Scraping Booking.com Property Listings with Rust in 2023

In this article, we will learn how to scrape property listings from Booking.com using Rust. We will use the reqwest and select crates to fetch the HTML content and then extract key information like property name, location, ratings, etc.

Prerequisites

To follow along, you will need:

Rust installed on your system

Cargo package manager

Basic knowledge of Rust programming

Creating a New Project

Let's start by creating a new Rust project:

cargo new booking-scraper
cd booking-scraper

This will generate a simple Rust project for us to work with.

Adding Dependencies

Now we need to add the reqwest and select crates as dependencies in Cargo.toml:

[dependencies]
reqwest = "0.11"
select = "0.5"

Importing Crates

At the top of main.rs, let's import the crates:

use reqwest;
use select::document::Document;
use select::predicate::Name;

reqwest will be used to make HTTP requests.

select will help parse and query the HTML.

Defining the Target URL

Let's define the URL we want to scrape:

let url = "<https://www.booking.com/searchresults.html?ss=New+York&>...";

We won't paste the full URL here for brevity.

Setting a User Agent

We need to set a valid user agent header:

let client = reqwest::Client::new();
let headers = reqwest::header::HeaderMap::new();
headers.insert("User-Agent", "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/98.0.4758.102 Safari/537.36".parse().unwrap());

This will make the request appear to come from a real browser.

Fetching the HTML Page

Now we can make the GET request:

let res = client.get(url).headers(headers).send().await?;

if res.status().is_success() {
  // Parse HTML
} else {
  println!("Request failed");
}

We check that the request succeeded before parsing the HTML.

Parsing the HTML

To parse the HTML, we convert the response body to a string:

let html = res.text().await?;
let document = Document::from(html.as_str());

This creates a select::Document from the HTML.

Extracting Property Cards

The property cards have a data-testid attribute we can search for:

let property_cards = document.find(Name("div").and(Name("data-testid").equals("property-card")));

This uses CSS selectors to find the matching

elements.

Looping Through Cards

We can iterate through the cards:

for card in property_cards {

  // Extract data from card

}

Inside this loop we will extract information from each card node.

Extracting Title

To get the title, we search for the data-testid="title" element:

let title = card.find(Name("div").and(Name("data-testid").equals("title")))
                .next()
                .map(|n| n.text());

We take the first matching node and get its text contents.

Extracting Location

Similarly, the address is under a data-testid="address" element:

let location = card.find(Name("span").and(Name("data-testid").equals("address")))
                   .next()
                   .map(|n| n.text());

The pattern is the same for other fields.

Extracting Rating

The star rating aria-label contains the score:

let rating = card.find(Name("div").and(Class("e4755bbd60")))
                 .next()
                 .and_then(|n| n.attr("aria-label"));

Here we get the aria-label attribute from the

Extracting Review Count

The review count text is inside a class="abf093bdfe" element:

let review_count = card.find(Class("abf093bdfe"))
                       .next()
                       .map(|n| n.text());

Extracting Description

The description is in a class="d7449d770c" element:

let description = card.find(Class("d7449d770c"))
                      .next()
                      .map(|n| n.text());

Printing the Data

Finally, we can print out the extracted data:

println!("Name: {}", title);
println!("Location: {}", location);
println!("Rating: {}", rating);
// etc...

Here is the full code.


use reqwest;
use select::document::Document;
use select::predicate::{Class, Name};

#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {

  let url = "https://www.booking.com/searchresults.en-gb.html?ss=New+York&checkin=2023-03-01&checkout=2023-03-05&group_adults=2";
  
  let client = reqwest::Client::new();

  let headers = reqwest::header::HeaderMap::new();
  headers.insert("User-Agent", "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/98.0.4758.102 Safari/537.36".parse().unwrap());

  let res = client.get(url).headers(headers).send().await?;

  if res.status().is_success() {

    let html = res.text().await?;

    let document = Document::from(html.as_str());

    let property_cards = document.find(Name("div").and(Name("data-testid").equals("property-card")));

    for card in property_cards {
    
      let title = card.find(Name("div").and(Name("data-testid").equals("title")))
                      .next()
                      .map(|n| n.text());

      let location = card.find(Name("span").and(Name("data-testid").equals("address")))
                         .next()
                         .map(|n| n.text());
      
      let rating = card.find(Name("div").and(Class("e4755bbd60")))
                       .next()
                       .and_then(|n| n.attr("aria-label"));
                       
      let review_count = card.find(Class("abf093bdfe"))
                             .next()
                             .map(|n| n.text());
                             
      let description = card.find(Class("d7449d770c"))
                            .next()
                            .map(|n| n.text());

      println!("Name: {}", title);
      println!("Location: {}", location);
      println!("Rating: {}", rating);
      println!("Review Count: {}", review_count); 
      println!("Description: {}", description);
    }

  } else {
    println!("Request failed");
  }

  Ok(())
}

And that covers the basics of scraping data from Booking.com in Rust! The same principles can be applied to any site.

While these examples are great for learning, scraping production-level sites can pose challenges like CAPTCHAs, IP blocks, and bot detection. Rotating proxies and automated CAPTCHA solving can help.

Proxies API offers a simple API for rendering pages with built-in proxy rotation, CAPTCHA solving, and evasion of IP blocks. You can fetch rendered pages in any language without configuring browsers or proxies yourself.

This allows scraping at scale without headaches of IP blocks. Proxies API has a free tier to get started. Check out the API and sign up for an API key to supercharge your web scraping.

With the power of Proxies API combined with Python libraries like Beautiful Soup, you can scrape data at scale without getting blocked.

Scraping Booking.com Property Listings with Rust in 2023

Prerequisites

Creating a New Project

Adding Dependencies

Importing Crates

Defining the Target URL

Setting a User Agent

Fetching the HTML Page

Parsing the HTML

Extracting Property Cards

Looping Through Cards

Extracting Title

Extracting Location

Extracting Rating

Extracting Review Count

Extracting Description

Printing the Data

Browse by language:

The easiest way to do Web Scraping

Scraping Booking.com Property Listings with Rust in 2023

Prerequisites

Creating a New Project

Adding Dependencies

Importing Crates

Defining the Target URL

Setting a User Agent

Fetching the HTML Page

Parsing the HTML

Extracting Property Cards

Looping Through Cards

Extracting Title

Extracting Location

Extracting Rating

Extracting Review Count

Extracting Description

Printing the Data

The easiest way to do Web Scraping

Don't leave just yet!