R507 - Computer Management (FastAPI)

R507 is a REST API developed with FastAPI to manage a fleet of computers. It allows you to create, read, update, and delete computers, as well as retrieve their resources (RAM, CPU, OS).

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🚀 Features

• Add a computer with its specifications (MAC, IP, OS, RAM, etc.)
• Update information for an existing computer
• Delete a computer
• List all computers
• Retrieve memory usage, CPU load, and OS information via SSH (if configured)
• API compatible with unit tests and in-memory cache

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🧩 Technologies Used

• Python 3.12
• FastAPI for the REST API
• SQLModel + SQLite for persistence
• Paramiko for SSH connections
• Uvicorn as the ASGI server
• Poetry for dependency management
• Docker for containerization

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📦 Docker Installation

Build the Docker image:

docker build -t R507 -f app3.Dockerfile .

Run the container:

docker run -d -p 8000:8000 R507

Access the API:

• Base URL: http://localhost:8000
• Interactive Swagger documentation: http://localhost:8000/docs
• ReDoc documentation: http://localhost:8000/redoc

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⚙️ Local Development (Poetry)

Install dependencies:

poetry install

Run the API locally:

poetry run uvicorn code.main:app --reload

Run unit tests:

poetry run pytest

or via bash:

alambic.sh           # export db
linter.sh            # show if code is well write
lunch.sh             # lunch docker and api
test_fonctionnels.sh # test fonctionnels of api
test_unitaires.sh    # test unitaires of api

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📝 Main Endpoints

Method	Endpoint	Description
GET	/	Welcome message
GET	/ordinateurs	List all computers
POST	/add_ordinateur	Add a computer
PUT	/edit_ordinateur	Update an existing computer
DELETE	/delete_ordinateur/{ip}	Delete a computer by IP
GET	/memory/{ip}	Get free and total memory
GET	/cpu_load/{ip}	Get CPU load
GET	/os_release/{ip}	Get OS information via SSH

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📂 Project Structure

r507/
├─ code/
│  ├─ main.py          # FastAPI application
│  ├─ models.py        # Pydantic and SQLModel models
│  ├─ db.py            # Database and session management
├─ tests/
│  ├─ unit/
│  │  ├─ test_main.py  # Unit tests for the API
├─ pyproject.toml      # Poetry dependencies
├─ poetry.lock
├─ README.md
└─ app3.Dockerfile     # Dockerfile for building the image

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⚠️ Notes

• The API uses an in-memory cache (app.state.ordinateurs) to speed up tests.
• Unit tests reset the cache on each startup.
• SSH connections are optional but required to retrieve certain system information.

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🛠️ Author

Malo – 126970037+Malaudos35@users.noreply.github.com https://github.com/Malaudos35/R507