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A Brief Introduction to Web Scraping

 The internet we know and love is structured around efficient exchange and storage of information. It is an underappreciated contributor to the incredible acceleration of technological improvement that the world experienced in the last 50 years. With the power to connect people all around the globe, it creates the perfect circumstances for the exchange of information that brings the accumulated knowledge together, used by the brightest minds to create revolutionary inventions, products, and software.

Web Scraping

The web infuses our basic necessities with efficiency and convenience. Companies and business-minded individuals use the internet to grow, promote and manage their profitable activities. Casual users indulge in the entertainment and social networks on the web to communicate with others and spend quality time. The internet is informative, addictive, efficient, and so much more.

Everything we enjoy comes from the manipulation of information technologies. Today, the web has so much public data that one user could never go through and memorize the available knowledge in multiple lifetimes. Still, the web has tons of valuable snippets of information and it only keeps growing. Just as we use technological assistance to build these digital structures, businesses, and private individuals have to use automated tools to get the most benefits from available information.

In this article, we want to give our readers a brief introduction to web scraping - the automated data extraction process that allows us to open and extract public data contained in websites on the web. Programmers can write code for basic web scrapers with little programming knowledge. We will discuss the benefits of automated data extraction for both businesses and private individuals, as well as address coding languages used for web scraping. We will also address no code scraping, where you can achieve a sufficient or even a better result with sophisticated pre-built tools. To learn more about them,check out informative blogs provided by Smartproxy - a business-oriented proxy provider that works with companies that use web scraping to safely extract information with no code scraping. For now, let's gloss over web scraping and its applications.

How web scraping works

In essence, web scrapers are simple automated bots that extract the HTML code from targeted websites. However, when data scientists talk about scraping, a large portion of the process is often omitted. The extraction of the code is simple, but the code itself has little value for analysis.

Web scraping is followed by parsing which completes the process of extraction by restructuring HTML code into a readable and understandable format, similar to the content presented on the web. With the right tools, multiple web scrapers, and parsers, companies and private individuals can rapidly collect and store valuable knowledge from multiple targets at the same time, much faster than an average user ever could.

Why do businesses depend on web scraping?

Web scraping has immense applicability in the modern business environment, so let's discuss the most beneficial reasons companies depend on information extraction.

Retailers and other businesses with online shops often have to compete with other companies selling and advertising similar products and services. The battle between competitors boils down to superior knowledge. Companies that extract information from other players on the market can recognize their strengths and weaknesses to make adjustments that will help outperform them. The most sensitive subject is price sensitivity. Businesses that track the prices of similar products sold by their competitors can keep adjusting their own pricing to undercut them and present a better deal. Web scraping helps us get access to these priceless snippets of public data as fast as possible.

Another big one is the conduct of research for digital marketing campaigns. Information technologies create far greater circumstances for targeted advertisement. Unlike TV or radio, the web is full of digital spaces that can be filled with ads. Companies can scrape social media networks to find respectable influencers that create valuable content but need financial aid to fuel their passion. Growing your brand through these public individuals will help you reach a potential client base that is more likely to be interested in your products and transform them into loyal customers.

Programming languages for web scraping

The first and most obvious choice is Python - the most popular programming language that is relatively easy to understand and has many applications in data science. You can use the standard urllib library to open, read and save the HTML code of targeted websites. Python has a large community of enthusiasts that create external libraries that greatly enhance the applicability of the language and the simplicity of its use. Scrapy and Beautiful soup are powerful open-source frameworks that can be easily installed to assist users in their web scraping tasks.

You can also use Node.js - a runtime environment that helps programmers run JavaScript outside their browsers. It is a great choice for small to moderate scraping projects but rarely used for large data extraction tasks.

Coders that are proficient in C and C++ can also use familiar languages to build basic scrapers for personal projects, but their functionality will remain limited when compared to Python.

Other options worth looking into are PHP and Ruby, but Python and the abundance of open-source frameworks make it the best choice for web scraping. However, if you have enough resources to avoid these steps or want to save time, you can outsource your web scraping tasks to experienced data scientists or use pre-built scrapers for quick and easy access to desired public data.

Understanding the basics of web scraping should help you better grasp the value of information on the internet and the tools used for its manipulation. We encourage you to use this knowledge to dive deeper into the world of information aggregation and data science!

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