A full-stack MERN (MongoDB, Express, React, Node.js) project designed to scrape user details from their LinkedIn profiles and display the structured data in a simple, interactive interface.
This application automates the process of collecting publicly available information from a LinkedIn profile URL, such as:
- Name
- Headline
- Work experience
- Education
- Skills
- Connections
It can be useful for recruiters, data aggregation platforms, or professionals aiming to analyze LinkedIn data.
OutFlo-Assignment/
├── backend/ # Node.js + Express API handling scraping logic
└── frontend/ # React.js TypeScript UI for entering LinkedIn URLs and displaying results
- 🔗 Input a LinkedIn profile URL
- 🧠 Scrape details using backend logic
- 🖥️ Clean and responsive frontend UI
- 📤 Seamless communication between frontend and backend
- 📂 Structured output of scraped data
- 🛡️ Basic error handling for invalid or blocked requests
Frontend:
- React.js
- TypeScript
- HTML5 + CSS3
Backend:
- Node.js
- Express.js
- Puppeteer or Cheerio for scraping
- Axios / Fetch for API calls
Database (optional for extension):
- MongoDB with Mongoose
git clone https://github.com/ayush123-bit/OutFlo-Assignment.git
cd OutFlo-Assignmentcd backend
npm install
npm startcd ../frontend
npm install
npm startFrontend runs on http://localhost:3000
Backend runs on http://localhost:5000
- Start both frontend and backend servers.
- Enter a valid LinkedIn profile URL in the input field.
- Click submit to fetch and view the scraped data.
- Extend the project by saving results to a database if required.
This tool scrapes data from LinkedIn, which may violate their terms of service. It is intended for educational purposes only. Please use responsibly and ensure legal and ethical compliance.
Ayush Rai
GitHub: @ayush123-bit
This project is open-source and available under the MIT License.