Flask REST API

A RESTful API built with Flask, MongoDB, and Docker, designed for learning and demonstration purposes. The API provides operations for users and is ready for deployment in both local and production environments.

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Features

• Flask REST API with modular structure
• MongoDB integration (local for dev, Atlas for production)
• Docker & Docker Compose for containerized development
• Unit tests with pytest
• Environment-based configuration (development vs production)
• Hosted on Heroku

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Technologies

• Python 3.12
• Flask + Flask-RESTful
• MongoDB + MongoEngine
• Docker & Docker Compose
• Pytest
• Heroku (production)

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Installation & Setup

Prerequisites

• Docker & Docker Compose
• Python 3.12 (for local development without Docker)

Clone the repository

git clone https://github.com/Andre-Franco1/restapi-flask.git
cd restapi-flask

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Local Development

Using Docker Compose

make compose

• This will start the Flask API and a local MongoDB instance.
• API will be available at http://localhost:5000.

Without Docker

1. Create virtual environment:

python3 -m venv .venv
source .venv/bin/activate

2. Install dependencies:

pip install -r requirements.txt

3. Run the application:

python3 wsgi.py

• API will run on http://127.0.0.1:5000.

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Configuration

The app uses environment-based configurations:

• DevConfig → local MongoDB
• ProdConfig → MongoDB Atlas

Set the following environment variables for production in the Heroku application settings 'Config Vars' after the MongoDB Atlas cluster is up and runnig:

• MONGODB_HOST
• MONGODB_USER
• MONGODB_PASSWORD
• MONGODB_DB

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API Endpoints

Method	Endpoint	Description
GET	/users	Get all users
POST	/user	Create a new user
GET	/user/<cpf>	Get user by CPF

Example request (POST /user):

{
  "first_name": "John",
  "last_name": "Doe",
  "cpf": "635.631.290-45",
  "email": "johndoe@mail.com",
  "birth_date": "2001-01-01"
}

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Running Tests

make test

• Runs pytest and flake8 for code linting and unit tests.

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Deployment

Heroku (Docker)

make heroku

• Logs into Heroku container registry, pushes the Docker image, and releases the web process.

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Notes

• The API is containerized using Docker; local MongoDB is used for development, and MongoDB Atlas is used in production.
• The application uses an app factory pattern, making it easier to scale and test.