Web Scraping Google With Rust

The Rust programming language was developed by Mozilla in 2010, as an alternative to C and C++. It is widely used for web and game development.

This blog post will mainly focus on how to extract data from Google Search Results and some pros and cons of this programming language.

We are going to use two libraries, request and scraper, in this tutorial for scraping and parsing the raw HTML data.

By the end of this article, you will have a basic understanding of scraping Google Search Results with Rust. You can also leverage this knowledge for future web scraping projects with other programming languages.

Rust is a high-level powerful programming language that has given a good amount of significance to its performance and concurrency. Its asynchronous programming structure allows scraping servers to handle multiple requests simultaneously, which makes it a reliable choice for handling large amounts of data and complex web scraping tasks.

Another advantage of using Rust is that it has several powerful libraries for web scraping such as reqwest that can help developers extract and process web pages easily. Also, libraries like html5ever and scraper are blazingly fast when it comes to HTML parsing.

Overall, Rust can be an efficient choice for not only scraping Google but also for other web scrapings tasks, which is only possible due to its insane emphasis on performance and its robust system of libraries.

Scraping Google Search Results With Rust is pretty easy. We will extract the first page results from Google, consisting of the title, link, and description. I must say, it will take a while for beginners to get used to Ruby syntax. But yeah, practice makes you better!

The scraping would be in two parts:

For beginners, to install Rust on your device, you can watch these videos:

After installing Rust successfully, you can run this command to create a Rust project folder:

Then, we will install two libraries that we will use in this tutorial.

You can add these libraries to your cargo.toml file like this:

Now, these libraries are finally accessible in the src/main.rs file.

So, we are done with the setup. You can open your project file in your editor and write the below code to import both the required crates:

Then, we will create the main function to extract the results.

Step-by-step explanation:

Now, with the help of Html object from the scraper crate, we convert the extracted HTML into a document object model.

Then, with the help of a Selector object from the scraper crate, we will select all the matching div with the class name g.

If you iterate the Google Search Page, you will get to know that every organic result is inside the div with class g.

Let us now iterate over all these selected divs to get the required search data.

We have followed the same process for the link and snippet, but a little difference in the link is we have extracted the href attribute of the anchor(represented by a in the code) tag.

You can find the tags for the title, link, and description under the container div.g.

After running the code successfully, your results should look like this:

So, this is the fundamental way of scraping Google Search results with Rust.

1. Rust can handle a large amount of data thanks to its robust concurrency model.

2. Extreme level of performance by Rust makes it a popular choice for game development, system-level programming, and other intensive applications.

3. It supports reverse compatibility, allowing it to run older code even on the latest versions of the language.

1. The code can be challenging to understand for beginners because of the complex syntax.

2. Community support has not grown much, so the developer has to struggle even more to solve a small error.

In this tutorial, we learned to scrape Google Search Results with Rust. We also learned some benefits and disadvantages of using Rust.

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