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python-fastapi-todo-app

Creates a simple Todo REST API with FastAPI, SQLite, and basic CRUD operations. Use when the user asks to create a todo app, task manager API, or a simple Python REST API with create/read/update/delete endpoints.

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价格未确认★ 57 GitHub Stars目录更新于 · 2026年10月2日agent-skill

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Skill: Python FastAPI Todo App

Creates a simple Todo API with FastAPI, SQLite, and basic CRUD operations.

When to use

When the user asks to create a todo app, task manager API, or simple REST API with Python.

Steps

First, make sure Python 3.11+ is installed. On macOS use brew install python@3.11, on Linux use apt-get install python3.11.

Create the project directory and initialize a virtual environment:

mkdir -p todo-api/app
cd todo-api
python3 -m venv venv
source venv/bin/activate

Install the dependencies:

pip install fastapi uvicorn sqlalchemy

Create the file app/database.py:

from sqlalchemy import create_engine
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import sessionmaker

DATABASE_URL = "sqlite:///./todos.db"

engine = create_engine(DATABASE_URL, connect_args={"check_same_thread": False})
SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine)
Base = declarative_base()

Create the file app/models.py:

from sqlalchemy import Column, Integer, String, Boolean
from .database import Base

class Todo(Base):
    __tablename__ = "todos"

    id = Column(Integer, primary_key=True, index=True)
    title = Column(String, index=True)
    description = Column(String, default="")
    completed = Column(Boolean, default=False)

Create app/main.py with the FastAPI app, including these endpoints:

GET /todos — list all todos
POST /todos — create a new todo
PUT /todos/{id} — update a todo
DELETE /todos/{id} — delete a todo

The app should read $API_HOST and $API_PORT from the environment for the server bind address.

Add the project conventions to QWEN.md at the root (Qwen Code reads QWEN.md, and also AGENTS.md, for persistent project context).

Test the API:

curl http://localhost:8000/todos

curl -X POST http://localhost:8000/todos -H "Content-Type: application/json" -d '{"title": "Buy milk", "completed": false}'

For each endpoint, run a quick smoke test to make sure it returns 200.

Notes

Keep it simple, no auth needed
Use SQLite so there's no external database dependency
Add a .env with API_HOST=0.0.0.0 and API_PORT=8000

查看来源 ↗

文件元数据

name: python-fastapi-todo-app
description: Creates a simple Todo REST API with FastAPI, SQLite, and basic CRUD operations. Use when the user asks to create a todo app, task manager API, or a simple Python REST API with create/read/update/delete endpoints.
allowedTools:
  - write_file
  - edit
  - read_file
  - run_shell_command

查看原始文本

---
name: python-fastapi-todo-app
description: Creates a simple Todo REST API with FastAPI, SQLite, and basic CRUD operations. Use when the user asks to create a todo app, task manager API, or a simple Python REST API with create/read/update/delete endpoints.
allowedTools:
  - write_file
  - edit
  - read_file
  - run_shell_command
---

# Skill: Python FastAPI Todo App

> Creates a simple Todo API with FastAPI, SQLite, and basic CRUD operations.

## When to use

When the user asks to create a todo app, task manager API, or simple REST API with Python.

## Steps

First, make sure Python 3.11+ is installed. On macOS use `brew install python@3.11`, on Linux use `apt-get install python3.11`.

Create the project directory and initialize a virtual environment:

```bash
mkdir -p todo-api/app
cd todo-api
python3 -m venv venv
source venv/bin/activate
```

Install the dependencies:

```bash
pip install fastapi uvicorn sqlalchemy
```

Create the file `app/database.py`:

```python
from sqlalchemy import create_engine
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import sessionmaker

DATABASE_URL = "sqlite:///./todos.db"

engine = create_engine(DATABASE_URL, connect_args={"check_same_thread": False})
SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine)
Base = declarative_base()
```

Create the file `app/models.py`:

```python
from sqlalchemy import Column, Integer, String, Boolean
from .database import Base

class Todo(Base):
    __tablename__ = "todos"

    id = Column(Integer, primary_key=True, index=True)
    title = Column(String, index=True)
    description = Column(String, default="")
    completed = Column(Boolean, default=False)
```

Create `app/main.py` with the FastAPI app, including these endpoints:

- `GET /todos` — list all todos
- `POST /todos` — create a new todo
- `PUT /todos/{id}` — update a todo
- `DELETE /todos/{id}` — delete a todo

The app should read `$API_HOST` and `$API_PORT` from the environment for the server bind address.

Add the project conventions to `QWEN.md` at the root (Qwen Code reads `QWEN.md`, and also `AGENTS.md`, for persistent project context).

Test the API:

```bash
curl http://localhost:8000/todos
```

```bash
curl -X POST http://localhost:8000/todos -H "Content-Type: application/json" -d '{"title": "Buy milk", "completed": false}'
```

For each endpoint, run a quick smoke test to make sure it returns 200.

## Notes

- Keep it simple, no auth needed
- Use SQLite so there's no external database dependency
- Add a `.env` with `API_HOST=0.0.0.0` and `API_PORT=8000`

查看并核实来源

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许可证: MIT
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安装前审查: 避免自动安装

许可证: MIT

Dependency or permission surface needs review
Permission surface may require sandboxing
The skill does not include a step to start the FastAPI server (e.g., uvicorn command) before testing, which may lead to confusion.
The instruction to add project conventions to QWEN.md is vague; it does not specify what conventions to include.
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
GitHub adoption: 57 GitHub stars
Stars/forks activity: 57 stars, 8 forks; issue activity unavailable in current metadata
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution

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2先让 Agent 提出计划，批准环境配置和费用，再进行隔离的小规模测试。
3检查输出和变更文件，只报告实际执行结果，并保留来源版本以便复现。

请在来源中核实依赖、API 密钥及第三方费用。公开仓库不代表所有服务免费。

来源与使用须知

已收录

仓库元数据和审核信号仅供参考。受欢迎、已发现来源、成功运行是不同的事实。

来源仓库: andersonamaral2/Claude-Code-to-Deep-Agents-Skills-Converter
许可证: MIT
版本: Unknown
最近 GitHub 推送: 2026年9月22日
目录更新于: 2026年10月2日
技能指令路径: examples/qwen-output/python-fastapi-todo-app/SKILL.md @ 9f454d91ea79

版本来自目录元数据，使用前请核实来源发布记录。

质量

65/100

有潜力

信任

53/100

Do not auto-install

审计

72/100

需审查

打开完整审计查看评估报告

Dependency or permission surface needs review
Permission surface may require sandboxing
The skill does not include a step to start the FastAPI server (e.g., uvicorn command) before testing, which may lead to confusion.
The instruction to add project conventions to QWEN.md is vague; it does not specify what conventions to include.
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
GitHub adoption: 57 GitHub stars
Stars/forks activity: 57 stars, 8 forks; issue activity unavailable in current metadata
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution

Verified installs: —
结果: —

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创作者: andersonamaral2
来源: andersonamaral2/Claude-Code-to-Deep-Agents-Skills-Converter
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告诉我们这个 Skill 是否对你的 Agent 工作流有帮助。汇总反馈会持续改善排序。

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