In this blog, I am going to use a puppeteer to scrap Wikipedia pages

Puppeteer is a Node library that provides a high-level API to control Chrome or Chromium over the DevTools Protocol. which is headless

we are going to achieve this in two steps the first step scrap the Wikipedia page[en.wikipedia.org/wiki/List_of_programming_l.. to get all the programming names and URLs to specific Wikipedia programming language pages [en.wikipedia.org/wiki/:programminglanguageN.. and stored in an array(which contains an object of name and URLs

const puppeteer = require("puppeteer");//headless chrome 

var fs = require("fs");
let List_of_programming_languages = [];// to store the name ad urls of programming languages 
(async () => {
  const browser = await puppeteer.launch();

  const page = await browser.newPage();
  await page.goto(
    "https://en.wikipedia.org/wiki/List_of_programming_languages"
  );
  await page.waitForTimeout(2000);//waiting for 2000 seconds to load the webpage 

  const getLanguageUrl = await page.evaluate(() => {
    let urls = document.querySelectorAll(".div-col ul li a");//the class name for extracting  anchor tag  

    const urlList = [...urls];

    console.log(urlList);
    const extractedUrls = urlList.map((u) => u.getAttribute("href"));//extracting only links from anchor tags 

    return extractedUrls;
  });

  const getLanguageName = await page.evaluate(() => {
    let headingFromWeb = document.querySelectorAll(".div-col");//the class name for extracting  div 


    const lanuagesNameList = [...headingFromWeb];

    const extractedLanuagesNameList = lanuagesNameList.map((h) => h.innerText);//extracting only inner text from div 

    return extractedLanuagesNameList;
  });

  const allLanguagesUrls = [...getLanguageUrl];
  const allLanguagesNames = [...getLanguageName];
  const nameDataSplit = allLanguagesNames.join("").split("\n");
//saving the urls and name as single object
  List_of_programming_languages = nameDataSplit.map((name, i) => {
    return {
      name,
      url: allLanguagesUrls[i],
    };
  });

the second step using the above array of URLs. from this specific Wikipedia programming I have taken full data from table(which has class name .infobox) like [Paradigm, Designed by, Developer, First appeared, Website, etc..] including images and also took the first four-paragraph for description and generated an object for each programming pushed it into an array and saved it into the file.

const getEachLanguageDetails = async () => {
    const browser = await puppeteer.launch();
    const page = await browser.newPage();

    let allLanguagesDetails = [];
    for (i = 0; i <= List_of_programming_languages.length; i++) {
      try {
        await page.goto(
          "https://en.wikipedia.org" + List_of_programming_languages[i].url
        );
        await page.waitForTimeout(1000);

        const name = await page.evaluate(() => {
          return document.querySelector(".infobox-title")
            ? document.querySelector(".infobox-title").innerText
            : undefined;
        });

        const img_result = await page.evaluate(() => {
          return document.querySelector(".infobox-image a img ")
            ? document
                .querySelector(".infobox-image a img ")
                .getAttribute("src")
            : undefined;
        });

        const getTableLabels = await page.evaluate(() => {
          let labelsdata = document.querySelectorAll(
            ".infobox  .infobox-label"
          );

          const labelList = [...labelsdata];

          const extractedLabelList = labelList.map((h) => h.innerText);

          return extractedLabelList;
        });
        const getTableData = await page.evaluate(() => {
          let tableData = document.querySelectorAll(".infobox  .infobox-data");

          const tableDataList = [...tableData];

          const extractedTableDataList = tableDataList.map((h) => h.innerText);

          return extractedTableDataList;
        });

        const p1 = await page.evaluate(
          () => document.querySelectorAll("p")[1].innerText
        );
        const p2 = await page.evaluate(
          () => document.querySelectorAll("p")[2].innerText
        );
        const p3 = await page.evaluate(
          () => document.querySelectorAll("p")[3].innerText
        );
        const p4 = await page.evaluate(
          () => document.querySelectorAll("p")[4].innerText
        );

        let eachLanguageDescription = {
          name: name ? name : List_of_programming_languages[i].name,
          image: img_result ? "https:" + img_result : undefined,
          description: p1 + " " + p2 + " " + p3 + " " + p4,
        };
        getTableLabels.forEach((e, i) => {
          eachLanguageDescription[e] = getTableData[i];
        });

        allLanguagesDetails.push(eachLanguageDescription);
      } catch (e) {
        console.log(e);
      }
    }
    fs.writeFile(
      "languages.txt",
      JSON.stringify(allLanguagesDetails),
      (err) => {
        if (err) throw err;
        console.log('The "data to append" was appended to file!');
      }
    );
  };

  getEachLanguageDetails();
  await browser.close();
})();

The final code will be available at wikipedia-scraping-puppeteer