• General Web Scraping

  Scrape AajTak.com with Rust & PostgreSQL: Extracting News Headlines, Categories, and Publish Dates for Media Analysis

  Posted by Wisteria Radim on 02/12/2025 at 6:16 pm

  Scrape AajTak.com with Rust

  Introduction to Web Scraping with Rust: AajTak.com Case Study

  Web scraping is a powerful technique used to extract information from websites. It is particularly useful for gathering data from sites that do not provide an API. In this article, we will explore how to scrape AajTak.com, a popular Indian news website, using the Rust programming language. Rust is known for its performance and safety, making it an excellent choice for web scraping tasks.

  AajTak.com is a comprehensive news portal that covers a wide range of topics, including politics, sports, entertainment, and more. By scraping this site, we can gather valuable data for analysis, research, or personal use. This case study will guide you through the process of setting up a Rust-based scraper to extract information from AajTak.com.

  Before diving into the implementation, it’s important to understand the legal and ethical considerations of web scraping. Always ensure that you comply with the website’s terms of service and robots.txt file. Additionally, be mindful of the server load and avoid making excessive requests that could disrupt the website’s operations.

  Rust offers several libraries that facilitate web scraping, such as `reqwest` for making HTTP requests and `scraper` for parsing HTML. These libraries provide a robust foundation for building a scraper that can efficiently extract data from AajTak.com.

  In the following sections, we will walk through the process of implementing a Rust-based scraper for AajTak.com. We will cover everything from setting up the development environment to writing the code and storing the scraped data in a database.

  Implementing a Rust-Based Scraper for AajTak.com

  To begin, we need to set up our Rust development environment. Ensure that you have Rust and Cargo installed on your system. You can download them from the official Rust website. Once installed, create a new Rust project using Cargo:

  cargo new aajtak_scraper

  Next, add the necessary dependencies to your `Cargo.toml` file. We will use `reqwest` for HTTP requests and `scraper` for HTML parsing:

  [dependencies]
  reqwest = “0.11”
  scraper = “0.12”

  With the dependencies in place, we can start writing the code for our scraper. First, let’s create a function to fetch the HTML content of a webpage:

  use reqwest;
  async fn fetch_html(url: &str) -> Result<String, reqwest::Error> {
  let response = reqwest::get(url).await?;
  let body = response.text().await?;
  Ok(body)
  }

  Now that we can fetch the HTML content, let’s parse it to extract the desired data. We will use the `scraper` library to select and extract elements from the HTML:

  use scraper::{Html, Selector};
  fn parse_html(html: &str) {
  let document = Html::parse_document(html);
  let selector = Selector::parse(“h2.title”).unwrap();
  for element in document.select(&selector) {
  let title = element.text().collect::().join(” “);
  println!(“Title: {}”, title);
  }
  }

  Storing Scraped Data in a Database

  Once we have extracted the data, the next step is to store it in a database for further analysis. We will use SQLite, a lightweight and easy-to-use database, to store the scraped data. First, add the `rusqlite` dependency to your `Cargo.toml` file:

  [dependencies]
  rusqlite = “0.25”

  Next, create a function to set up the database and insert the scraped data:

  use rusqlite::{params, Connection};
  fn setup_database() -> Result<Connection, rusqlite::Error> {
  let conn = Connection::open(“aajtak.db”)?;
  conn.execute(“CREATE TABLE IF NOT EXISTS news (id INTEGER PRIMARY KEY, title TEXT NOT NULL)”, params![])?;
  Ok(conn)
  }

  Now, let’s create a function to insert the scraped titles into the database:

  fn insert_title(conn: &Connection, title: &str) -> Result<(), rusqlite::Error> {
  conn.execute(“INSERT INTO news (title) VALUES (?1)”, params![title])?;
  Ok(())
  }

  Finally, integrate the database functions with the scraping logic to store the extracted titles:

  async fn scrape_aajtak() -> Result<(), Box<dyn std::error::Error>> {
  let url = “https://www.aajtak.com”;
  let html = fetch_html(url).await?;
  let conn = setup_database()?;
  parse_html(&html, &conn);
  Ok(())
  }

  Conclusion

  In this article, we explored how to scrape AajTak.com using the Rust programming language. We covered the entire process, from setting up the development environment to writing the code and storing the scraped data in a database. By leveraging Rust’s performance and safety features, we created an efficient and reliable web scraper.

  Web scraping is a valuable skill that can be applied to various domains, including data analysis, research, and business intelligence. With Rust, you can build powerful scrapers that handle large volumes of data with ease.

  Remember to always adhere to legal and ethical guidelines when scraping websites. Respect the website’s terms of service and avoid overloading their servers with excessive requests.

  We hope this case study has provided you with valuable insights into web scraping with Rust. Feel free to experiment with the code and adapt it to your specific needs. Happy scraping!

  For further reading, consider exploring Rust’s extensive documentation and community resources. There are many libraries and tools available that can enhance your web scraping projects.

  Wisteria Radim replied 1 week, 2 days ago 1 Member · 0 Replies
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