FastAPI Device Management Project

This project is a FastAPI-based application for managing devices. It provides endpoints for creating, reading, updating, and deleting device information, as well as running tests inside a Docker container.

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Features

• CRUD Operations: Create, read, update, and delete device information via API endpoints.
• Validation: Input data is validated using Pydantic models to ensure data integrity.
• Database: Utilizes SQLite for storing device information.
• Testing: Includes pytest tests to ensure the functionality of the API endpoints.
• Linting: Uses pylint for code linting to maintain code quality.

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Project Structure

.
├── Dockerfile
├── README.md
├── COMMENTS.md
├── requirements.txt
├── .gitignore
└── app/
    ├── main.py
    ├── api/
    │   └── routers/
    │       └── devices.py
    ├── database/
    │   └── operations/
    │       └── devices.py
    ├── models/
    │   ├── coordinate.py
    │   └── device.py
    └── tests/
        └── unit/
            └── test_device_api.py
└── images/
    ├── jwt_authentication.svg
    └── oauth2.0_authentication.svg

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Installation

Clone the repository:

git clone https://github.com/tpemeja/Edgematrix-Private

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Usage - Docker Container

Getting the Docker Image

For the rest of the project, we will assume that you have built the image locally with the name myapp. To obtain the Docker image, you have two options:

Build the Image Locally:

You can create the Docker image by executing the following command in the directory containing your Dockerfile:

docker build -t myapp .

This command will build the Docker image with the tag myapp.

Download from Docker Hub:

Alternatively, you can directly download the pre-built image from Docker Hub using the following command:

docker pull tpemeja/edgematrix:main-latest

This command will pull the latest version of the image tagged as main-latest from the Docker Hub repository tpemeja/edgematrix.

Running the Docker Container

To run the Docker container, execute:

docker run -d -p <PORT>:80 -v <DATABASE_PATH>:/data myapp

• <PORT> is the port number to map the FastAPI server to. For example, 8000.
• <DATABASE_PATH> is the path to the directory where to store the SQLite database file. For example, /home/user/myproject/database.

Accessing the Swagger UI

Once the Docker container is running, you can access the Swagger UI by navigating to:

http://localhost:<PORT>/docs

Running Tests

To run tests using pytest inside a Docker container, execute:

docker run -v <DATABASE_PATH>:/data myapp pytest

Or to run it on an existing container

docker exec <CONTAINER_NAME|CONTAINER_ID> pytest

Running Linting

To perform linting using pylint, run:

docker run myapp pylint /code/app

Or to run it on an existing container

docker exec <CONTAINER_NAME|CONTAINER_ID> pylint /code/app

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Usage - Local Testing

Installing Requirements

First, install the required dependencies by running:

pip install -r requirements.txt

Creating Database Directory

Ensure you have created a directory for the SQLite database. You can create it using the following command:

mkdir /data

The database will be stored in /data/devices.db by default unless the value is modified using the variable DATABASE_PATH in the app/database/startup.py file.

Running Tests Locally

To run tests locally using pytest, execute:

pytest

Running Linting Locally

To perform linting using pylint locally, run:

pylint app/

Starting the FastAPI Server Locally

To start the FastAPI server locally, execute:

uvicorn app.main:app --host 0.0.0.0 --port <PORT>

Accessing the Swagger UI

Once the FastAPI server is running locally, you can access the Swagger UI by navigating to:

http://localhost:<PORT>/docs