements.txt
- Async all the way — Once async, stay async through call chain
- No backwards compatibility — Delete, don't deprecate. Change directly
- LiteLLM for LLM APIs — Use LiteLLM proxy for all LLM integrations
No Backwards Compatibility
Delete unused code. Change directly. No compatibility layers.
# ❌ BAD: Deprecated decorator kept around
import warnings
def old_function():
warnings.warn("Use new_function instead", DeprecationWarning)
return new_function()
# ❌ BAD: Alias for renamed functions
new_name = old_name # "for backwards compatibility"
# ❌ BAD: Unused parameters with underscore
def process(_legacy_param, data):
...
# ❌ BAD: Version checking for old behavior
if version < "2.0":
# old behavior
...
# ✅ GOOD: Just delete and update all usages
def new_function():
...
# Then: Find & replace all old_function → new_function
# ✅ GOOD: Remove unused parameters entirely
def process(data):
...
LiteLLM for LLM APIs
Use LiteLLM proxy. Don't call provider APIs directly.
# src/myapp/llm.py
from openai import AsyncOpenAI
from myapp.config import settings
# Connect to LiteLLM proxy using OpenAI SDK
client = AsyncOpenAI(
base_url=settings.litellm_url, # "http://localhost:4000"
api_key=settings.litellm_api_key,
)
async def complete(prompt: str, model: str = "gpt-4o") -> str:
"""Call any LLM through LiteLLM proxy."""
response = await client.chat.completions.create(
model=model, # "gpt-4o", "claude-3-opus", "gemini-pro", etc.
messages=[{"role": "user", "content": prompt}],
)
return response.choices[0].message.content or ""
Quick Start
1. Initialize Project
# Install uv (if not installed)
curl -LsSf https://astral.sh/uv/install.sh | sh
# Create new project
uv init myapp
cd myapp
# Set Python version
echo "3.12" > .python-version
# Add dependencies
uv add fastapi uvicorn pydantic sqlalchemy httpx
uv add --dev pytest pytest-asyncio ruff mypy
2. Apply Tech Stack
| Layer | Recommendation |
|---|---|
| Package Manager | uv |
| Linting + Format | Ruff |
| Type Checking | mypy |
| Validation | Pydantic v2 |
| Web Framework | FastAPI |
| Database | SQLAlchemy 2.0 + asyncpg |
| HTTP Client | httpx |
| Testing | pytest + pytest-asyncio |
| Logging | structlog |
Version Strategy
Always use latest. Never pin in templates.
[project]
dependencies = [
"fastapi", # uv resolves to latest
"pydantic",
"sqlalchemy",
]
uv addfetches latest compatible versionsuv.lockensures reproducible buildsuv syncinstalls exact locked versions
3. Use Standard Structure (src layout)
myapp/
├── pyproject.toml # Single config file
├── uv.lock # Lock file (commit this)
├── .python-version # Python version for uv
├── src/
│ └── myapp/
│ ├── __init__.py
│ ├── __main__.py # Entry point
│ ├── main.py # FastAPI app
│ ├── config.py # Pydantic Settings
│ ├── models/ # Pydantic models
│ │ ├── __init__.py
│ │ └── user.py
│ ├── services/ # Business logic
│ │ ├── __init__.py
│ │ └── user.py
│ ├── repositories/ # Data access
│ │ ├── __init__.py
│ │ └── user.py
│ ├── api/ # HTTP layer
│ │ ├── __init__.py
│ │ ├── deps.py # Dependencies
│ │ └── routes/
│ │ ├── __init__.py
│ │ └── user.py
│ └── core/ # Shared utilities
│ ├── __init__.py
│ ├── exceptions.py
│ └── logging.py
├── tests/
│ ├── __init__.py
│ ├── conftest.py # Fixtures
│ └── test_user.py
└── Makefile
Architecture Layers
main.py — FastAPI Application
# src/myapp/main.py
from contextlib import asynccontextmanager
from fastapi import FastAPI
from myapp.api.routes import router
from myapp.config import settings
from myapp.core.logging import setup_logging
from myapp.db import engine
@asynccontextmanager
async def lifespan(app: FastAPI):
# Startup
setup_logging()
yield
# Shutdown
await engine.dispose()
app = FastAPI(
title=settings.app_name,
lifespan=lifespan,
)
app.include_router(router, prefix="/api/v1")
@app.get("/health")
async def health():
return {"status": "ok"}
config.py — Pydantic Settings
# src/myapp/config.py
from pydantic_settings import BaseSettings, SettingsConfigDict
class Settings(BaseSettings):
model_config = SettingsConfigDict(
env_file=".env",
env_file_encoding="utf-8",
)
app_name: str = "myapp"
debug: bool = False
# Database
database_url: str = "postgresql+asyncpg://localhost/myapp"
# LiteLLM
litellm_url: str = "http://localhost:4000"
litellm_api_key: str = ""
settings = Settings()
models/ — Pydantic Models
# src/myapp/models/user.py
from datetime import datetime
from uuid import UUID
from pydantic import BaseModel, EmailStr, Field
class UserBase(BaseModel):
email: EmailStr
name: str = Field(min_length=2, max_length=100)
class UserCreate(UserBase):
pass
class UserUpdate(BaseModel):
email: EmailStr | None = None
name: str | None = Field(default=None, min_length=2, max_length=100)
class User(UserBase):
id: UUID
created_at: datetime
updated_at: datetime
model_config = {"from_attributes": True}
services/ — Business Logic
# src/myapp/services/user.py
from uuid import UUID
from myapp.core.exceptions import NotFoundError, ConflictError
from myapp.models.user import User, UserCreate, UserUpdate
from myapp.repositories.user import UserRepository
class UserService:
def __init__(self, repo: UserRepository):
self.repo = repo
async def get(self, id: UUID) -> User:
user = await self.repo.get(id)
if not user:
raise NotFoundError("user", str(id))
return user
async def create(self, data: UserCreate) -> User:
existing = await self.repo.get_by_email(data.email)
if existing:
raise ConflictError("email already exists")
return await self.repo.create(data)
async def update(self, id: UUID, data: UserUpdate) -> User:
user = await self.get(id)
return await self.repo.update(user, data)
async def delete(self, id: UUID) -> None:
user = await self.get(id)
await self.repo.delete(user)
api/routes/ — HTTP Handlers
# src/myapp/api/routes/user.py
from uuid import UUID
from fastapi import APIRouter, Depends, status
from myapp.api.deps import get_user_service
from myapp.models.user import User, UserCreate, UserUpdate
from myapp.services.user import UserService
router = APIRouter(prefix="/users", tags=["users"])
@router.get("/{id}", response_model=User)
async def get_user(
id: UUID,
service: UserService = Depends(get_user_service),
):
return await service.get(id)
@router.post("", response_model=User, status_code=status.HTTP_201_CREATED)
async def create_user(
data: UserCreate,
service: UserService = Depends(get_user_service),
):
return await service.create(data)
@router.patch("/{id}", response_model=User)
async def update_user(
id: UUID,
data: UserUpdate,
service: UserService = Depends(get_user_service),
):
return await service.update(id, data)
@router.delete("/{id}", status_code=status.HTTP_204_NO_CONTENT)
async def delete_user(
id: UUID,
service: UserService = Depends(get_user_service),
):
await service.delete(id)
core/exceptions.py — Custom Exceptions
# src/myapp/core/exceptions.py
from fastapi import HTTPException, status
class AppError(Exception):
"""Base application error."""
def __init__(self, message: str, code: str):
self.message = message
self.code = code
super().__init__(message)
class NotFoundError(AppError):
def __init__(self, resource: str, id: str):
super().__init__(f"{resource} not found: {id}", "NOT_FOUND")
class ConflictError(AppError):
def __init__(self, message: str):
super().__init__(message, "CONFLICT")
class ValidationError(AppError):
def __init__(self, message: str):
super().__init__(message, "VALIDATION_ERROR")
# FastAPI exception handler
def app_error_to_http(error: AppError) -> HTTPException:
status_map = {
"NOT_FOUND": status.HTTP_404_NOT_FOUND,
"CONFLICT": status.HTTP_409_CONFLICT,
"VALIDATION_ERROR": status.HTTP_400_BAD_REQUEST,
}
return HTTPException(
status_code=status_map.get(error.code, status.HTTP_500_INTERNAL_SERVER_ERROR),
detail={"message": error.message, "code": error.code},
)
pyproject.toml
[project]
name = "myapp"
version = "0.1.0"
description = "My application"
requires-python = ">=3.12"
dependencies = [
"fastapi",
"uvicorn[standard]",
"pydantic",
"pydantic-settings",
"sqlalchemy[asyncio]",
"asyncpg",
"httpx",
"structlog",
]
[tool.uv]
dev-dependencies = [
"pytest",
"pytest-asyncio",
"pytest-cov",
"ruff",
"mypy",
]
[tool.ruff]
line-length = 100
target-version = "py312"
[tool.ruff.lint]
select = [
"E", # pycodestyle errors
"F", # pyflakes
"I", # isort
"UP", # pyupgrade
"B", # flake8-bugbear
"SIM", # flake8-simplify
]
[tool.ruff.lint.isort]
known-first-party = ["myapp"]
[tool.mypy]
strict = true
python_version = "3.12"
[tool.pytest.ini_options]
asyncio_mode = "auto"
testpaths = ["tests"]
Extended Reference
Detailed material starting at ## Testing has been moved to reference/extended.md to keep this skill concise. Load that reference when the task requires the moved examples, command catalogs, checklists, platform details, or implementation templates.
FAQ
What does the python-project skill do?
Modern Python project architecture guide for 2025. Use when creating Python projects (APIs, CLI, data pipelines). Covers uv, Ruff, Pydantic, FastAPI, and async patterns.
How do I install python-project?
Run npx skills add https://github.com/majiayu000/spellbook --skill python-project in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/python-project/ (personal) or .claude/skills/python-project/ (project).
Which AI agents can use python-project?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is python-project safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains python-project?
It is published by majiayu000 in majiayu000/spellbook. It has 80 recorded installs.
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