Collecting data with Selenium: fast website parsing

If you've ever wondered how experienced programmers automate their tasks without wasting time on routine actions like opening pages, entering data and collecting information - welcome to the world of parsing with Selenium and Python.

If you need to process large amounts of data or automate interaction - with Python and Selenium, parsing a website is easy. In this article we will tell you how to use them for data collection.

Why is parsing needed?

Why waste time on manual data collection when it can be automated? Who would think of copying information from websites and pasting it into spreadsheets manually? It's not just slow, it's catastrophically inefficient. In the era of big data, every self-respecting professional is using parsing to automate the collection of information from thousands of pages in minutes.

But if you think that just opening a website with your browser is parsing, you're in for a disappointment. Parsing is a science. And you need to know tools like Selenium to conquer websites. Selenium handles your browser as if you were sitting at your computer. Except it doesn't make mistakes and it doesn't get tired.

Is parsing easier with Selenium?

Selenium is a framework that allows you to fully control your browser: open pages, click buttons, enter text, scroll pages and, of course, parse data. With Selenium, parsing becomes simple. Selenium supports all browsers: Chrome, Firefox, Safari, Opera - and even Internet Explorer, if you suddenly decide to remember 2010.

But most importantly: with Selenium, parsing a website is different because you have control over the DOM (Document Object Model), the structure of the HTML page. This is what allows you to find and extract any data. That is, when you see a huge table with a million rows on the page, you just tell Selenium: “Find me this element and copy the data”. And Selenium will do it.

What happens after entering these commands? Selenium opens the site, finds the element with ID “my_element” and extracts the text.

Why is Python the best choice for parsing?

Python is one of the simplest and most powerful languages for working with data. Python already has all the necessary libraries for working with the web: BeautifulSoup, Requests and, of course, Selenium. 

Libraries are not everything. Python has a clear and concise syntax. Even beginners quickly learn to write and read code. 

Large projects like Reddit and Dropbox are written in Python. And if these companies trust their products to Python, the choice is obvious.

Proxy is an indispensable assistant in parsing

Parsing is not just going to a website and downloading data. Websites are not as friendly as they seem. They don't like it when you send too many requests, especially from the same IP address. 

That's where proxies come in. Proxy servers change IPs, masking your location.

We offer all kinds of proxies: mobile, residential, and server proxies. They are easy to integrate into Python and Selenium code, which allows you not just to parse, but to do it as efficiently as possible.

How to configure Selenium with proxy?

Let's show you how to add a proxy to Selenium quickly and easily. For example, let's take Chrome and configure it with a proxy:

Now we have added a proxy as an argument for Chrome browser so that all requests go through it. This is a key point that will help to avoid bans and increase the chances of successful parsing.

Selenium and captchas: not an easy task

Captchas are a stumbling block for parsing. But experienced users know that you can fight captchas. The easiest way is to use services for automatic captcha solving, such as 2Captcha or AntiCaptcha.

With Selenium integration with such services, parsing of large sites becomes not just possible, but routine. But if a site uses too complex protection mechanisms, Selenium plus a proxy from Proxys.io will help to easily complete data collection.

Parsing with Selenium and Python is the best solution for web automation. If you want not just to do it, but to do it with efficiency, you need Selenium for browser control, Python for code and a proxy from Proxys.io.