Eve Playground

A simple backend application using Eve, Pydantic, and MongoDB in a Docker container. The project is designed to demonstrate a scalable and modular structure for building APIs with Eve while utilizing Pydantic for data validation and environment variables for configuration.

---

Table of Contents

• Project Overview
• Tech Stack
• Requirements
• Setup
  • 1. Clone the Repository
  • 2. Install Dependencies
  • 3. Run MongoDB in Docker
  • 4. Set Up Environment Variables
  • 5. Run the Application
• Usage
• API Endpoints
• Project Structure
• Contributing

---

Project Overview

This project is a simple demonstration of building a scalable REST API backend using Eve, a REST API framework built on top of Flask. The app utilizes Pydantic for input validation, MongoDB for data storage (hosted inside a Docker container), and environment variables loaded via .env for configuration.

The goal is to show how to structure an Eve API application in a modular way, including good practices for project organization, data validation, and use of environment variables for configurations.

---

Tech Stack

• Eve: REST API framework built on Flask.
• Pydantic: Data validation and settings management.
• MongoDB: Database for storing user data.
• Docker: Used for running MongoDB in a containerized environment.
• Python: The main programming language used.
• Flask: Web framework used by Eve.
• Python-dotenv: For managing environment variables via .env file.

---

Requirements

• Python 3.9 or higher
• Docker (for MongoDB container)
• pip (Python package installer)

---

Setup

1. Clone the Repository

Clone the repository to your local machine:

git clone https://github.com/gustavovalle23/eve-playground.git
cd eve-playground

2. Install Dependencies

Create a virtual environment and install dependencies:

python3 -m venv venv
source venv/bin/activate  # On Windows use `venv\Scripts\activate`
pip install -r requirements.txt

3. Run MongoDB in Docker

Ensure Docker is installed and running on your machine. Then, use Docker to run MongoDB:

docker-compose up -d

This will pull the official MongoDB image and run it in a container.

4. Set Up Environment Variables

Create a .env file in the project root and define the following variables:

MONGO_URI=mongodb://localhost:27017
MONGO_DBNAME=mydatabase
DEBUG=True

This ensures that your app is connected to the local MongoDB instance and the app runs in debug mode.

5. Run the Application

Now you can run the application using:

python -m app.main

This will start the Eve API on http://127.0.0.1:5000.

---

Usage

Once the application is running, you can interact with the API via HTTP requests.

Create a User

curl -X POST "http://127.0.0.1:5000/users" \
-H "Content-Type: application/json" \
-d '{"username": "john_doe", "email": "[email protected]", "age": 30}'

Get All Users

curl -X GET "http://127.0.0.1:5000/users"

---

API Endpoints

• POST /users - Create a new user.
• GET /users - Retrieve all users.
• GET /users/<user_id> - Retrieve a single user by ID.
• PATCH /users/<user_id> - Update a user.
• DELETE /users/<user_id> - Delete a user.

---

Project Structure

The folder structure of the project is designed to be scalable and modular:

backend/
│── app/
│   ├── models/            # Database models
│   │   ├── user.py
│   │   ├── __init__.py
│   ├── schemas/           # Pydantic schemas for validation
│   │   ├── user.py
│   │   ├── __init__.py
│   ├── settings.py        # Eve settings and MongoDB configuration
│   ├── main.py            # Eve app instance
│   ├── __init__.py
│── .env                   # Environment variables
│── docker-compose.yml      # MongoDB in Docker
│── requirements.txt        # Project dependencies
│── README.md               # Documentation

---

Contributing

Contributions are welcome! Feel free to open an issue or submit a pull request. If you want to improve the project or have ideas for new features, let me know.

Steps to contribute:

1. Fork the repository
2. Create a new branch (git checkout -b feature-name)
3. Commit your changes (git commit -am 'Add new feature')
4. Push to your branch (git push origin feature-name)
5. Create a new Pull Request