This project is a simple Python application demonstrating data masking while fetching data from a MongoDB instance. It is built with Flask and connected to MongoDB using Docker containers. The data is fetched from MongoDB and masked before being returned via a Flask API.
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Install Docker: Make sure you have Docker installed on your system. You can download it from Docker's official website.
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Clone the Repository: Clone this repository to your local machine.
git clone https://github.com/your-username/flask-mongodb-data-masking.git
cd flask-mongodb-data-masking- Ensure the Required Files Exist:
docker-compose.yml: Defines services for MongoDB and the Flask app.app.py: The Flask API that connects to MongoDB and masks sensitive data.config/init-mongo.js: MongoDB initialization script (for setting up initial data).src/: Directory where the Flask application and other code reside.
The project uses Docker Compose to create and manage the containers for both the MongoDB database and the Flask application.
Steps to Run the Project:
- Build and Run Containers: Ensure Docker is running, then use the following command to build and start the services:
docker compose up --build- Access the Flask Application: Once the containers are up, access the Flask app via:
http://localhost:5001/usersThe default port is 5001, but you can change it in docker-compose.yml if needed.
Check MongoDB: MongoDB will be accessible at localhost:27017. The MongoDB root username is root, and the password is example (set in docker-compose.yml).
An initial MongoDB setup script, config/init-mongo.js, is used to populate the database with some default data.
The Flask API exposes the following endpoint:
GET /users: Fetch all users from MongoDB. Sensitive information (like ssn) will be masked before being returned.
- Python: Backend logic using Flask.
- MongoDB: A NoSQL database for storing user data.
- Docker: Containerization for both the Flask app and MongoDB instance.
- PyMongo: MongoDB driver for Python.