Instagram is a very massive social media platform with tons of data, so let’s scrape some using Python! This is a pretty basic beginner project, we’re essentially going to be able to input an Instagram URL into our code, run the program, output specific data points and store them in a data frame, if that sounds like fun let’s get started! Oct 01, 2020 Selenium Python bindings is an API interface to use Python with Selenium WebDriver for writing functional/acceptance tests. We shall be using these Python bindings for Selenium to capture full page screenshots, HTML element-specific screenshots and save it in our desired location.

Beginner's guide to web scraping with python's selenium

In the first part of this series, we introduced ourselves to the concept of web scraping using two python libraries to achieve this task. Namely, requests and BeautifulSoup. The results were then stored in a JSON file. In this walkthrough, we'll tackle web scraping with a slightly different approach using the selenium python library. We'll then store the results in a CSV file using the pandas library.

Selenium Python Documentation

The code used in this example is on github.

Why use selenium

Selenium is a framework which is designed to automate test for web applications.You can then write a python script to control the browser interactions automatically such as link clicks and form submissions. However, in addition to all this selenium comes in handy when we want to scrape data from javascript generated content from a webpage. That is when the data shows up after many ajax requests. Nonetheless, both BeautifulSoup and scrapy are perfectly capable of extracting data from a webpage. The choice of library boils down to how the data in that particular webpage is rendered.

Other problems one might encounter while web scraping is the possibility of your IP address being blacklisted. I partnered with scraper API, a startup specializing in strategies that'll ease the worry of your IP address from being blocked while web scraping. They utilize IP rotation so you can avoid detection. Boasting over 20 million IP addresses and unlimited bandwidth.

In addition to this, they provide CAPTCHA handling for you as well as enabling a headless browser so that you'll appear to be a real user and not get detected as a web scraper. For more on its usage, check out my post on web scraping with scrapy. Although you can use it with both BeautifulSoup and selenium.

If you want more info as well as an intro the scrapy library check out my post on the topic.

Using this scraper api link and the codelewis10, you'll get a 10% discount off your first purchase!

For additional resources to understand the selenium library and best practices, this article by towards datascience and accordbox.

Setting up

We'll be using two python libraries. selenium and pandas. To install them simply run pip install selenium pandas

In addition to this, you'll need a browser driver to simulate browser sessions.Since I am on chrome, we'll be using that for the walkthrough.

Driver downloads

1. Chrome.

Getting started

For this example, we'll be extracting data from quotes to scrape which is specifically made to practise web scraping on.We'll then extract all the quotes and their authors and store them in a CSV file.

The code above is an import of the chrome driver and pandas libraries.We then make an instance of chrome by using driver = Chrome(webdriver)Note that the webdriver variable will point to the driver executable we downloaded previously for our browser of choice. If you happen to prefer firefox, import like so

Main script

On close inspection of the sites URL, we'll notice that the pagination URL isHttp://quotes.toscrape.com/js/page/{{current_page_number}}/

where the last part is the current page number. Armed with this information, we can proceed to make a page variable to store the exact number of web pages to scrape data from. In this instance, we'll be extracting data from just 10 web pages in an iterative manner.

The driver.get(url) command makes an HTTP get request to our desired webpage.From here, it's important to know the exact number of items to extract from the webpage.From our previous walkthrough, we defined web scraping as

This is the process of extracting information from a webpage by taking advantage of patterns in the web page's underlying code.

We can use web scraping to gather unstructured data from the internet, process it and store it in a structured format.

On inspecting each quote element, we observe that each quote is enclosed within a div with the class name of quote. By running the directive driver.get_elements_by_class('quote')we get a list of all elements within the page exhibiting this pattern.

Final step

To begin extracting the information from the webpages, we'll take advantage of the aforementioned patterns in the web pages underlying code.

We'll start by iterating over the quote elements, this allows us to go over each quote and extract a specific record.From the picture above we notice that the quote is enclosed within a span of class text and the author within the small tag with a class name of author.

Finally, we store the quote_text and author names variables in a tuple which we proceed to append to the python list by the name total.

Using the pandas library, we'll initiate a dataframe to store all the records(total list) and specify the column names as quote and author.Finally, export the dataframe to a CSV file which we named quoted.csv in this case.

Don't forget to close the chrome driver using driver.close().

Adittional resources

1. finding elements

You'll notice that I used the find_elements_by_class method in this walkthrough. This is not the only way to find elements. This tutorial by Klaus explains in detail how to use other selectors.

2. Video

If you prefer to learn using videos this series by Lucid programming was very useful to me.https://www.youtube.com/watch?v=zjo9yFHoUl8

Web Scraping Selenium Python Example

3. Best practises while using selenium

4. Toptal's guide to modern web scraping with selenium

And with that, hopefully, you too can make a simple web scraper using selenium 😎.

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open to collaboration

I recently made a collaborations page on my website. Have an interesting project in mind or want to fill a part-time role?You can now book a session with me directly from my site.

Thanks.

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.

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.

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:

• Clicking on buttons
• Filling forms
• Scrolling
• Taking a screenshot

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.

Installation

We will use Chrome in our example, so make sure you have it installed on your local machine:

• selenium package

To install the Selenium package, as always, I recommend that you create a virtual environment (for example using virtualenv) and then:

Quickstart

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 title
• driver.current_url gets the current URL (this can be useful when there are redirections on the website and you need the final URL)

Locating Elements

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).

Web Scraping Python Selenium Chrome

There are many methods available in the Selenium API to select elements on the page. You can use:

• Tag name
• Class name
• IDs
• XPath
• CSS selectors

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:

find_element

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.

WebElement

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:

• Accessing the text of the element with the property element.text
• Clicking on the element with element.click()
• Accessing an attribute with element.get_attribute('class')
• Sending text to an input with: 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.

Full example

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:

• Go to the login page using driver.get()
• Select the username input using driver.find_element_by_* and then element.send_keys() to send text to the input
• Follow the same process with the password input
• Click on the login button using element.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:

• Check for an error message (like “Wrong password”)
• Check for one element on the page that is only displayed once logged in.

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:

Taking a screenshot

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.

Waiting for an element to be present

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:

• Use a time.sleep(ARBITRARY_TIME) before taking the screenshot.
• Use a 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:

Python Web Scraping Example

• 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

Executing Javascript

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:

Conclusion

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.

Web Scraping Selenium Python

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: