Nearby Users

A minimal full-stack app to fetch, store, and visualize random user data with geolocation-based nearest user discovery.

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Overview

This app:

• Fetches random users from RandomUser API
• Stores their info and location in a SQLite database
• Finds the K-nearest users to a given user (by latitude/longitude)
• Visualizes results using a Streamlit dashboard with an interactive Folium map

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Tech Stack

• Backend: FastAPI, SQLAlchemy, SQLite
• Frontend: Streamlit, Folium (streamlit-folium)
• Other: Pydantic, Requests

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Installation

1. Clone the repository

git clone https://github.com/Nachiket-2024/nearby_users.git
cd nearby-users

2. Set up the environment

Install dependencies with pip:

pip install -r requirements.txt

Or use Conda:

conda env create -f environment.yml
conda activate nearby-users

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Run the App

1. Start the FastAPI backend

cd backend
uvicorn main:app --reload

2. Run the Streamlit frontend

cd frontend
streamlit run app.py

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API Endpoints

Method	Route	Description
POST	/fetch-users/	Fetch and store N random users
GET	/random-user/	Return a random user from the database
GET	/nearest-users/	Return K nearest users to a given user

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Deploying the App

You can deploy this app using Docker on any platform that supports containerized apps.

Railway

1. Make your GitHub repository public (or provide Railway access).
2. Connect your GitHub repository to Railway.
3. Choose the Dockerfile option — Railway will automatically build and deploy the app.
4. Configure environment variables (like database URL or others) if needed, via the Railway dashboard.

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Vercel

Vercel is mainly optimized for frontend apps (Next.js, React, etc.), not backend APIs like FastAPI.

For full-stack deployment, use Railway, Render, or Fly.io, or you can host manually on a VPS.

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Render

Render is a cloud platform where you can deploy Dockerized applications like this one. It also supports auto-deployment via GitHub.

1. Connect your GitHub repository to Render.
2. Choose the Docker option to deploy.
3. Render will automatically detect and deploy the application using the provided Dockerfile.
4. Set up any necessary environment variables in the Render dashboard.

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