Web Scraping with Kotlin & ChatGPT

Sep 25, 2023 ยท 3 min read

Kotlin is a great language for web scraping thanks to its concise syntax, safety features and excellent library support. ChatGPT is an AI assistant that can provide explanations and generate code for scraping tasks. This article covers web scraping in Kotlin with help from ChatGPT.

Setting Up Kotlin for Web Scraping

You'll need Kotlin installed along with these libraries:

// Ktor for HTTP requests

// Jsoup for HTML parsing

// CSVWriter for CSV output

Introduction to Web Scraping in Kotlin

Web scraping involves sending HTTP requests to websites and extracting data from the HTML, JSON or XML responses. Useful Kotlin libraries:

  • Ktor - Asynchronous HTTP client
  • Jsoup - Java HTML parser with CSS selectors
  • Kotlinx Serialization - JSON and XML parsing
  • Typical web scraping workflow:

  • Send HTTP request to download a page
  • Parse response and extract relevant data
  • Store scraped data
  • Repeat for other pages
  • Using ChatGPT for Web Scraping Help

    ChatGPT is an AI assistant created by Anthropic to be helpful, harmless, and honest. It can provide explanations and generate code snippets for web scraping:

    Getting Explanations

    Ask ChatGPT to explain web scraping concepts or specifics:

  • How to use Jsoup to extract text from paragraph elements
  • Strategies for scraping content spread across pagination
  • Generating Code Snippets

    Give a description of what you want to scrape and have ChatGPT provide starter Kotlin code:

  • Scrape product listings into a CSV file
  • Parse date strings into LocalDateTime when extracting
  • Validate any code before using.

    Improving Prompts

    Ask ChatGPT to suggest ways to improve your prompt if it doesn't provide helpful responses.

    Asking Follow-up Questions

    Chat with ChatGPT to get explanations for any other questions you have.

    Explaining Errors

    Share any errors and ask ChatGPT to debug and explain the problem.

    Web Scraping Example Using ChatGPT

    Let's walk through scraping a Wikipedia page with ChatGPT's assistance.


    Extract the chronology table from: https://en.wikipedia.org/wiki/Chronology_of_the_universe

    Step 1: Download page

    ChatGPT: Kotlin code to download this page:
    // ChatGPT provides this code
    val response = client.get<String>("<https://en.wikipedia.org/wiki/Chronology_of_the_universe>")

    Step 2: Inspect HTML, table has class wikitable

    Step 3: Extract table data to CSV

    ChatGPT: Kotlin code to extract wikitable table to CSV
    // ChatGPT provides this code
    val doc = Jsoup.parse(response)
    val table = doc.select("table.wikitable").first()
    val headers = table.select("thead th").map { it.text() }
    val rows = table.select("tbody tr").map { row ->
      row.select("td").map { it.text() }
    // Write rows to CSV

    This demonstrates using ChatGPT to get Kotlin scraping code quickly.


    Key points:

  • Kotlin provides safety and concision for web scraping
  • ChatGPT can explain concepts and provide Kotlin code
  • Inspect HTML to understand how to extract data
  • Follow best practices like throttling requests, randomizing user agents
  • Web scraping allows gathering data from websites at scale with Kotlin
  • ChatGPT + Kotlin is a great combo for creating web scrapers.

    However, some limitations:

  • Handling anti-scraping measures like CAPTCHAs
  • Avoiding IP blocks when running locally
  • Rendering complex JavaScript pages
  • A more robust solution is using a web scraping API like Proxies API

    Proxies API provides:

  • Millions of proxy IPs to prevent blocks
  • Automated solving of CAPTCHAs
  • JavaScript rendering with headless browsing
  • Simple API instead of running your own scrapers
  • Easily scrape any site:

    val response = client.get<String>("<https://api.proxiesapi.com/?url=example.com&key=XXX>")

    Get started now with 1000 free API calls to supercharge your web scraping!

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    curl "http://api.proxiesapi.com/?key=API_KEY&url=https://example.com"

    <!doctype html>
        <title>Example Domain</title>
        <meta charset="utf-8" />
        <meta http-equiv="Content-type" content="text/html; charset=utf-8" />
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