Python Based Backend

A Python-based REST API backend that demonstrates modern web development practices. It's a paragraph management system with user authentication, text processing, and search functionality. The core features include JWT-based authentication, paragraph submission, automatic word indexing using background tasks, and frequency-based search."

High-Level Architecture

Client (Browser/Postman) 
    ↓ HTTP Requests
FastAPI Application
    ↓ Database Operations
SQLAlchemy ORM
    ↓ Data Storage
SQLite Database
    ↓ Background Processing
FastAPI BackgroundTasks (Word Indexing)

Features

• User Authentication: JWT-based auth with register/login/logout
• Paragraph Management: Submit multiple paragraphs in a single request
• Word Indexing: Automatic background indexing with word frequency tracking
• Smart Search: Find top 10 paragraphs ranked by word frequency
• Containerized: Docker setup with lightweight images
• Interactive Docs: Auto-generated Swagger UI documentation

Tech Stack

• Backend: FastAPI (Python 3.11+)
• Database: SQLAlchemy ORM with SQLite
• Authentication: JWT tokens with bcrypt password hashing
• Background Tasks: FastAPI BackgroundTasks for word indexing
• Testing: pytest with comprehensive test coverage
• Deployment: Docker, Render-ready configuration

Quick Start

Prerequisites

• Python 3.11+
• pip (or Docker for containerized setup)

Installation

1. Clone the repository:

   git clone https://github.com/Suk022/Python-based-backend.git
   cd backend-assignment

2. Install dependencies:

   pip install -r requirements.txt

3. Run the application:

   uvicorn app.main:app --reload --port 8000

4. Access the API:

   • API Documentation: http://localhost:8000/docs
   • Health Check: http://localhost:8000/health
   • Root Endpoint: http://localhost:8000/

API Endpoints

Authentication

• POST /auth/register - Register new user
• POST /auth/login - User login (returns JWT token)
• POST /auth/logout - Logout and invalidate refresh token

Paragraphs

• POST /paragraphs - Submit multiple paragraphs
• GET /paragraphs - List user paragraphs (paginated)
• GET /paragraphs/search?word=<word> - Search paragraphs by word frequency

Documentation

• GET /docs - Interactive Swagger UI
• GET / - API information
• GET /health - Health check endpoint

Testing Guide

Below are the instructions for testing APIs using different methods:

1. Start the application:

   # Using Python directly
   uvicorn app.main:app --reload --port 8000
   
   # Using Docker
   docker-compose -f docker-compose.dev.yml up --build

2. Open Swagger UI: http://localhost:8000/docs

3. Test User Registration:

   • Find POST /auth/register
   • Click "Try it out"
   • Enter test data:

     {
       "email": "test@example.com",
       "password": "password123"
     }

   • Click "Execute"
   • Expected: Status 200, user_id returned

4. Test User Login:

   • Find POST /auth/login
   • Use same credentials as registration
   • Click "Execute"
   • Copy the access_token from response

5. Authorize for Protected Endpoints:

   • Click "Authorize" button (top right)
   • Enter: YOUR_ACCESS_TOKEN
   • Click "Authorize"

6. Test Paragraph Submission:

   • Find POST /paragraphs/
   • Enter test paragraphs:

     {
       "paragraphs": [
         "Python is a great programming language. Python is easy to learn.",
         "I love coding in Python. Python has many libraries.",
         "JavaScript is popular, but Python is my favorite programming language."
       ]
     }

   • Click "Execute"
   • Expected: Status 200, success message

7. Test Word Search:

   • Find GET /paragraphs/search
   • Enter search word: python
   • Click "Execute"
   • Expected: Paragraphs ranked by word frequency

8. Test Paragraph Listing:

   • Find GET /paragraphs/
   • Click "Execute"
   • Expected: Paginated list of your paragraphs

Method 2: Using Postman

1. Import Collection: Create requests for each endpoint
2. Set Environment Variable: {{token}} for authorization
3. Test Flow: Register - Login - Save token - Test protected endpoints

Method 3: Automated Testing

# Register user
curl -X POST "http://localhost:8000/auth/register" \
  -H "Content-Type: application/json" \
  -d '{"email": "user@example.com", "password": "password123"}'

# Login
curl -X POST "http://localhost:8000/auth/login" \
  -H "Content-Type: application/json" \
  -d '{"email": "user@example.com", "password": "password123"}'

# Submit paragraphs (use token from login)
curl -X POST "http://localhost:8000/paragraphs/" \
  -H "Authorization: Bearer <your-token>" \
  -H "Content-Type: application/json" \
  -d '{"paragraphs": ["I love apple pie. Apple is sweet.", "The apple tree grows apples."]}'

# Search for word
curl -X GET "http://localhost:8000/paragraphs/search?word=apple" \
  -H "Authorization: Bearer <your-token>"

Testing

# Run tests (uses SQLite automatically)
make test

# Or directly with pytest
USE_SQLITE=true python -m pytest tests/ -v

Make Commands

make build      # Build Docker images
make up         # Start production mode (all services)
make dev-up     # Start development mode (web only)
make test       # Run tests
make clean      # Clean Docker resources
make clean-all  # Clean everything including images
make dev-local  # Run locally without Docker

Architecture

Models

• User - User accounts with email/password
• Paragraph - User-submitted text content
• WordCount - Global word frequency per user
• ParagraphWordCount - Word frequency per paragraph
• RefreshToken - JWT refresh token storage

Indexing Process

1. User submits paragraphs via POST /paragraphs
2. Paragraphs are stored immediately
3. Background task indexes words:
   • Tokenizes text (lowercase, remove punctuation)
   • Updates ParagraphWordCount (per paragraph)
   • Updates WordCount (global user totals)
   • Uses SQL upserts for concurrency safety

Search Algorithm

1. Query ParagraphWordCount for user + word
2. Join with Paragraph for content
3. Order by word count descending
4. Return top 10 results

Database Indexes

Optimized for fast search:

• (user_id, word) - Word lookup
• (user_id, word, count) - Frequency sorting
• (paragraph_id) - Paragraph joins

Live Demo

The project is deployed on Render and can be accessed via https://python-based-backend.onrender.com/. Test the APIs directly through the link.