Top 4 Programming Languages for Web Scraping

Which programming language should I choose for web scraping?

Just like any other technology today, web scraping is constantly advancing and expanding, evolving and changing every day. Although web scraping was an extremely simple process written in simple code in the past, today it has become an extremely complex process where many different software tools are used and executed in line with these software tools. More importantly, web scraping can be built with various programming languages and can also be performed with a number of proxies.

You cannot do web scraping without using a programming language, as web scraping would be an impossible process without scraping bots. Bots are extremely important to web scraping tools that you need to code properly to perform certain actions. These web scraping tools may be powered by artificial intelligence, or they may be software-only. If you want to develop viable data scraping tools, you need to learn the basics of programming. In this article, we told you why you should choose the right language, whether web scraping speed depends on the software language, how to do error-free and risk-free web scraping, and the best programming languagesfor web scraping.

If you don’t want to learn a brand new programming language from scratch, or if you want to run a web scraping project without the need for software, Scrape.do team would like to help you. Simply contact us to take advantage of our cloud-based web scraping tools. Choose us to get the best service at the cheapest prices in the industry!

Why is Choosing the Right Language for Web Scraping Important?

Learning a good programming language is essential if you want to build a scraping bot and scan the web. After learning the programming language, you can create a web scraper bot that can target websites, filter relevant content to get the data you need, and easily scrape the web. If you want your web scraping project, whether large or small, to be successful, you need to choose the right programming language for this task.

The language you choose to create a web scraper bot is extremely important because the more complex code the bot you create, the easier it can perform web scraping and help you get the data you want. If you want to choose one of the best scripting languages for your web scraping, you should make sure that your scripting language has these features:

Level of flexibility to edit as you wish
Operational ability to develop and nurture your database
Possibility of high-level scanning and scraping
Easy to code
Being scalable
Being sustainable
Ability to avoid mechanisms such as blocking and detection that can negatively affect your web scraping process

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Does Your Web Scraping Project Completion Speed Depend On The Programming Language You Choose?

While many beginners think that the programming language affects the completion speed of their web scraping projects a lot, in fact, the processing speed of the programming language is a factor that does not affect the web scraping speed too much. When we think practically, we can say that the main factor that affects the speed the most is the input/output. If you want your web scraping speed to increase, the main point you should pay attention to is communication with the internet.

As it is known, the speed of your internet cannot easily keep up with the speed of your processor. However, this does not mean that the speed of the coding languages and themselves are unimportant. The speed of a programming language often depends on the speed of development, ease of maintenance, and code readability. Naturally, the speed of completion of your web scraping project also depends on the potential speed of your programming language.

How to Execute a Web Project That Doesn’t Contain Risk and Errors in Any Way?

Proxy servers, which will come across as one of the best solutions you can use if you want to run a secure and efficient web scraping project, have the middle stage role between a user and the website that the user wants to access.

Let’s reinforce it with an example. If you want to access information from a website and scrape that information and store it elsewhere, you must first send a request to the website owner asking for access. However, this request will reach the proxy server just before it reaches the owner of the website you want to scrape. After the proxy server sees your request, it will change the IP address and send your request to access the website to the website owner. Since your proxy server shows the website owner by changing your IP address, you will not be at any risk and you will be able to start viewing the data and scraping the data you want after your request is automatically approved by the website owner.

We mentioned that the proxy server changes your IP address, so it will be impossible to track your trace on the internet. Since web scraping will not be a one-time process and you will be doing web scraping frequently, you will need to make some changes and take advantage of programs to understand what requirements you will need and to ensure that your web scraping projects are not hindered.

Best Programming Languages for Web Scraping: Top 4

Let’s list the top five programming languagesyou can use for web scraping, JavaScript, Python, Ruby, and C++. You should continue reading this section to learn the language that you can use for your web scraping project and which is most suitable for you. After reading this chapter, you will understand more clearly which programming language you need.

1. JavaScript

According to statistics published by Github, a famous code-sharing site, JavaScript, which was chosen as the most popular programming language last year, was originally designed for front-end web development. Thanks to this coding language, which has the Node.js environment, it has become possible to develop web applications. As an important part of Javascript, Node.js also has libraries such as Puppeteer and Axios that are often used for web scraping. Puppeteer was chosen as the best library according to a 2019 study comparing which libraries are better for web scraping projects, and it performed much more efficiently than the other options. If you have even some experience with JavaScript, you should use JavaScript with Node.js. Here are the benefits of using JavaScript for web scraping:

JavaScript is one of the best programming languages to find support through large communities, online forums, and tutorials. Compared to other programming languages in this article, we can say that JavaScript is the programming language that has the most questions and therefore resources on Stackoverflow.
You can process simultaneous web page queries using Node.js at the same time and get a very efficient result as a result of this process.
For operations that require a constant stream of data input and data output, Node.js has much better performance than Python. Also, if you use Node.js, your waiting time will be minimized.

Here are the challenges you will encounter when using JavaScript for web scraping:

JavaScript is not easy for people with no knowledge of coding or programming to understand.
JavaScript is not as good, robust, and efficient as Python for CPU-intensive tasks like parsing and editing data after collecting large amounts of data.
There is also a challenge known as callback hell for JavaScript, which is of a nature that allows multiple queries to run efficiently. This challenge addresses a nested function structure that cascades a bug in any function to other layers of the code. Developers with no experience in JavaScript should be aware of workarounds to avoid this hassle.

2. Python

Python, the second most common programming language of 2021, is extremely convenient and easy to understand, especially for programmers who are just starting out with the coding. To automate the web scraping task, Python includes Selenium as well as third-party libraries such as BeautifulSoup and Scrapy specifically for web scraping. Python is often used for web scraping because Python is extremely easy to use and has a wealth of open-source guides and tutorials. If you are new to coding and web scraping, it would make the most sense to continue any web scraping project you have with Python. Here are the benefits of Python:

While JavaScript is the most popular when it comes to the availability of online resources and community, Python is also extremely rich in resources.
Python is the ideal language for people with little or no experience because Python is easier to understand than other languages.

Here are some of the challenges you may encounter once you start using Python:

Python’s most popular challenges are language-specific rather than web scraping-specific. One of these problems is that database access is weaker. Python has weaker protocols for database access compared to JDBC or ODBC, so Python is less preferred by companies because of its database. If you want your web scraping results to be stored directly in your database, you should integrate another layer for that.
Python is one of the slowest languages compared to other programming languages. According to tests on Benchmarksgame, Python is extremely slow compared to JavaScript. However, when it comes to web scraping, the speed of the programming language largely depends on the code of the program and the quality and quantity of requests made to the website. For this reason, whether you use Python or JavaScript, your web scraping project can be extremely long to complete.

3. Ruby

When we compare Ruby with Python and JavaScript, we can say that Ruby is much less used by programmers, but this programming language has certain features tailored to web scraping use cases. For example, Ruby’s library called Nokogiri has powerful ways to parse HTML and XML that you can use to output web scraping. Here’s why you should use Ruby:

Although Ruby’s syntax is not as interpretable as Python’s, coding with Python’s functionality can be done in Ruby with fewer lines of code.
Ruby’s Bundler feature makes it easy to manage and distribute packages from GitHub, helping you save time, especially on projects where you need to use an existing package.
Ruby’s Nokogiri library will be able to deal with broken HTML code more easily than other languages.

If you’re wondering why Ruby isn’t so popular, you should definitely check out these challenges:

Ruby is not a programming language of choice as much as Python and Javascript because it has far fewer resources and community tools.
Machine learning and NLP toolkits are some of the most important use cases that rely on web scraping data and are often the purpose of web scraping. These toolkits were not developed for Ruby, just as they were not developed for other languages such as Python. If you choose Ruby for data collection and parsing, models may still need to be developed in other languages.

4. C++

While running a web scraping project with C and C++, which offers outstanding execution, is extremely costly, these languages are often preferred for web scraping. It is not recommended to use this language for just web scraping unless you want to have a dedicated organization for web scraping and data storage only. Let’s explain why you should choose C++ for web scraping, listing it as follows:

The C++ scripting language is extremely easy to use and customize for web scraping.
Just use C++’s libcurl to get the URL addresses.
You don’t need a library to turn the entire HTML document into a scannable structure, as scraping just for a specific topic is simpler than editing and executing a DOM tree.
The most important advantage of using the C++ scripting language is that you can easily parallelize your scraper.

Here is a list of reasons why it is not appropriate to use C++ for web scraping:

For any web scraping-related project, using C++ will definitely not be a great choice, as it will be easier to handle using a dynamic language.
As we explained earlier, if you want to set up a web scraping setup using C++, you may have to pay quite a bit of money.

If you want to learn a programming language for your web scraping projects and save time and hassle for data extraction and parsing, you can get help from a web scraping agency. We at Scrape.do offer you cloud services that speed up the process and facilitate data storage and enable you to enjoy all the benefits of cloud web scraping. You also need additional development when you use the web scraping program yourself. At Scrape.do we handle dynamic IP and proxy issues and help you do your best web scraping. ‍