Web Scraping with Python: BeautifulSoup, Requests & Selenium
1.23 GB | MP4 + SRT | 8 Hours | English | Elearning | 301 kb/s | 1280x720 | aac, 48000 Hz, stereo
Description

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Web Scraping (also termed Screen Scraping, Web Data Extraction, Web Harvesting,

etc.) is a technique for extracting large amounts of data from websites and save the

the extracted data to a local file or to a database.

In this course, you will learn how to perform web scraping using Python 3 and the

Beautiful Soup, a free open-source library written in Python for parsing HTML.

We will use lxml, which is an extensive library for parsing XML and HTML documents

very quickly; it can even handle messed up tags. We will also be using the Requests

module instead of the already built-in urllib2 module due to improvements in speed

and readability.

Finally, we will use Selenium alongside Beautiful Soup to crawl AJAX & jаvascript

driven pages. The course cover the following topics: accessing web pages

programmatically; scraping web pages to extract the required data using Beautiful

Soup to parse web pages; interacting with web pages to do different things with them

programmatically; and using Selenium for web scraping and when we need it.

By the end of this course, you will be able to understand how websites and servers

function, diverse data extraction techniques, and methods of handling and organizing

data.

This Web Scraping course covers the following topics:

Review of data structures (Lists, Dictionaries, Tuples, File Handling)
How websites are hosted on servers
Calls to the server (GET, POST methods)
Review of HTML and CSS
Requests Module and BeautifulSoup Module overview
Parsing HTML using BeautifulSoup
Filtering elements using BeautifulSoup and navigating the Parse Tree
jаvascript and AJAX overview
Selenium and the need for it
Selecting elements using Selenium
CSS selectors
XPath selectors
Navigating pages using Selenium
Practical Projects

Requirements

Some prior programming experience in Python (e.g. Data Structures and OOP) will

help. The course includes a full Python refresher section.
Complete beginners may wish to take a beginner Python course first, and then

transition to this course afterwards.
This course adopts a step-by-step approach and requires you to open a Python editor,

download available *.py code files, and start applying the provided examples and

exercises.
Python 3: Codes of this course are tested on Python 3. It is up to you to adapt them

if you want to run them in Python 2.

Who is the target audience?
Those whoe want to learn how to use Python for web scraping and data extraction.