Web Scraping Google Search Knowledge Graph using Nodejs

What will be scraped

📌Note: The knowledge graph has different layouts, so the code I provide works with this layout as shown in the screenshot.

Google Knowledge Graph API

Alternatively, you can use the Google Knowledge Graph API from SerpApi. SerpApi is a free API with 100 search per month. If you need more searches, there are paid plans.

The difference is that you will get a ready-made structured JSON, and you will not need to look for the right selectors, which can change over time, bypass blocking from Google, and maintain a solution written from scratch. Check out the playground.

First we need to install google-search-results-nodejs. To do this you need to enter in your console: npm i google-search-results-nodejs

const SerpApi = require("google-search-results-nodejs");
const search = new SerpApi.GoogleSearch(process.env.API_KEY);

const searchString = "tesla";                           // what we want to search

const params = {
  engine: "google",                                     // search engine
  q: searchString,                                      // search query
  google_domain: "google.com",                          // google domain of the search
  gl: "us",                                             // parameter defines the country to use for the Google search
  hl: "en",                                             // Parameter defines the language to use for the Google search
};

const getKnowledgeGraph = function ({ knowledge_graph }) {
  const allInfo = {
    title: '',
    type: '',
    image: '',
    website: '',
    description: {},
    main: {},
    profiles: {},
    peopleAlsoSearchFor: {}
  } 
    for (const key in knowledge_graph) {
        if (key.includes('_link') || key.includes('_stick') || key === "see_results_about") {
        } else if (key === 'title') {
          allInfo.title = knowledge_graph[key]
        } else if (key === 'type') {
          allInfo.type = knowledge_graph[key]
        } else if (key === 'image') {
          allInfo.image = knowledge_graph[key]
        } else if (key === 'website') {
          allInfo.website = knowledge_graph[key]
        } else if (key === 'description') {
          allInfo.description.text = knowledge_graph[key];
        } else if (key === 'source') {
          allInfo.description.source = knowledge_graph[key].name;
          allInfo.description.link = knowledge_graph[key].link;
        } else if (key === 'profiles') {
          allInfo.profiles = knowledge_graph[key].reduce((acc, el) => {
            return { ...acc, [el.name]: el.link };
          }, {});
        } else if (key === 'people_also_search_for') {
          allInfo.peopleAlsoSearchFor = knowledge_graph[key].reduce((acc, el) => {
            return { ...acc, [el.name]: el.link };
          }, {});
        } else {
          allInfo.main = {...allInfo.main, [key]: knowledge_graph[key]}
    }
  }
  return allInfo
};

const getJson = (params) => {
  return new Promise((resolve) => {
    search.json(params, resolve);
  })
}

getJson(params).then(getKnowledgeGraph).then(console.log)

Code explanation

Declare constants from required libraries:

const SerpApi = require("google-search-results-nodejs");
const search = new SerpApi.GoogleSearch(API_KEY);

Next, we write down what we want to search and the necessary parameters for making a request:

const searchString = "tesla";

const params = {
  engine: "google",
  q: searchString,
  google_domain: "google.com",
  gl: "us",
  hl: "en",
};

Next, we write a callback function in which we describe what data we need from the result of our request:

const getKnowledgeGraph = function ({ knowledge_graph }) {
  const allInfo = {
    title: '',
    type: '',
    image: '',
    website: '',
    description: {},
    main: {},
    profiles: {},
    peopleAlsoSearchFor: {}
  } 
    for (const key in knowledge_graph) {
        if (key.includes('_link') || key.includes('_stick') || key === "see_results_about") {
        } else if (key === 'title') {
          allInfo.title = knowledge_graph[key]
        } else if (key === 'type') {
          allInfo.type = knowledge_graph[key]
        } else if (key === 'image') {
          allInfo.image = knowledge_graph[key]
        } else if (key === 'website') {
          allInfo.website = knowledge_graph[key]
        } else if (key === 'description') {
          allInfo.description.text = knowledge_graph[key];
        } else if (key === 'source') {
          allInfo.description.source = knowledge_graph[key].name;
          allInfo.description.link = knowledge_graph[key].link;
        } else if (key === 'profiles') {
          allInfo.profiles = knowledge_graph[key].reduce((acc, el) => {
            return { ...acc, [el.name]: el.link };
          }, {});
        } else if (key === 'people_also_search_for') {
          allInfo.peopleAlsoSearchFor = knowledge_graph[key].reduce((acc, el) => {
            return { ...acc, [el.name]: el.link };
          }, {});
        } else {
          allInfo.main = {...allInfo.main, [key]: knowledge_graph[key]}
    }
  }
  return allInfo
};

Also, we need to iterate our knowledge_graph object instead of just getting data like const allInfo = {title: knowledge_graph.title, ...} because data (key names) that I called main is changes with different search requests in the knowledge_graph object.

Next, we wrap the search method from the SerpApi library in a promise to further work with the search results and run it:

const getJson = (params) => {
  return new Promise((resolve) => {
    search.json(params, resolve);
  })
}

getJson(params).then(getKnowledgeGraph).then(console.log)

Output

{
  "title": "Tesla, Inc.",
  "type": "Automotive company",
  "image": "https://serpapi.com/searches/628b8735c9de453fe70b510f/images/1a7dfb07b83eed4f02ee96a98be925e974d4df171887903d.png",
  "website": "http://www.tesla.com/",
  "description": {
    "text": "Tesla, Inc. is an American automotive and clean energy company based in Austin, Texas. Tesla designs and manufactures electric vehicles, battery energy storage from home to grid-scale, solar panels and solar roof tiles, and related products and services.",
    "source": "Wikipedia",
    "link": "https://en.wikipedia.org/wiki/Tesla,_Inc."
  },
  "main": {
    "customer_service_chat": "Online Chat",
    "stock_price": "TSLA (NASDAQ) $663.90 0.00 (0.00%)May 20, 4 - 00 PM EDT - Disclaimer",
    "customer_service": "1 (888) 518-3752",
    "sales": "1 (650) 681-5100",
    "founded": "July 1, 2003, San Carlos, CA",
    "headquarters": "Austin, TX",
    "founders": "Elon Musk, Martin Eberhard, JB Straubel, Marc Tarpenning, Ian Wright",
    "latest_models": [
      {
        "name": "2022 Tesla Model 3",
        "link": "https://www.google.com/search?gl=us&hl=en&q=2022+Tesla+Model+3&stick=H4sIAAAAAAAAAONgFuLUz9U3SCmyNEhR4tVP1zc0LEoxyzUwLqvQEnbOzy1IzKsMyffNT0nNiUxNLCpexCpkZGBkpBCSWpyTqAAWVzDewcoIAL7IDD1JAAAA&sa=X&ved=2ahUKEwjSlIW_2PX3AhVIgnIEHZbWC48QxA16BAhbEAQ",
        "serpapi_link": "https://serpapi.com/search.json?device=desktop&engine=google&gl=us&google_domain=google.com&hl=en&q=2022+Tesla+Model+3&stick=H4sIAAAAAAAAAONgFuLUz9U3SCmyNEhR4tVP1zc0LEoxyzUwLqvQEnbOzy1IzKsMyffNT0nNiUxNLCpexCpkZGBkpBCSWpyTqAAWVzDewcoIAL7IDD1JAAAA",
        "image": "https://serpapi.com/searches/628b8735c9de453fe70b510f/images/1a7dfb07b83eed4f02ee96a98be925e99c59f5f2d71c9ea5561e55bdf61e24cadcb4829328a89a90.jpeg"
      },
      {
        "name": "2022 Tesla Model Y",
        "link": "https://www.google.com/search?gl=us&hl=en&q=2022+Tesla+Model+Y&stick=H4sIAAAAAAAAAONgFuLUz9U3SCmyNEhR4tVP1zc0LEqxrCgptCzWEnbOzy1IzKsMyffNT0nNiUxNLCpexCpkZGBkpBCSWpyTqAAWV4jcwcoIAPfknH5JAAAA&sa=X&ved=2ahUKEwjSlIW_2PX3AhVIgnIEHZbWC48QxA16BAhbEAY",
        "serpapi_link": "https://serpapi.com/search.json?device=desktop&engine=google&gl=us&google_domain=google.com&hl=en&q=2022+Tesla+Model+Y&stick=H4sIAAAAAAAAAONgFuLUz9U3SCmyNEhR4tVP1zc0LEqxrCgptCzWEnbOzy1IzKsMyffNT0nNiUxNLCpexCpkZGBkpBCSWpyTqAAWV4jcwcoIAPfknH5JAAAA",
        "image": "https://serpapi.com/searches/628b8735c9de453fe70b510f/images/1a7dfb07b83eed4f02ee96a98be925e99c59f5f2d71c9ea50307ca9e270b1cba5b983d776f28ce53.jpeg"
      },
      {
        "name": "2022 Tesla Model S",
        "link": "https://www.google.com/search?gl=us&hl=en&q=2022+Tesla+Model+S&stick=H4sIAAAAAAAAAONgFuLUz9U3SCmyNEhR4tVP1zc0LIovN0sqLE_XEnbOzy1IzKsMyffNT0nNiUxNLCpexCpkZGBkpBCSWpyTqAAWVwjewcoIANpU_c1JAAAA&sa=X&ved=2ahUKEwjSlIW_2PX3AhVIgnIEHZbWC48QxA16BAhbEAg",
        "serpapi_link": "https://serpapi.com/search.json?device=desktop&engine=google&gl=us&google_domain=google.com&hl=en&q=2022+Tesla+Model+S&stick=H4sIAAAAAAAAAONgFuLUz9U3SCmyNEhR4tVP1zc0LIovN0sqLE_XEnbOzy1IzKsMyffNT0nNiUxNLCpexCpkZGBkpBCSWpyTqAAWVwjewcoIANpU_c1JAAAA",
        "image": "https://serpapi.com/searches/628b8735c9de453fe70b510f/images/1a7dfb07b83eed4f02ee96a98be925e99c59f5f2d71c9ea5c9f47ee764fde2f1e79caf855134005d.jpeg"
      },
      {
        "name": "2022 Tesla Model X",
        "link": "https://www.google.com/search?gl=us&hl=en&q=2022+Tesla+Model+X&stick=H4sIAAAAAAAAAONgFuLUz9U3SCmyNEhR4tVP1zc0LEqxKDMtN0_SEnbOzy1IzKsMyffNT0nNiUxNLCpexCpkZGBkpBCSWpyTqAAWV4jYwcoIAFWdvepJAAAA&sa=X&ved=2ahUKEwjSlIW_2PX3AhVIgnIEHZbWC48QxA16BAhbEAo",
        "serpapi_link": "https://serpapi.com/search.json?device=desktop&engine=google&gl=us&google_domain=google.com&hl=en&q=2022+Tesla+Model+X&stick=H4sIAAAAAAAAAONgFuLUz9U3SCmyNEhR4tVP1zc0LEqxKDMtN0_SEnbOzy1IzKsMyffNT0nNiUxNLCpexCpkZGBkpBCSWpyTqAAWV4jYwcoIAFWdvepJAAAA",
        "image": "https://serpapi.com/searches/628b8735c9de453fe70b510f/images/1a7dfb07b83eed4f02ee96a98be925e99c59f5f2d71c9ea5f246cc054e2a0060fbff0bd16f3567fb.jpeg"
      }
    ]
  },
  "profiles": {
    "Twitter": "https://twitter.com/Tesla",
    "LinkedIn": "https://www.linkedin.com/company/tesla-motors",
    "Instagram": "https://www.instagram.com/teslamotors",
    "YouTube": "https://www.youtube.com/user/TeslaMotors",
    "Facebook": "https://www.facebook.com/electriceverywhere/"
  },
  "peopleAlsoSearchFor": {
    "Rivian": "https://www.google.com/search?gl=us&hl=en&q=Rivian&si=AC1wQDBgv4q3A2ojf086TvVgL6tTfKEZW2vrlR3V2uQ-r4wcbsReC3ET6H2gzOSJ83emah_DqBM87DBklcE_mqoTL6cnz4FB1PMxbYfHDHyZdLCyx8zARIwys088KWe7WiklQlXZK_a7dUf-yHR9rfskLPg5guGpehAFTM3fd3hWpBPW5dczKTfsYPqr14le6A9ntskIhEz3TcTFs-NfV-pYomsgg4TqTCwEZ2q78gSuQ2k7lCmM2RK7N6D_QrOJII8refqi1sQCnF5fSz2dpVnhex28ek6DZBQAIBWnfpqfBT0TR8mmzQY%3D&sa=X&ved=2ahUKEwjSlIW_2PX3AhVIgnIEHZbWC48QxA16BAhcEAU",
    "Porsche": "https://www.google.com/search?gl=us&hl=en&q=Porsche&si=AC1wQDCwN61-ebmuwbQCO5QCrgOvEq5bkWeIzJ5JczItzAKNdRDXvnuw4L4VhlFx9HJV6OqmqtHAqzPbjVJQTwLot5VNg5xzaaCA4jSgbzJaVgihv2J3-LIDNlX1WqL91VSm_FeZk82jX-bHWYKn10Fi0s1BJzHTawI0qAtv96gwjDkx7V_htiR2kxFVzA7AQ4cQCw3CJ6Ip1UkJtRCk5CfuKq3PhLki8BfCXnAWXVPJ7q8ySkdC74wGOae908caHajpT8We8-UmIUtPdHFJCOecopicrNqwbDKyCtQFvP-2Q5CY5uyu2DA%3D&sa=X&ved=2ahUKEwjSlIW_2PX3AhVIgnIEHZbWC48QxA16BAhcEAc",
    "NIO": "https://www.google.com/search?gl=us&hl=en&q=NIO&si=AC1wQDAXKblb4YtxZaDquKpQ5Js55CVph8NS1FIwBhgs6qyyHkehlU67aH1NSQuNhCW8DVAYZPw0DpddMm6wTKTN_Bvaze-B5FZFuI7smOYC3exZRBqB1hk0qKg9Kiv1fQ59L8TBbBAU8OOK0XFI4nAnmzy7G1NxHWMC_rq2hInqckB6GzyuGbsYEFixmX3yYpjCk9nUgVi_bvFQ-uWAdGaEZEaX-TpmPVtqjgcckC13fXyJMz-b8twpo4MntcWGbO06ceNB2YD9IvnaliU-XIfwHtOZc2pEhvax5L1V4cNA2sXlCyiTCx0%3D&sa=X&ved=2ahUKEwjSlIW_2PX3AhVIgnIEHZbWC48QxA16BAhcEAk",
    "Sunrun": "https://www.google.com/search?gl=us&hl=en&q=Sunrun&si=AC1wQDBgv4q3A2ojf086TvVgL6tTfKEZW2vrlR3V2uQ-r4wcbmSu5nhquKqWlG2lGADH9r4kgGmXn4Lx085H40Gw8Qkq5MAMrE_2zOdeGSFnxbNwaYps0-scCzFFuAgxHXGMOmaKcxEYHFbpyU29GQaUYPgTlYfFkN9MHAcmUOFQVoDAAuPOSgbHN3qoHZP7jZiqoHw74zfkgeYScjelV-aWW1jx8mBj4pStMhjKSwEoLlri5O63Di9LXMX9LIAasThnFWea1p-jMKTqh4GUWrQXSjXOMFRGAgS_uBO7Fkfe0-vXKOx77A0%3D&sa=X&ved=2ahUKEwjSlIW_2PX3AhVIgnIEHZbWC48QxA16BAhcEAs"
  }
}

DIY Preparation

First, we need to create a Node.js* project and add npm packages cheerio to parse parts of the HTML markup, and axios to make a request to a website. To do this, in the directory with our project, open the command line and enter npm init -y, and then npm i cheerio axios.

*If you don't have Node.js installed, you can download it from nodejs.org and follow the installation documentation.

Process

SelectorGadget Chrome extension was used to grab CSS selectors by clicking on the desired element in the browser. If you have any struggles understanding this, we have a dedicated Web Scraping with CSS Selectors blog post at SerpApi.
The Gif below illustrates the approach of selecting different parts of the results.

DIY Code

const cheerio = require("cheerio");
const axios = require("axios");

const searchString = "tesla";                                    // what we want to search
    const encodedString = encodeURI(searchString);              // what we want to search for in URI encoding

const domain = `http://google.com`;                             // google domain of the search

const AXIOS_OPTIONS = {
  headers: {
    "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/101.0.4951.64 Safari/537.36",
  },                                                            // adding the User-Agent header as one way to prevent the request from being blocked
  params: {
    q: encodedString,                                           // our encoded search string
    hl: "en",                                                   // Parameter defines the language to use for the Google search
    gl: "us",                                                   // parameter defines the country to use for the Google search
  },
};

function getKnowledgeGraphInfo() {
  return axios.get(`${domain}/search`, AXIOS_OPTIONS).then(function ({ data }) {
    let $ = cheerio.load(data);

    const pattern = /s='(?<img>[^']+)';\w+\s\w+=\['(?<id>\w+_\d+)'];/gm;      // https://regex101.com/r/pMd0yx/1
    const images = [...data.matchAll(pattern)].map(({ groups }) => ({ id: groups.id, img: groups.img.replace(/\\x3d/gi, "") }));

    const allInfo = {
      title: $(".I6TXqe .qrShPb span").text().trim(),
      type: $(".I6TXqe .wwUB2c span").text().trim(),
      image: images.find(({ id }) => id === $(".I6TXqe .FZylgf img").attr("id"))?.img,
      website: $(".I6TXqe .B1uW2d").attr("href"),
      description: {
        text: $(".LWkfKe+ span").text().trim(),
        source: $(".NJLBac").text().trim(),
        link: $(".NJLBac").attr("href"),
      },
      main: Array.from($(".I6TXqe .wDYxhc .Z1hOCe")).reduce((acc, el) => {
        const key = $(el).find(".w8qArf a").text().trim();
        return { ...acc, [key]: $(el).find(".kno-fv").text() };
      }, {}),
      profiles: Array.from($(".I6TXqe .OOijTb .fl")).reduce((acc, el) => {
        const key = $(el).find(".CtCigf").text().trim();
        return { ...acc, [key]: $(el).find("a").attr("href") };
      }, {}),
      peopleAlsoSearchFor: Array.from($(".I6TXqe .VLkRKc").closest(".UDZeY").find(".Wr0c6d")).reduce((acc, el) => {
        const key = $(el).text().trim();
        return { ...acc, [key]: domain + $(el).attr("href") };
      }, {}),
    };

    return allInfo;
  });
}

getKnowledgeGraphInfo().then(console.log);

Code explanation

Declare constants from required libraries:

const cheerio = require("cheerio");
const axios = require("axios");

Next, we write in constants what we want to search for and encode our text into a URI string:

const searchString = "tesla";
const encodedString = encodeURI(searchString);

Next, we write down the necessary parameters for making a request:

const AXIOS_OPTIONS = {
  headers: {
    "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/101.0.4951.64 Safari/537.36",
  },
  params: {
    q: encodedString,
    hl: "en",
    gl: "us",
  },
};

And finally a function to get the necessary information:

function getKnowledgeGraphInfo() {
  return axios.get(`${domain}/search`, AXIOS_OPTIONS).then(function ({ data }) {
    let $ = cheerio.load(data);

    const pattern = /s='(?<img>[^']+)';\w+\s\w+=\['(?<id>\w+_\d+)'];/gm;
    const images = [...data.matchAll(pattern)].map(({ groups }) => ({ id: groups.id, img: groups.img.replace(/\\x3d/gi, "") }));

    const allInfo = {
      title: $(".I6TXqe .qrShPb span").text().trim(),
      type: $(".I6TXqe .wwUB2c span").text().trim(),
      image: images.find(({ id }) => id === $(".I6TXqe .FZylgf img")?.attr("id")).img,
      website: $(".I6TXqe .B1uW2d").attr("href"),
      description: {
        text: $(".LWkfKe+ span").text().trim(),
        source: $(".NJLBac").text().trim(),
        link: $(".NJLBac").attr("href"),
      },
      main: Array.from($(".I6TXqe .wDYxhc .Z1hOCe")).reduce((acc, el) => {
        const key = $(el).find(".w8qArf a").text().trim();
        return { ...acc, [key]: $(el).find(".kno-fv").text() };
      }, {}),
      profiles: Array.from($(".I6TXqe .OOijTb .fl")).reduce((acc, el) => {
        const key = $(el).find(".CtCigf").text().trim();
        return { ...acc, [key]: $(el).find("a").attr("href") };
      }, {}),
      peopleAlsoSearchFor: Array.from($(".I6TXqe .VLkRKc").closest(".UDZeY").find(".Wr0c6d")).reduce((acc, el) => {
        const key = $(el).text().trim();
        return { ...acc, [key]: domain + $(el).attr("href") };
      }, {}),
    };

    return allInfo;
  });
}

Now we can launch our parser. To do this enter node YOUR_FILE_NAME in your command line. Where YOUR_FILE_NAME is the name of your .js file.

Output

{
  "title": "Tesla, Inc.",
  "type": "Automotive company",
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  "website": "http://www.tesla.com/",
  "description": {
    "text": "Tesla, Inc. is an American automotive and clean energy company based in Austin, Texas. Tesla designs and manufactures electric vehicles, battery energy storage from home to grid-scale, solar panels and solar roof tiles, and related products and services.",
    "source": "Wikipedia",
    "link": "https://en.wikipedia.org/wiki/Tesla,_Inc."
  },
  "main": {
    "Customer service chat": "Online Chat",
    "Stock price": "TSLA (NASDAQ) $663.90 -45.52 (-6.42%)May 20, 4:00 PM EDT - Disclaimer",
    "Customer service": "1 (888) 518-3752",
    "Sales": "1 (650) 681-5100",
    "Founded": "July 1, 2003, San Carlos, CA",
    "Headquarters": "Austin, TX",
    "Founders": "Elon Musk, Martin Eberhard, JB Straubel, Marc Tarpenning, Ian Wright"
  },
  "profiles": {
    "Twitter": "https://twitter.com/Tesla",
    "Instagram": "https://www.instagram.com/teslamotors",
    "LinkedIn": "https://www.linkedin.com/company/tesla-motors",
    "YouTube": "https://www.youtube.com/user/TeslaMotors",
    "Facebook": "https://www.facebook.com/electriceverywhere/"
  },
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  }
}

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