/ramped-test-backend

Primary LanguagePythonOtherNOASSERTION

Python FastAPI MongoDB Auth Project

This project is a Python-based test implementation that uses FastAPI, MongoDB. It's containerized with Docker Compose for easy deployment.

Description

This project employs the following technologies:

  1. FastAPI Backend:

    • FastAPI is a modern, high-performance web framework for building APIs with Python.
    • The backend handles HTTP requests, data processing, and communicates with MongoDB.

  2. MongoDB:

    • MongoDB is a NoSQL database that stores data in a flexible, JSON-like format.
    • It's used to persist and manage the application's data, supporting structured and unstructured data storage.

Software Requirements

To run this project, you need the following software:

  1. Operating System: Windows, Linux, macOS
  2. Docker and Docker Compose

How to Run this Project

  1. Clone the Git repository:

    git clone gitlink

  2. Create a .env file with the following content:

    ENV="dev"
DB_URL="mongodb://root:example@mongo:27017/"
DB_USERNAME=root
DB_PASSWORD=example
DB_NAME=test
BACKEND_URL="http://api:8080"
ACCESS_TOKEN_EXPIRES_IN=15
REFRESH_TOKEN_EXPIRES_IN=1440
JWT_ALGORITHM=RS256
CLIENT_ORIGIN=http://localhost:3000
JWT_PRIVATE_KEY=<Your JWT Private Key Here>
JWT_PUBLIC_KEY=<Your JWT Public Key Here>

    Replace <Your JWT Private Key Here> and <Your JWT Public Key Here> with your actual JWT keys.

  3. Run the Docker Compose file:

    docker-compose up -d --build

    This command will build and run Docker images for the services defined in the docker-compose.yaml file.

    • Access the Streamlit UI at: http://localhost:8501 on your local machine.

    • If you want to view the database, you can install MongoDB Compass and use the following connection string:

      mongodb://root:example@<Your local IPv4 address>:27017/

  4. Import Data into MongoDB:

    Download CSV file from https://docs.google.com/spreadsheets/d/1b0c1fbBuq4WNejtBi6IdPodOx74BG2-VwI1nGbyPHck/edit?usp=sharing.

    And import the csv into Jobs collection in MongoDb

That's it! You can now explore and customize this boilerplate code to add your own logic and features. Enjoy working with this project!