Best Web Scraping Beginners Guide

 

Understanding the Power of Web Scraping and Why Python is the Best Choice

Suppose we have a website that has tons of useful data, e.g., millions of email addresses or names of hospitals in the whole state, which needs to be downloaded. Manually, it would be very difficult to extract them into the computer for further processing, here comes web scraping.

Web scraping makes it easier to extract data or information from websites or web pages into a personal computer in much lesser time without doing much manual work. It is done by writing code or programs that will reach the website, parse the HTML of the pages, and extract the data from predefined tags of HTML.

Programming languages vary, but the most recommended programming language for web scraping is Python due to its processing speed, simplified syntax, mature community, and overwhelming adoption by corporate sectors.

Let’s Understand by a Scenario

Suppose you have a website that contains 30 thousand schools in the USA, UK, or say New York, and you need the names and contact numbers of these schools. Would you open 30K links and copy-paste the names and contact numbers manually? No.

So, the developer writes Python code and executes it. The code sends HTTPS requests to the website and gets the response back from the website in HTML. It parses this HTML, searches for names and contact numbers of schools effectively, and stores them in Excel or JSON on the local computer. And this all takes much less time than doing it manually.

For large-scale scraping or ongoing projects, you can also get help from Scraping Consultancy Services to build efficient, secure, and scalable scrapers.

Why Python?

Easy to learn for beginners with simple syntax yet a powerful programming language with a collection of more than 100,000 libraries and huge community support. Python is also known for fewer lines of code for large tasks compared to other programming languages like Java or C#.

If you’re building automation-based solutions, you can combine your scraping with Web Automation tools for a more robust workflow.

What You Should Know Before Learning Web Scraping

Basic Programming in Python:

Loops, if-else, try-except, list, dictionary, sets, Data Frame, typecasting, etc.
Built-in functions like len, type, range, break, pass, etc.
Boolean operators: or, and, not.

HTML:

HTML (Hypertext Markup Language) is used for creating the structure of web pages and formatting content. It’s standard for creating web pages, as almost all websites on the internet use HTML for their structure.

It consists of elements represented by HTML tags; these tags contain content like text, links, and images enclosed between them or sometimes nested inside.

Applications of Web Scraping

  • Extract Data

  • Images

  • Contacts

  • Customized Data

  • E-commerce Product Scraping

  • Comparison of Products and/or Prices

  • Events

  • Betting Statistics Scraping

If your business involves real estate or price tracking, our specialized Property Data Scraping and Price Comparison Services can also help automate your data collection.

How Data is Delivered

The scraped data or content can be delivered in various forms. MS Excel (.xlsx) or CSV (.csv) files are most commonly used. Although JSON or SQL Databases could also be good options for structured data storage.

Main Libraries for Beginners

  • Pandas

  • BS4 or Beautiful Soup

  • Requests

  • Selenium

Extras

  • Basics of Servers: Servers in web scraping are used to execute time-taking scripts that need more computational power.

  • Linux Commands: Proficiency in basic Linux commands is necessary for effectively utilizing Linux servers for web scraping tasks.

  • Converting (.py) to (.exe): pyinstaller is used to convert script.py into a script.exe file.

Future of Web Scraping

Web scraping will continue to be vital for data analysis, market analysis, and sentiment analysis to drive results and make data-oriented decisions. Further, web scraping can be extended into data mining, data preparation, and data visualization to support AI and machine learning projects.

If you have any questions, are curious to learn, or don’t know where to start, or if you have a task you want done, don’t hesitate to reach out to Scraping Solution by email or WhatsApp live chat.

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