Developers
June 16, 2020

Web Scraping: What It Is and Why Python Is the Language of Choice

Showcasing its versatility, Python is one of the premier languages for scraping websites.
Source: Pixabay

It’s estimated there are 1.6 to 1.9 billion websites as of 2020, although less than 400 million are active. Even more impressive, it’s estimated some 440,000 GB of data is being uploaded to the internet every minute.

Needless to say, the internet is a treasure trove of data, but mining it presents significant challenges. One technique that is commonly used is web scraping.

What Is Web Scraping, What Is It Used For?

Web scraping is the process of extracting, or scraping, large amounts of data from websites. The scraping can be done with an algorithm or program, and automatically saved to a database, spreadsheet or a local file. There are a myriad of reasons why web scraping is used.

One common reason for web scraping is research. With nearly 2 billion websites, the internet contains an enormous amount of data. Even websites that are no longer actively maintained often contain valuable information. Data scientists and researchers will often use such information as the basis of their studies and reports, making web scraping a critical step in the process.

Shopping sites and apps are another popular use for web scraping. Third-party Craigslist apps and websites are a perfect example. By default, Craigslist only allows visitors to search one location at a time, limiting the value that users can gain from the site. Third-party apps and websites, however, will often employ web scraping techniques to present users with Craigslist results from as many regions as they want, including the entire US.

The same is true for other shopping and travel sites. Many third-party services will scrape the data from a number of popular options, presenting them to users in a way that saves them time and effort.

Web Scraping Challenges

One of the biggest challenges in web scraping is the variety of websites in existence. There is infinite variety in website designs, structure, code and information. As a result, a web scraper needs to be built with flexibility and easy updating in mind.

A second challenge is the constantly changing nature of the web. As information is added, website designs updated, new pages uploaded and old pages removed, it can be a challenge consistently scraping information from the site, especially if the scraping is an ongoing effort. Again, powerful libraries and easy-to-update code are critical.

A word of caution is in order, however. Many websites explicitly prohibit web scraping in their terms of service. Others, while tolerating it, prohibit its use for any malicious reason, or in any way that makes the original website look bad. Many websites will even go so far as to permanently block IP addresses routinely associated with web scraping. Therefore, every developer should be sure of what they’re doing before engaging in web scraping.

Why Python Is the Preferred Language

Python was released in 1991, following two years of being a “hobby” of creator Guido van Rossum. Right from the start, Python embraced a philosophy of extensibility. The core language is relatively small and modular, and is augmented by a large library of tools and packages for specific tasks.

Python’s overall approach is best explained in the Zen of Python document:

Beautiful is better than ugly.

Explicit is better than implicit.

Simple is better than complex.

Complex is better than complicated.

Flat is better than nested.

Sparse is better than dense.
Readability counts.

Special cases aren't special enough to break the rules.

Although practicality beats purity.

Errors should never pass silently.

Unless explicitly silenced.

In the face of ambiguity, refuse the temptation to guess.

There should be one-- and preferably only one --obvious way to do it.

Although that way may not be obvious at first unless you're Dutch.

Now is better than never.

Although never is often better than right now.

If the implementation is hard to explain, it's a bad idea.

If the implementation is easy to explain, it may be a good idea.

Namespaces are one honking great idea -- let's do more of those!

Those principles combine to create a language that is ideal for web scraping. First and foremost, Python is relatively easy to learn and work with. It’s dynamically typed, meaning a programmer doesn’t have to predefine every element at the outset.

Third-party libraries, as mentioned, provide a major boost to the language’s role in web scraping. Some of the popular web scraping libraries are Beautiful Soup, Lxml, Mechanical, Requests, Selenium and Urllib2.

Web Scraping With Python: A Match Made In Heaven

Without a doubt, web scraping is a valuable tool for today’s internet. It offers the ability to gather large quantities of disparate information for research, information gathering, shopping and much more.

Python has clearly established itself as the language of choice—and for good reason. It offers ease-of-use, dynamic coding and some of the most powerful libraries available to assist in scraping.

TagsWeb ScrapingPython
Matt Milano
Technical Writer
Matt is a tech journalist and writer with a background in web and software development.

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DevelopersJune 16, 2020
Web Scraping: What It Is and Why Python Is the Language of Choice
Showcasing its versatility, Python is one of the premier languages for scraping websites.

It’s estimated there are 1.6 to 1.9 billion websites as of 2020, although less than 400 million are active. Even more impressive, it’s estimated some 440,000 GB of data is being uploaded to the internet every minute.

Needless to say, the internet is a treasure trove of data, but mining it presents significant challenges. One technique that is commonly used is web scraping.

What Is Web Scraping, What Is It Used For?

Web scraping is the process of extracting, or scraping, large amounts of data from websites. The scraping can be done with an algorithm or program, and automatically saved to a database, spreadsheet or a local file. There are a myriad of reasons why web scraping is used.

One common reason for web scraping is research. With nearly 2 billion websites, the internet contains an enormous amount of data. Even websites that are no longer actively maintained often contain valuable information. Data scientists and researchers will often use such information as the basis of their studies and reports, making web scraping a critical step in the process.

Shopping sites and apps are another popular use for web scraping. Third-party Craigslist apps and websites are a perfect example. By default, Craigslist only allows visitors to search one location at a time, limiting the value that users can gain from the site. Third-party apps and websites, however, will often employ web scraping techniques to present users with Craigslist results from as many regions as they want, including the entire US.

The same is true for other shopping and travel sites. Many third-party services will scrape the data from a number of popular options, presenting them to users in a way that saves them time and effort.

Web Scraping Challenges

One of the biggest challenges in web scraping is the variety of websites in existence. There is infinite variety in website designs, structure, code and information. As a result, a web scraper needs to be built with flexibility and easy updating in mind.

A second challenge is the constantly changing nature of the web. As information is added, website designs updated, new pages uploaded and old pages removed, it can be a challenge consistently scraping information from the site, especially if the scraping is an ongoing effort. Again, powerful libraries and easy-to-update code are critical.

A word of caution is in order, however. Many websites explicitly prohibit web scraping in their terms of service. Others, while tolerating it, prohibit its use for any malicious reason, or in any way that makes the original website look bad. Many websites will even go so far as to permanently block IP addresses routinely associated with web scraping. Therefore, every developer should be sure of what they’re doing before engaging in web scraping.

Why Python Is the Preferred Language

Python was released in 1991, following two years of being a “hobby” of creator Guido van Rossum. Right from the start, Python embraced a philosophy of extensibility. The core language is relatively small and modular, and is augmented by a large library of tools and packages for specific tasks.

Python’s overall approach is best explained in the Zen of Python document:

Beautiful is better than ugly.

Explicit is better than implicit.

Simple is better than complex.

Complex is better than complicated.

Flat is better than nested.

Sparse is better than dense.
Readability counts.

Special cases aren't special enough to break the rules.

Although practicality beats purity.

Errors should never pass silently.

Unless explicitly silenced.

In the face of ambiguity, refuse the temptation to guess.

There should be one-- and preferably only one --obvious way to do it.

Although that way may not be obvious at first unless you're Dutch.

Now is better than never.

Although never is often better than right now.

If the implementation is hard to explain, it's a bad idea.

If the implementation is easy to explain, it may be a good idea.

Namespaces are one honking great idea -- let's do more of those!

Those principles combine to create a language that is ideal for web scraping. First and foremost, Python is relatively easy to learn and work with. It’s dynamically typed, meaning a programmer doesn’t have to predefine every element at the outset.

Third-party libraries, as mentioned, provide a major boost to the language’s role in web scraping. Some of the popular web scraping libraries are Beautiful Soup, Lxml, Mechanical, Requests, Selenium and Urllib2.

Web Scraping With Python: A Match Made In Heaven

Without a doubt, web scraping is a valuable tool for today’s internet. It offers the ability to gather large quantities of disparate information for research, information gathering, shopping and much more.

Python has clearly established itself as the language of choice—and for good reason. It offers ease-of-use, dynamic coding and some of the most powerful libraries available to assist in scraping.

Web Scraping
Python
About the author
Matt Milano -Technical Writer
Matt is a tech journalist and writer with a background in web and software development.

Related Articles