Beginner’s Guide for Web Scraping

 

Suppose we have a website that has tons of useful data e.g.: Millions of email address 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 process, 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 of programs that will reach the website, parse the HTML of the pages, and extract the data predefined tags of HTML.

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

Let’s understand by a scenario:

Suppose you have a website that contains 30 thousand schools in 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 will send HTTPS requests to the website and get the response back from the website in HTML. It parses this HTML, searches for names and contact numbers of schools in that HTML effectively and stores them in excel or JSON on the local computer. And this all takes much less time than doing it manually.

Why Python:

Easy to learn for beginners with simple syntax yet powerful programming language with collections of more than 100 thousand libraries with huge community support. Python is also known for lesser numbers of lines for large tasks as compared to other programming languages like Java or C#.

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 its content. It is standard for creating web pages as almost all the websites on the internet have html for their structuring.

It consists of elements represented by html tags, these tags contain content like text, links, images enclosed between them or sometimes enclosed in them.

Applications of web scraping: 

  1. Extract Data
  2. Images
  3. Contacts
  4. Customized Data
  5. E-commerce Products Scraping
  6. Comparison of Products and/or Prices
  7. Events
  8. Betting Statistics Scraping

How data is delivered:

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

Main Libraries for Beginners: 

  1. Pandas 
  2. BS4 or Beautiful Soup
  3. Requests
  4. Selenium

Extras:

  • Basics of Servers: Servers in web scraping are used to execute time taking scraping 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 script.exe file.

Future:

Web scraping could be helpful in future for data analysis, market analysis and sentiment analysis to drive the results and make data oriented decisions. Further web scraping can be extended as data mining, data preparation, Data Visualization etc.

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

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