• Post category:StudyBullet-8
  • Reading time:8 mins read


Extract data with Python , JavaScript, API and using No Code

What you will learn

Scrape data automatically with No Code

Scrape YouTube data using JavaScript and YouTube Data API

Scrape Amazon Data with Python

Scrape data with Scrapy

Scrape data with BeautifuSoup

Scrape data into GoogleSheets from YouTube

Description

Web scraping is the process of collecting structured web data in an automated fashion. It’s also called web data extraction. Some of the main use cases of web scraping include price monitoring, price intelligence, news monitoring, lead generation, and market research among many others.

In general, web data extraction is used by people and businesses who want to make use of the vast amount of publicly available web data to make smarter decisions.

If you’ve ever copied and pasted information from a website, you’ve performed the same function as any web scraper, only on a microscopic, manual scale. Unlike the mundane, mind-numbing process of manually extracting data, web scraping uses intelligent automation to retrieve hundreds, millions, or even billions of data points from the internet’s seemingly endless frontier.


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Web data extraction – also widely known as data scraping – has a huge range of applications. A data scraping tool can help you automate the process of extracting information from other websites, quickly and accurately. It can also make sure the data you’ve extracted is neatly organized, making it easier to analyze and use for other projects.

In the world of e-commerce, web data scraping is widely used for competitor price monitoring. It’s the only practical way for brands to check the pricing of their competitors’ products and services, allowing them to fine-tune their own price strategies and stay ahead of the game. It’s also used as a tool for manufacturers to ensure retailers are compliant with pricing guidelines for their products. Market research organizations and analysts depend on web data extraction to gauge consumer sentiment by keeping track of online product reviews, news articles, and feedback.

There’s a vast array of applications for data extraction in the financial world. Data scraping tools are used to extract insight from news stories, using this information to guide investment strategies. Similarly, researchers and analysts depend on data extraction to assess the financial health of companies. Insurance and financial services companies can mine a rich seam of alternative data scraped from the web to design new products and policies for their customers.

English
language

Content

Introduction

Introduction
What is Web Scraping and Web Crawling
What is Robot.txt
Legality of Web Scraping
Checks before web scraping

Python Setup

Installing Python on Windows
Installing Python on Macs
Create a virtual environment on Windows
Activate a virtual environment on Windows
Create a virtual environment on Macs
Activate a virtual environment on Macs
Update pip
Install Beautiful soup
Install Scrapy
Installing Visual Studio Code

Web Scraping with Python and Beautiful Soup

What we will scrape
Building the web scraping script : part 1
Building the web scraping script : part 2
Prototyping the script: Part 1
Prototyping the script: Part 2
Prototyping the script: Part 3
Prototyping the script: Part 4
Prototyping the script: Part 5
Testing the script

Web Scraping with Python and Scrapy

Create a Scrapy project
Components ofa scrapy project
Scrapy architecture
Creating a Spider: Part 1
Creating a Spider: Part 2
Scraping data with Scrapy shell: Part 1
Scraping data with Scrapy shell: Part 2
Testing the Scrapy Spider

Scraping Amazon Data with Python

Create and activate a virtual environment
Install Python Packages
Create a Python File
Create variables
send emails from Python
Create functions: Part 1
Create functions: Part 2
Create functions: Part 3
Testing the script

Web Scraping YouTube Data with API & JavaScript

What is an API
YouTube Data API
Using GoogleSheets
Building JavaScript Scraper : Part 1
Building JavaScript Scraper : Part 2
Building JavaScript Scraper : Part 3
Testing the first scraper
Building the second scraper
Testing the second scraper

Microsoft 365 and Power Automate Setup

Microsoft 365 Business Standard Setup
Getting started with Microsoft 365
What is Power Automate

Automating Web Scraping with No Code

Installing Power Automate Desktop
Explore Power Automate Desktop
Automate web scraping
Scrape Amazon website data
Scrape Ebay website data
Scrape Jobs website data
Scrape Hackernews website data