Web scraping is also known as web harvesting or data extraction. It is used for extracting data from the website. Web scraping a web page involves fetching and extracting from it. Fetching is the downloading of a page. Therefore, web crawling is a main component of web scraping, to fetch pages for later processing. Once fetched, then the extraction can take place. It is also used for contact scrapping, and as a component of applications used for web indexing, web mining, and data mining.
Data can be extracted from the web source using a number of methods, popular websites like Google, Facebook, and Twitter to extract the available data in a structured manner. This prevents the use of other methods that may not be preferred by the API provider.
To carry out web scraping using Python, you will first have to install the Python Environment, which enables to run code written in the python language. It exactly understands the website and how the things are laid out and Python we are using because it is ridiculous fast as well as easy to this kind of web- scraping.
The very first step is to check a website's Terms and Conditions before you scrape it. Be careful to read the statements about legal use of data. Usually, the data you scrape should not be used for commercial purposes.
Don't request data from the website too aggressively with your program termed as spamming, as this may break the website. The program should behave in a reasonable manner means it should work as a human. One request for one webpage per second is good practice.
The layout of a website may change from time to time, so make sure to revisit the site and rewrite your code as needed.
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