Big data is the necessity and prospect of the digital world. Businesses rely on it for varied purposes. The internet is full of data and any business can extract data of varied types for their business. Data extraction or scraping is executed in two ways; manually and automatically. Python scraping is renowned for automatic web scraping.
Beautiful soup is one of the best and most sought after Python scraping libraries. It can pull data from XML and HTML. It is the easiest to learn for any budding programmer.
It has some dependencies like a “request library” for accessing the website. Besides, you need to use external parsers for data extraction. The use of dependencies makes the coding transfer intricate. Though its code transfer is complicated, it is the only Python scraping library with few lines of code.
It is a friendly tool but a little difficult to master. Moreover, it allows you to include actions such as click a button, select the drop-down menu and maximize windows.
The only distressing factor is its low speed. It is slower than an HTTP request and makes Python scraping longer but still, you can use it if speed is not a concern. Or you have few websites to extract.
Python scraping in India also uses the Scrapy framework for data extraction. The framework is exclusively dedicated to scraping and crafted using Python. It can work without traditional threading models. Its twisted asynchronous framework responds to different connections very easily.
Identifying the merits and demerits of each tool will let you select the best from the three. It is said that for large extraction projects you can fearlessly opt Scrapy framework for its greater functionalities and architecture. On the other hand, for simple and small web scraping projects, Beautifulsoup is the best choice. Selenium would be in the middle. You can use it as per your requirement.
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