Many people choose to use Python for data extraction, and not without a good reason. If you want to get something done, it is best to get it done in the most accessible way in a world where time and resources mean money. It explains the rush towards using Python and its flock of libraries and frameworks for web scraping.
What is Web Scraping.
Web scraping, also commonly called web data extraction or web harvesting is defined as the process of collecting both structured and unstructured user data in varying amounts from multiple websites.
The process is mainly automated and finds a way to interact with the target website, retrieve the necessary data, parse it, and then save it on the client’s computer in an easily readable format, e.g., a spreadsheet.
The purpose of doing this is to have enough valuable data to drive business decisions, and some of the things a business can do with the collected data include:
⦁ Brand monitoring and protection
⦁ Monitoring competition and price
⦁ Conducting market research and analysis
Main Programming Languages Used in Web Scraping
There are several languages used in web scraping. But the choice of which of the languages to use should be based, first, on what your needs are and, next, on which of the languages you are great at. And when trying to choose the best web scraping language, it is believed that the shortlist of questions below could help you make the right choice:
⦁ How flexible is the language?
⦁ How practical is any given crawling session?
⦁ How easy is it to write and code in that language?
⦁ Is the scraping script written in that language accessible to both scale and maintain?
⦁ Does the language have an operational ability to handle a vast database?
Best Web Scraping Languages
Python is, by all standards, the most popular web scraping language because it does not only make it easy to scrape websites automatically but also makes the entire process smooth and seamless.
Python is also the easiest to learn, and a typical web scraping Python script can be written in only a few lines. And within this language alone, you will find both the tools to extract data and parse or return it.
Some of the important Python tools widely employed in web scraping include libraries such as BeautifulSoup and Selenium or complete frameworks.
When combined, they can be used for asynchronous web scraping. Meaning you can scrape multiple websites at the same time.
Some of the features offered by this package include:
⦁ ExpressJS: a highly flexible framework that can be used on both mobile and web applications
⦁ Request, Request-promise, and Axios: very simple HTTP clients used for making HTTP requests
⦁ First, you find the webpage you intend to scrape
⦁ Next, you make an HTTP request to extract the data
⦁ The data is extracted and parsed to your device
⦁ Finally, you save the extracted data usually in JSON format
However, the choice of which web scraping language to use should be based entirely on what you wish to achieve and which of the languages you are already vast in.