Python as Web Scraping Language: Wintr as an Effective Web Scraper

By  //  May 13, 2020

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There is a deluge of information on the Internet as of today that can only be absorbed in a lifetime. Do you need access to such information? Certainly, not. Instead, you need a way to be able to collect or gather, organize, and analyze the information.

There is a deluge of information on the Internet as of today that can only be absorbed in a lifetime. Do you need access to such information? Certainly, not. Instead, you need a way to be able to collect or gather, organize, and analyze the information.

This is where you need web scraping. The function of web scraping is to extract data and make it presentable so that the user can make the most out of it.

While it is correct that the applications of web scraping cannot be exhausted. With the extent of versatility that this process has, which makes it suitable for a variety of situations, it can equally be applied in the financial industry. Web scraping can be defined as a means of gathering information from the Internet. Copy and paste are also a form of web scraping and it is an automated process.

Meanwhile, while some websites detest automatic scraping, others do not mind. The tremendous amount of data on the Internet can serve any field of personal interest or research. To retrieve the data, you have to up your game and be skilled at web scraping. 

Using Python as a web scraping language

You can use the Python libraries’ requests and Beautiful Soup, which are great tools for the job. On the fundamental stage, your understanding of Python and HTML can help with the process.

You can also consider other advanced options. One of these is the BeautifulSoup, which is a simple and great tool, to execute your web scraping. In case you are interested in scraping at a larger scale, you can use these alternatives:

#1. Scrapy: This is a great python scraping framework

#2. Integrate your code with some public APIs. Retrieving data is more efficient than scraping web pages. If you take a look at Facebook Graph API, you can get hidden data that are not evident on Facebook webpages.

#3. Use a database backend like MySQL. With this, you can store very large data. 

The basic method requires using requests and Beautiful Soup to scrape and parse data from the web. Subsequently, you can walk through the pipeline from the beginning to finish.

Then, you can build a script to harvest job offers from the web and get the information you need in your console. 

APIs as an alternative to Web Scraping

Some websites offer APIs (Application Programming Interfaces) so that you can gain access to the data of the website providers very quickly. APIs afford you an opportunity to avoid parsing HTML. Rather, you will be able to access the data directly with formats like JSON and XML.

HTML is a primary way to present content to users visually. And with an API, you get the process done in a more stable manner instead of gathering the data through the conventional web scraping. The reason being that APIs are designed to be consumed by programs and not for the human eyes. 

Components of a web scraper

Typically, web scraping works like any other Extract-Transform-Load (ETL) process. That is, the process begins with extracting data, followed by transforming the data into a usable structured format, and finally loads it into a file or database. When used with Java, NodeJs and Python, web scraping software can access the World Wide Web with the HTTP (Hypertext Transfer Protocol) or via a web browser.

Even though web scraping can be done manually by a software user, web scraping means an automated process that works with a bot or web crawler.

Even though many services like Scrapestorm Jp, Grepsr, and ScrapingHub offer the same with web scraping, you can also build your own web scraper application with Java, NodeJs and Python. Web scrapers are deployed to automate many scenarios. 

If you are looking for a scraping tool, try our web scraper for free.

Final verdict

Web scraping allows you to do some programs that a human does in a browser and even many more. In fact, the uses are infinite like what you can use with the Internet.

Some of the various uses of web scraping include in search engines, price monitoring, sales and marketing, content aggregators, sales intelligence, SEO monitoring, and data for research, among others. With Wintr, you can do a lot more web scraping functions more effectively, especially with Python as a scraping language.

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