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README.md

Design LinkedIn - Professional Social Network

Codebase Stats

Metric Value
Total SLOC 11,095
Source Files 62
.ts 5,736
.tsx 3,013
.md 1,845
.sql 249
.json 124

Overview

A simplified LinkedIn-like platform demonstrating professional social graphs, connection recommendations, feed ranking, and job matching algorithms. This educational project focuses on building a professional networking system with sophisticated recommendation engines.

Key Features

1. Professional Profiles

  • Work history and education
  • Skills and endorsements
  • Profile completeness scoring

2. Connection Graph

  • First, second, third-degree connections
  • Connection requests and acceptance
  • Mutual connections display
  • "People You May Know" (PYMK) recommendations

3. Feed & Content

  • Professional posts with rich content
  • Engagement (likes, comments)
  • Feed ranking algorithm based on engagement, recency, and relationship

4. Job Matching

  • Job listings with requirements and salary ranges
  • Candidate-job matching score based on skills, experience, location
  • Application tracking
  • Recommended jobs for users

5. Company Pages

  • Company profiles with industry and size
  • Job postings per company

Tech Stack

  • Frontend: TypeScript + Vite + React 19 + TanStack Router + Zustand + Tailwind CSS
  • Backend: Node.js + Express + TypeScript
  • Database: PostgreSQL
  • Cache: Redis
  • Search: Elasticsearch
  • Containerization: Docker Compose

Quick Start

Prerequisites

  • Node.js 18+
  • Docker and Docker Compose
  • npm or yarn

1. Start Infrastructure

# Start PostgreSQL, Redis, and Elasticsearch
docker-compose up -d

# Wait for services to be healthy (about 30 seconds)
docker-compose ps

2. Setup Backend

cd backend

# Install dependencies
npm install

# Seed the database with test data
npm run seed

# Start the development server
npm run dev

The backend will be available at http://localhost:3001

3. Setup Frontend

cd frontend

# Install dependencies
npm install

# Start the development server
npm run dev

The frontend will be available at http://localhost:5173

Demo Accounts

All demo accounts use the password: password123

Email Role Description
alice@example.com Admin Senior Software Engineer at TechCorp
bob@example.com User Product Manager at DataFlow
carol@example.com User Data Scientist at CloudScale
david@example.com User Engineering Lead at TechCorp
emma@example.com User Frontend Developer at StartupXYZ
frank@example.com User Backend Engineer at CloudScale
grace@example.com User DevOps Engineer at DataFlow
henry@example.com User Solutions Architect at GlobalBank

API Endpoints

Authentication

  • POST /api/auth/register - Register new user
  • POST /api/auth/login - Login
  • POST /api/auth/logout - Logout
  • GET /api/auth/me - Get current user

Users/Profiles

  • GET /api/users/:id - Get user profile with experience, education, skills
  • PATCH /api/users/me - Update own profile
  • GET /api/users?q=query - Search users
  • POST /api/users/me/experiences - Add experience
  • POST /api/users/me/education - Add education
  • POST /api/users/me/skills - Add skill
  • POST /api/users/:id/skills/:skillId/endorse - Endorse a skill

Connections

  • GET /api/connections - Get my connections
  • GET /api/connections/requests - Get pending requests
  • POST /api/connections/request - Send connection request
  • POST /api/connections/requests/:id/accept - Accept request
  • POST /api/connections/requests/:id/reject - Reject request
  • DELETE /api/connections/:userId - Remove connection
  • GET /api/connections/degree/:userId - Get connection degree
  • GET /api/connections/mutual/:userId - Get mutual connections
  • GET /api/connections/second-degree - Get 2nd degree connections
  • GET /api/connections/pymk - Get People You May Know recommendations

Feed

  • GET /api/feed - Get feed (posts from connections)
  • POST /api/feed - Create post
  • GET /api/feed/:id - Get single post
  • DELETE /api/feed/:id - Delete post
  • POST /api/feed/:id/like - Like post
  • DELETE /api/feed/:id/like - Unlike post
  • GET /api/feed/:id/comments - Get comments
  • POST /api/feed/:id/comments - Add comment
  • GET /api/feed/user/:userId - Get user's posts

Jobs

  • GET /api/jobs - List/search jobs
  • GET /api/jobs/recommended - Get recommended jobs
  • GET /api/jobs/:id - Get job details
  • POST /api/jobs/:id/apply - Apply for job
  • GET /api/jobs/my/applications - Get my applications
  • GET /api/jobs/companies - List companies
  • POST /api/jobs - Create job (admin only)
  • POST /api/jobs/companies - Create company (admin only)

Architecture

See architecture.md for detailed system design documentation.

Development Notes

Running Multiple Backend Instances

# Terminal 1
npm run dev:server1  # Port 3001

# Terminal 2
npm run dev:server2  # Port 3002

# Terminal 3
npm run dev:server3  # Port 3003

Environment Variables

Create a .env file in the backend directory:

# Database
DB_HOST=localhost
DB_PORT=5432
DB_NAME=linkedin
DB_USER=linkedin
DB_PASSWORD=linkedin_password

# Redis
REDIS_HOST=localhost
REDIS_PORT=6379

# Elasticsearch
ELASTICSEARCH_URL=http://localhost:9200

# Session
SESSION_SECRET=your-secret-key

# Frontend URL (for CORS)
FRONTEND_URL=http://localhost:5173

Key Technical Challenges

  1. Connection Degrees: Efficiently computing 2nd and 3rd degree connections using recursive CTEs
  2. People You May Know: Multi-factor scoring based on mutual connections, shared companies, schools, skills, and location
  3. Feed Ranking: Balancing recency, relevance (connection degree), and engagement signals
  4. Job Matching: Multi-factor scoring based on skill match, experience level, location, and company connections

Development Insights

See claude.md for development insights and design decisions.

References & Inspiration