In the last tutorial we learned how to leverage the Scrapy framework to solve common web scraping problems.Today we are going to take a look at Selenium (with Python ❤️ ) in a step-by-step tutorial.
The ScrapeHero Cloud allows you to scrape Google search result pages for a variety of search terms in a fast and cost-effective manner. Using the ScrapeHero Cloud, you can scrape Google search results to gather details from Google Knowledge Graph, monitor organic and paid search results, gather news articles, and more within a few clicks. You can search and scan the search results but it is too time-consuming and tedious. Web scraping is used to scrape the data from different websites and glean actionable intelligence from these sites in terms of equity research. Using a web scraping tool is the easiest and the cheapest way to collect information from Google. Google hides Google results data in the search results as duplicates. If anyone attempts to scrape the search results, Google can block their IP addresses. Web scraping is the process of gathering information from the Internet. Even copy-pasting the lyrics of your favorite song is a form of web scraping! However, the words “web scraping” usually refer to a process that involves automation. Some websites don’t like it when automatic scrapers gather their data, while others don’t mind.
Selenium refers to a number of different open-source projects used for browser automation. It supports bindings for all major programming languages, including our favorite language: Python.
The Selenium API uses the WebDriver protocol to control a web browser, like Chrome, Firefox or Safari. The browser can run either localy or remotely.
This is a specific form of screen scraping or web scraping dedicated to search engines only. Most commonly larger search engine optimization (SEO) providers depend on regularly scraping keywords from search engines, especially Google, to monitor the competitive position of their customers' websites for relevant keywords or their indexing status.
At the beginning of the project (almost 20 years ago!) it was mostly used for cross-browser, end-to-end testing (acceptance tests).
Now it is still used for testing, but it is also used as a general browser automation platform. And of course, it us used for web scraping!
Selenium is useful when you have to perform an action on a website such as:
It is also useful for executing Javascript code. Let's say that you want to scrape a Single Page Application. Plus you haven't found an easy way to directly call the underlying APIs. In this case, Selenium might be what you need.
We will use Chrome in our example, so make sure you have it installed on your local machine:
selenium
packageTo install the Selenium package, as always, I recommend that you create a virtual environment (for example using virtualenv) and then:
Once you have downloaded both Chrome and Chromedriver and installed the Selenium package, you should be ready to start the browser:
This will launch Chrome in headfull mode (like regular Chrome, which is controlled by your Python code).You should see a message stating that the browser is controlled by automated software.
To run Chrome in headless mode (without any graphical user interface), you can run it on a server. See the following example:
The driver.page_source
will return the full page HTML code.
Here are two other interesting WebDriver properties:
driver.title
gets the page's titledriver.current_url
gets the current URL (this can be useful when there are redirections on the website and you need the final URL)Locating data on a website is one of the main use cases for Selenium, either for a test suite (making sure that a specific element is present/absent on the page) or to extract data and save it for further analysis (web scraping).
There are many methods available in the Selenium API to select elements on the page. You can use:
We recently published an article explaining XPath. Don't hesitate to take a look if you aren't familiar with XPath.
As usual, the easiest way to locate an element is to open your Chrome dev tools and inspect the element that you need.A cool shortcut for this is to highlight the element you want with your mouse and then press Ctrl + Shift + C or on macOS Cmd + Shift + C instead of having to right click + inspect each time:
There are many ways to locate an element in selenium.Let's say that we want to locate the h1 tag in this HTML:
All these methods also have find_elements
(note the plural) to return a list of elements.
For example, to get all anchors on a page, use the following:
Some elements aren't easily accessible with an ID or a simple class, and that's when you need an XPath expression. You also might have multiple elements with the same class (the ID is supposed to be unique).
XPath is my favorite way of locating elements on a web page. It's a powerful way to extract any element on a page, based on it's absolute position on the DOM, or relative to another element.
A WebElement
is a Selenium object representing an HTML element.
There are many actions that you can perform on those HTML elements, here are the most useful:
element.text
element.click()
element.get_attribute('class')
element.send_keys('mypassword')
There are some other interesting methods like is_displayed()
. This returns True if an element is visible to the user.
It can be interesting to avoid honeypots (like filling hidden inputs).
Honeypots are mechanisms used by website owners to detect bots. For example, if an HTML input has the attribute type=hidden
like this:
This input value is supposed to be blank. If a bot is visiting a page and fills all of the inputs on a form with random value, it will also fill the hidden input. A legitimate user would never fill the hidden input value, because it is not rendered by the browser.
That's a classic honeypot.
Here is a full example using Selenium API methods we just covered.
We are going to log into Hacker News:
In our example, authenticating to Hacker News is not really useful on its own. However, you could imagine creating a bot to automatically post a link to your latest blog post.
In order to authenticate we need to:
driver.get()
driver.find_element_by_*
and then element.send_keys()
to send text to the inputelement.click()
Should be easy right? Let's see the code:
Easy, right? Now there is one important thing that is missing here. How do we know if we are logged in?
We could try a couple of things:
So, we're going to check for the logout button. The logout button has the ID “logout” (easy)!
We can't just check if the element is None
because all of the find_element_by_*
raise an exception if the element is not found in the DOM.So we have to use a try/except block and catch the NoSuchElementException
exception:
We could easily take a screenshot using:
Note that a lot of things can go wrong when you take a screenshot with Selenium. First, you have to make sure that the window size is set correctly.Then, you need to make sure that every asynchronous HTTP call made by the frontend Javascript code has finished, and that the page is fully rendered.
In our Hacker News case it's simple and we don't have to worry about these issues.
Dealing with a website that uses lots of Javascript to render its content can be tricky. These days, more and more sites are using frameworks like Angular, React and Vue.js for their front-end. These front-end frameworks are complicated to deal with because they fire a lot of AJAX calls.
If we had to worry about an asynchronous HTTP call (or many) to an API, there are two ways to solve this:
time.sleep(ARBITRARY_TIME)
before taking the screenshot.WebDriverWait
object.If you use a time.sleep()
you will probably use an arbitrary value. The problem is, you're either waiting for too long or not enough.Also the website can load slowly on your local wifi internet connection, but will be 10 times faster on your cloud server.With the WebDriverWait
method you will wait the exact amount of time necessary for your element/data to be loaded.
This will wait five seconds for an element located by the ID “mySuperId” to be loaded.There are many other interesting expected conditions like:
element_to_be_clickable
text_to_be_present_in_element
element_to_be_clickable
You can find more information about this in the Selenium documentation
Sometimes, you may need to execute some Javascript on the page. For example, let's say you want to take a screenshot of some information, but you first need to scroll a bit to see it.You can easily do this with Selenium:
I hope you enjoyed this blog post! You should now have a good understanding of how the Selenium API works in Python. If you want to know more about how to scrape the web with Python don't hesitate to take a look at our general Python web scraping guide.
Selenium is often necessary to extract data from websites using lots of Javascript. The problem is that running lots of Selenium/Headless Chrome instances at scale is hard. This is one of the things we solve with ScrapingBee, our web scraping API
Selenium is also an excellent tool to automate almost anything on the web.
If you perform repetitive tasks like filling forms or checking information behind a login form where the website doesn't have an API, it's maybe* a good idea to automate it with Selenium,just don't forget this xkcd:
The hardest part about web scraping can be getting to the data you want to scrape.
For example, you might want to scrape data from a search results page for a number of keywords.
You mighty setup separate scraping projects for each keyword.
However, there are powerful web scrapers that can automate the searching process and scrape the data you want.
Today, we will set up a web scraper to search through a list of keywords and scrape data for each one.
For this project, we will use ParseHub. A free and powerful web scraper that can scrape data from any website. Make sure to download and install ParseHub for free before we get started.
We will also scrape data from Amazon’s search result page for a short list of keywords.
Now it’s time to setup our project and start scraping data.
Do you want to extract more data from each product? Check out our guide on how to scrape product data from Amazon including prices, ASIN codes and more.
Do you want to extract more pages worth of data? Check out our guide on how to add pagination to your project and extract data from more than one page of results.
It is now time to run your project and export it as an Excel file.
To do this, click on the green “Get Data” button on left sidebar.
Here you will be able to test, run or schedule your scrape job. In this case, we will run it right away.
ParseHub is now off to extract all the data you’ve selected. Once your scrape is complete, you will be able to download it as a CSV or JSON file.
You now know how to search through a list of keywords and extract data from each result.
What website will you scrape first?