Getting good quality data is at the core of data analytics and machine learning.
And websites are undeniably good and sometimes only source for these.
These days many websites are dynamic and require a high level of
interactivity to get down to the actual data,
and this is where Selenium and Python combine to help us out.
Hey everyone, this is Pratheerth,
and welcome to my course Scraping Dynamic Web Pages with Python and Selenium.
In this first module, we'll be exploring Selenium with Python.
Before we get into the nitty gritty of the module,
let's quickly go over some things that you need to know.
Right out of the gate,
this course will assume a basic to intermediate level of Python programming.
You'll also need a basic understanding of HTML and CSS,
so you understand how a web page is structured,
which would make the whole course make more sense.
It'll also be helpful if you're familiar with some
fundamentals about data analytics,
which will help you understand the need for the things we do during the course.
We'll go about the course in the following way.
First, I'll introduce a concept to you,
then we'll get a little bit more deeper into and you'll
get to see the nuts and bolts of it.
Lastly, we'll have a practical implementation of what you've just learned.
Here's what we'll cover in the first module.
For starters, we'll get into what exactly scraping dynamic websites mean.
How it is different from scraping normal, static websites?
Then we'll dive into Selenium for a little while.
We'll have a brief overview of what it is,
what are its components, and its use cases.
Then we'll go into more detail about one of Selenium's tools, the WebDriver.
We'll have two demos for this module.
In the first one,
I'll walk you through all the libraries and packages
required to use Selenium with Python,
which is what we'll use for the duration of the course,
and how to go about installing them.
In the second one, we'll use the WebDriver to open a web page.
Let's get started.