Data science has become a crucial technology in today's business.
Web scraping is one of the essential parts of data source for data science. Here is some point on the facts about web scraping.
Web scraping means pulling data from the internet on a database with the help of a bot. If you are just copy-pasting, it won't be called web scraping.
Although our intuitions say that web scraping is illegal, it is legal to scrape publically available data. See the article https://tinyurl.com/2hbrjcwm. Although if the data is behind the login page, it might be unlawful to scrape.
There are two types of ways you can do web scraping. One is by coding, which is free, and the second is by using third party web scraping services. We use both of them equally.
Most common programming language used is python. And the packages that are primarily used are BeautifulSoup, requests, scrapy etc.
The most used tools are ParseHub, OctoParse, Scraper API, etc. They all have unique features and different price points.
Although web scraping is excellent, there are some challenges. Bot access, IP blocking, Captcha, Honeypot traps, Login requirement, and Dynamic content, to name a few, are the challenges that have to be mitigated for smooth scraping.
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