Google Custom Search with NodeJS

Goo

Google provides a custom search API by which you can use the power of google search engine in your own application. The base URL for the REST version of custom search API is:

https://www.googleapis.com/customsearch/v1

Before moving on to integration part, we need two things.

  1. API KEY
  2. Search Engine ID

The API KEY can be created by tapping the GET A KEY button and creating a new project at the following link:

https://developers.google.com/custom-search/json-api/v1/introduction

The next step is the search engine ID. You need to create an instance of a search engine at:

https://cse.google.com/

  1. Here you need to add a new instance, give the name of the engine, any website and just create it for now.
  2. Now go to its control panel and in the basic options > Sites to search, you have the option to search the entire web (with emphasis on some websites if you want to include some) or search only for some websites (should be included in list, patterns can also be included).
  3. Configure it as per your choice and in Details section you will find the search engine ID by clicking on the Search Engine ID button.

Now you are ready to integrate. The code to integrate the API using Express and Node JS is:

var express = require(‘express’);

var path = require(‘path’);

var app = express();

var request = require(‘request’);

// The main search function

var google_web_search = function(search, callback) {

    console.log(‘Searching the web for: ‘, search);

    var options = {

        method: ‘GET’,

        url: ‘https://www.googleapis.com/customsearch/v1’,

        qs: {

            q: search,

            key: ‘<API_KEY>’,

            cx: ‘<SEARCH_ENGINE_ID>’,

        }

    };

    request(options, function (error, response, body) {

        callback(error, body);

    });

};

app.get(‘/’, function (req, res) {

   google_web_search(‘<YOUR_SEARCH_QUERY>’, function(error, body) {

     if (!error) {

        res.send(body);

     } else {

        throw new Error(error);

     }

   });

});

app.listen(3000, function () {

    console.log(‘Example app listening on port 3000!’);

});

If you want more results, then you can use pagination by adding two query params:

  1. num: specifies the number of results to return in the response
  2. start: specifies the number of results to skip

gle provides a custom search API by which you can use the power of google search engine in your own application. The base URL for the REST version of custom search API is:

https://www.googleapis.com/customsearch/v1

Before moving on to integration part, we need two things.
1. API KEY
2. Search Engine ID

The API KEY can be created by tapping the GET A KEY button and creating a new project at the following link:

https://developers.google.com/custom-search/json-api/v1/introduction

The next step is the search engine ID. You need to create an instance of a search engine at:

https://cse.google.com/

1. Here you need to add a new instance, give the name of the engine, any website and just create it for now.
2. Now go to its control panel and in the basic options > Sites to search, you have the option to search the entire web (with emphasis on some websites if you want to include some) or search only for some websites (should be included in list, patterns can also be included).
3. Configure it as per your choice and in Details section you will find the search engine ID by clicking on the Search Engine ID button.

Now you are ready to integrate. The code to integrate the API using Express and Node JS is:

var express = require('express');
var path = require('path');
var app = express();

var request = require('request');

// The main search function
var google_web_search = function(search, callback) {
    console.log('Searching the web for: ', search);
    var options = {
        method: 'GET',
        url: 'https://www.googleapis.com/customsearch/v1',
        qs: {
            q: search,
            key: '<API_KEY>',
            cx: '<SEARCH_ENGINE_ID>',
        }
    };

    request(options, function (error, response, body) {
        callback(error, body);
    });
};
app.get('/', function (req, res) {
   google_web_search('<YOUR_SEARCH_QUERY>', function(error, body) {
     if (!error) {
        res.send(body);
     } else {
        throw new Error(error);
     }
   });
});

app.listen(3000, function () {
    console.log('Example app listening on port 3000!');
});

If you want more results, then you can use pagination by adding two query params:
1. num: specifies the number of results to return in the response
2. start: specifies the number of results to skip

Comments

One response to “Google Custom Search with NodeJS”

  1. Thanks for sharing. I read many of your blog posts, cool, your blog is very good.

Recent Post

  • AI Chatbots for Sales Team Automation: The Critical Role of AI Sales Assistants in Automating Your Sales Team

    Sales teams are the heart of any successful business, but managing them effectively can often feel like trying to juggle flaming swords. The constant pressure to generate leads, maintain relationships, and close deals leaves your team overwhelmed, spending more time on administrative tasks than actual selling. Here’s where AI-powered sales assistants step in to completely […]

  • Transforming HR with AI Assistants: The Comprehensive Guide

    The role of Human Resources (HR) is critical for the smooth functioning of any organization, from handling administrative tasks to shaping workplace culture and driving strategic decisions. However, traditional methods often fall short of meeting the demands of a modern, dynamic workforce. This is where our Human Resource AI assistants enter —a game-changing tool that […]

  • How Conversational AI Chatbots Improve Conversion Rates in E-Commerce?

    The digital shopping experience has evolved, with Conversational AI Chatbots revolutionizing customer interactions in e-commerce. These AI-powered systems offer personalized, real-time communication with customers, streamlining the buying process and increasing conversion rates. But how do Conversational AI Chatbots improve e-commerce conversion rates, and what are the real benefits for customers? In this blog, we’ll break […]

  • 12 Essential SaaS Metrics to Track Business Growth

    In the dynamic landscape of Software as a Service (SaaS), the ability to leverage data effectively is paramount for long-term success. As SaaS businesses grow, tracking the right SaaS metrics becomes essential for understanding performance, optimizing strategies, and fostering sustainable growth. This comprehensive guide explores 12 essential SaaS metrics that every SaaS business should track […]

  • Bagging vs Boosting: Understanding the Key Differences in Ensemble Learning

    In modern machine learning, achieving accurate predictions is critical for various applications. Two powerful ensemble learning techniques that help enhance model performance are Bagging and Boosting. These methods aim to combine multiple weak learners to build a stronger, more accurate model. However, they differ significantly in their approaches. In this comprehensive guide, we will dive […]

  • What Is Synthetic Data? Benefits, Techniques & Applications in AI & ML

    In today’s data-driven era, information is the cornerstone of technological advancement and business innovation. However, real-world data often presents challenges—such as scarcity, sensitivity, and high costs—especially when it comes to specific or restricted datasets. Synthetic data offers a transformative solution, providing businesses and researchers with a way to generate realistic and usable data without the […]

Click to Copy