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https://github.com/muhammedrahil/web-scraping-using-python

Web scraping is an automatic method to obtain large amounts of data from websites. Most of this data is unstructured data in an HTML format which is then converted into structured data in a spreadsheet or a database so that it can be used in various applications
https://github.com/muhammedrahil/web-scraping-using-python

beautifulsoup4 csv python requests web webscraping

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Web scraping is an automatic method to obtain large amounts of data from websites. Most of this data is unstructured data in an HTML format which is then converted into structured data in a spreadsheet or a database so that it can be used in various applications

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# Web-scraping-Using-Python

Web scraping is an automatic method to obtain large amounts of data from websites. Most of this data is unstructured data in an HTML format which is then converted into structured data in a spreadsheet or a database so that it can be used in various applications



## 1. Web Scraping



 Web scraping is an automatic method to obtain large amounts of data from websites. Most of this data is unstructured 

data in an HTML format which is then converted into structured data in a spreadsheet 

or a database so that it can be used in various applications. There are many different ways to perform web scraping to 

obtain data from websites. These include using online services, particular API’s or even creating your code for web 

scraping from scratch. Many large websites, like Google, Twitter, Facebook, StackOverflow, etc. have API’s that allow

you to access their data in a structured format. This is the best option, but there are other sites that don’t allow

users to access large amounts of data in a structured form or they are simply not that technologically advanced.

In that situation, it’s best to use Web Scraping to scrape the website for data.



## 2. How  Web Scrapers Work?

Web Scrapers can extract all the data on particular sites or the specific data that a user wants. Ideally,

 it’s best if you specify the data you want so that the web scraper only extracts that data quickly. For 

 example, you might want to scrape an Amazon page for the types of juicers available, but you might only 

 want the data about the models of different juicers and not the customer reviews. 



So, when a web scraper needs to scrape a site, first the URLs are provided. Then it loads all the HTML code 

for those sites and a more advanced scraper might even extract all the CSS and Javascript elements as well. 

Then the scraper obtains the required data from this HTML code and outputs this data in the format specified 

by the user. Mostly, this is in the form of an Excel spreadsheet or a CSV file, but the data can also be saved 

in other formats, such as a JSON file.



## 3. Different Types of Web Scrapers

Web Scrapers can be divided on the basis of many different criteria, including Self-built or Pre-built Web Scrapers,

 Browser extension or Software Web Scrapers, and Cloud or Local Web Scrapers.



eg:

  1. Price Monitoring

  2. Market Research

  3. News Monitoring

  4. Sentiment Analysis

  5. Email Marketing



## Reference Documents



Pypy beautifulsoup4 -  https://pypi.org/project/beautifulsoup4/



Beautiful Soup Documentation - https://www.crummy.com/software/BeautifulSoup/bs4/doc/



Web scraping wikipedia - https://en.wikipedia.org/wiki/Web_scraping



Web scraping geek for geek - https://www.geeksforgeeks.org/what-is-web-scraping-and-how-to-use-it/



example web scraping youtube video - https://www.youtube.com/watch?v=ng2o98k983k



## pip

``` pip install beautifulsoup4 ```



``` pip install requests ```



```  pip install lxml  ```