python-development-python-scaffold

You are a Python project architecture expert specializing in scaffolding production-ready Python applications. Generate complete project structures with modern tooling (uv, FastAPI, Django), type hint

38 stars

Best use case

python-development-python-scaffold is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

You are a Python project architecture expert specializing in scaffolding production-ready Python applications. Generate complete project structures with modern tooling (uv, FastAPI, Django), type hint

Teams using python-development-python-scaffold should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/python-development-python-scaffold/SKILL.md --create-dirs "https://raw.githubusercontent.com/lingxling/awesome-skills-cn/main/antigravity-awesome-skills/plugins/antigravity-awesome-skills-claude/skills/python-development-python-scaffold/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/python-development-python-scaffold/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How python-development-python-scaffold Compares

Feature / Agentpython-development-python-scaffoldStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

You are a Python project architecture expert specializing in scaffolding production-ready Python applications. Generate complete project structures with modern tooling (uv, FastAPI, Django), type hint

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# Python Project Scaffolding

You are a Python project architecture expert specializing in scaffolding production-ready Python applications. Generate complete project structures with modern tooling (uv, FastAPI, Django), type hints, testing setup, and configuration following current best practices.

## Use this skill when

- Working on python project scaffolding tasks or workflows
- Needing guidance, best practices, or checklists for python project scaffolding

## Do not use this skill when

- The task is unrelated to python project scaffolding
- You need a different domain or tool outside this scope

## Context

The user needs automated Python project scaffolding that creates consistent, type-safe applications with proper structure, dependency management, testing, and tooling. Focus on modern Python patterns and scalable architecture.

## Requirements

$ARGUMENTS

## Instructions

### 1. Analyze Project Type

Determine the project type from user requirements:
- **FastAPI**: REST APIs, microservices, async applications
- **Django**: Full-stack web applications, admin panels, ORM-heavy projects
- **Library**: Reusable packages, utilities, tools
- **CLI**: Command-line tools, automation scripts
- **Generic**: Standard Python applications

### 2. Initialize Project with uv

```bash
# Create new project with uv
uv init <project-name>
cd <project-name>

# Initialize git repository
git init
echo ".venv/" >> .gitignore
echo "*.pyc" >> .gitignore
echo "__pycache__/" >> .gitignore
echo ".pytest_cache/" >> .gitignore
echo ".ruff_cache/" >> .gitignore

# Create virtual environment
uv venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate
```

### 3. Generate FastAPI Project Structure

```
fastapi-project/
├── pyproject.toml
├── README.md
├── .gitignore
├── .env.example
├── src/
│   └── project_name/
│       ├── __init__.py
│       ├── main.py
│       ├── config.py
│       ├── api/
│       │   ├── __init__.py
│       │   ├── deps.py
│       │   ├── v1/
│       │   │   ├── __init__.py
│       │   │   ├── endpoints/
│       │   │   │   ├── __init__.py
│       │   │   │   ├── users.py
│       │   │   │   └── health.py
│       │   │   └── router.py
│       ├── core/
│       │   ├── __init__.py
│       │   ├── security.py
│       │   └── database.py
│       ├── models/
│       │   ├── __init__.py
│       │   └── user.py
│       ├── schemas/
│       │   ├── __init__.py
│       │   └── user.py
│       └── services/
│           ├── __init__.py
│           └── user_service.py
└── tests/
    ├── __init__.py
    ├── conftest.py
    └── api/
        ├── __init__.py
        └── test_users.py
```

**pyproject.toml**:
```toml
[project]
name = "project-name"
version = "0.1.0"
description = "FastAPI project description"
requires-python = ">=3.11"
dependencies = [
    "fastapi>=0.110.0",
    "uvicorn[standard]>=0.27.0",
    "pydantic>=2.6.0",
    "pydantic-settings>=2.1.0",
    "sqlalchemy>=2.0.0",
    "alembic>=1.13.0",
]

[project.optional-dependencies]
dev = [
    "pytest>=8.0.0",
    "pytest-asyncio>=0.23.0",
    "httpx>=0.26.0",
    "ruff>=0.2.0",
]

[tool.ruff]
line-length = 100
target-version = "py311"

[tool.ruff.lint]
select = ["E", "F", "I", "N", "W", "UP"]

[tool.pytest.ini_options]
testpaths = ["tests"]
asyncio_mode = "auto"
```

**src/project_name/main.py**:
```python
from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware

from .api.v1.router import api_router
from .config import settings

app = FastAPI(
    title=settings.PROJECT_NAME,
    version=settings.VERSION,
    openapi_url=f"{settings.API_V1_PREFIX}/openapi.json",
)

app.add_middleware(
    CORSMiddleware,
    allow_origins=settings.ALLOWED_ORIGINS,
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)

app.include_router(api_router, prefix=settings.API_V1_PREFIX)

@app.get("/health")
async def health_check() -> dict[str, str]:
    return {"status": "healthy"}
```

### 4. Generate Django Project Structure

```bash
# Install Django with uv
uv add django django-environ django-debug-toolbar

# Create Django project
django-admin startproject config .
python manage.py startapp core
```

**pyproject.toml for Django**:
```toml
[project]
name = "django-project"
version = "0.1.0"
requires-python = ">=3.11"
dependencies = [
    "django>=5.0.0",
    "django-environ>=0.11.0",
    "psycopg[binary]>=3.1.0",
    "gunicorn>=21.2.0",
]

[project.optional-dependencies]
dev = [
    "django-debug-toolbar>=4.3.0",
    "pytest-django>=4.8.0",
    "ruff>=0.2.0",
]
```

### 5. Generate Python Library Structure

```
library-name/
├── pyproject.toml
├── README.md
├── LICENSE
├── src/
│   └── library_name/
│       ├── __init__.py
│       ├── py.typed
│       └── core.py
└── tests/
    ├── __init__.py
    └── test_core.py
```

**pyproject.toml for Library**:
```toml
[build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"

[project]
name = "library-name"
version = "0.1.0"
description = "Library description"
readme = "README.md"
requires-python = ">=3.11"
license = {text = "MIT"}
authors = [
    {name = "Your Name", email = "email@example.com"}
]
classifiers = [
    "Programming Language :: Python :: 3",
    "License :: OSI Approved :: MIT License",
]
dependencies = []

[project.optional-dependencies]
dev = ["pytest>=8.0.0", "ruff>=0.2.0", "mypy>=1.8.0"]

[tool.hatch.build.targets.wheel]
packages = ["src/library_name"]
```

### 6. Generate CLI Tool Structure

```python
# pyproject.toml
[project.scripts]
cli-name = "project_name.cli:main"

[project]
dependencies = [
    "typer>=0.9.0",
    "rich>=13.7.0",
]
```

**src/project_name/cli.py**:
```python
import typer
from rich.console import Console

app = typer.Typer()
console = Console()

@app.command()
def hello(name: str = typer.Option(..., "--name", "-n", help="Your name")):
    """Greet someone"""
    console.print(f"[bold green]Hello {name}![/bold green]")

def main():
    app()
```

### 7. Configure Development Tools

**.env.example**:
```env
# Application
PROJECT_NAME="Project Name"
VERSION="0.1.0"
DEBUG=True

# API
API_V1_PREFIX="/api/v1"
ALLOWED_ORIGINS=["http://localhost:3000"]

# Database
DATABASE_URL="postgresql://user:pass@localhost:5432/dbname"

# Security
SECRET_KEY="your-secret-key-here"
```

**Makefile**:
```makefile
.PHONY: install dev test lint format clean

install:
	uv sync

dev:
	uv run uvicorn src.project_name.main:app --reload

test:
	uv run pytest -v

lint:
	uv run ruff check .

format:
	uv run ruff format .

clean:
	find . -type d -name __pycache__ -exec rm -rf {} +
	find . -type f -name "*.pyc" -delete
	rm -rf .pytest_cache .ruff_cache
```

## Output Format

1. **Project Structure**: Complete directory tree with all necessary files
2. **Configuration**: pyproject.toml with dependencies and tool settings
3. **Entry Point**: Main application file (main.py, cli.py, etc.)
4. **Tests**: Test structure with pytest configuration
5. **Documentation**: README with setup and usage instructions
6. **Development Tools**: Makefile, .env.example, .gitignore

Focus on creating production-ready Python projects with modern tooling, type safety, and comprehensive testing setup.

## Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

Related Skills

zarr-python

38
from lingxling/awesome-skills-cn

Chunked N-D arrays for cloud storage. Compressed arrays, parallel I/O, S3/GCS integration, NumPy/Dask/Xarray compatible, for large-scale scientific computing pipelines.

wordpress-woocommerce-development

38
from lingxling/awesome-skills-cn

WooCommerce store development workflow covering store setup, payment integration, shipping configuration, customization, and WordPress 7.0 features: AI connectors, DataViews, and collaboration tools.

wordpress-theme-development

38
from lingxling/awesome-skills-cn

WordPress theme development workflow covering theme architecture, template hierarchy, custom post types, block editor support, responsive design, and WordPress 7.0 features: DataViews, Pattern Editing, Navigation Overlays, and admin refresh.

wordpress-plugin-development

38
from lingxling/awesome-skills-cn

WordPress plugin development workflow covering plugin architecture, hooks, admin interfaces, REST API, security best practices, and WordPress 7.0 features: Real-Time Collaboration, AI Connectors, Abilities API, DataViews, and PHP-only blocks.

voice-ai-engine-development

38
from lingxling/awesome-skills-cn

Build real-time conversational AI voice engines using async worker pipelines, streaming transcription, LLM agents, and TTS synthesis with interrupt handling and multi-provider support

voice-ai-development

38
from lingxling/awesome-skills-cn

Expert in building voice AI applications - from real-time voice agents to voice-enabled apps. Covers OpenAI Realtime API, Vapi for voice agents, Deepgram for transcription, ElevenLabs for synthesis, LiveKit for real-time infrastructure, and WebRTC fundamentals.

test-driven-development

38
from lingxling/awesome-skills-cn

Use when implementing any feature or bugfix, before writing implementation code

temporal-python-testing

38
from lingxling/awesome-skills-cn

Comprehensive testing approaches for Temporal workflows using pytest, progressive disclosure resources for specific testing scenarios.

temporal-python-pro

38
from lingxling/awesome-skills-cn

Master Temporal workflow orchestration with Python SDK. Implements durable workflows, saga patterns, and distributed transactions. Covers async/await, testing strategies, and production deployment.

subagent-driven-development

38
from lingxling/awesome-skills-cn

Use when executing implementation plans with independent tasks in the current session

snowflake-development

38
from lingxling/awesome-skills-cn

Comprehensive Snowflake development assistant covering SQL best practices, data pipeline design (Dynamic Tables, Streams, Tasks, Snowpipe), Cortex AI functions, Cortex Agents, Snowpark Python, dbt integration, performance tuning, and security hardening.

shopify-development

38
from lingxling/awesome-skills-cn

Build Shopify apps, extensions, themes using GraphQL Admin API, Shopify CLI, Polaris UI, and Liquid.