Data is a crucial business asset in the modern world. You can use data to show companies where they currently stand in the market, how their processes work, their actual results in the field, what customers think of them, how they compare against competitors, etc.
It’s impossible to make the right business decisions without having the necessary data to get a complete overview of all the key factors involved. However, companies don’t have the resources to gather such a large amount of data and must focus on their core business operations.
Luckily, new solutions called web scrapers can help you do this in an automated fashion. There are several things to consider when choosing or building a scraping bot, and a big one is coding languages.
Web Scraping Defined
Source: cloudfront.net
Web scraping is the process of gathering publicly available data online in an automated fashion using scraping bots. These tools collect and store data in a structured manner so it’s ready for future use.
Companies can get scraping as a service from third parties that already have an established process. On the other hand, they can also build bots for specific needs. Both options can work well, depending on your current resources and organizational needs.
Data scraping has many business uses, and there are no limits to accessing public data. Some of the most common uses are:
- Market Research
- Business intelligence
- Price scraping
- Competitive research
- Customer review scraping
Benefits of Web Scraping
Source: itchronicles.com
At its core, data scraping is a straightforward process. You download online information directly into your computer, right? It sounds really simple, but this process has many obstacles and can’t be done manually.
Here are the advantages scraping offers.
Gather Large Volumes of Data Quickly
Scraping tools guarantee speed and accuracy. Instead of downloading and looking for information manually, you can simply set up your software and let it do its magic. Scrapers work much faster than humans and perform millions of repetitive tasks in just a minute without making any mistakes.
Avoid Online Blocks
Even though scraping is completely legal many websites don’t want organizations downloading their content. They use all kinds of encryptions, track website activity, employ user-agent detection, set honeypot traps, and so on. Web crawlers can bypass these systems and geo-blocks by rotating IPs, rotating user agents, using headless browsers, and connecting to the web via proxy servers.
Scraping is Cost-Efficient
Building a web scraper from scratch requires knowledge and financial resources. Instead, using a scraping service you pay a subscription for lets even smaller organizations tap into rich data. At the same time, the more you use a specific scraper, the lower your prices will be.
Wider Data Access
Gathering data is challenging, but you must find valuable data you can use to get the right insights. The internet is a big place, and it takes a lot of time to do this. Scrapers have all kinds of filtering systems and customizations that allow them to find relevant data quickly and discover new sources of information.
Scalable Process
Regardless of your data needs, data scrapers can take care of them. You only pay for the data you’ve requested and nothing else. That makes scraping super-affordable, and even small organizations can use valuable data to drive their numbers up.
Most Popular Languages for Web Scraping
Choosing the right coding language is crucial for developing a web scraper and affects its strengths and weaknesses. Even if you are looking for a third-party scraping service, you should learn what language the platform is built on.
Python
Source: ctfassets.net
Python is the most popular coding language for scrapers. Its general-purpose language makes it easy to create solutions for scraping sites, crawling data, targeting, and setting up the right mechanisms to help avoid detections and blocks.
Node.JS
Source: itprotoday.com
This open-source cross-platform lets developers use JavaScript for making server-side scripts. This functionality makes it ideal for scraping JavaScript content. Node.JS is excellent for sites with dynamic structures but lacks communication capabilities for large-scale scraping.
Ruby
Source: code-mentor.org
Ruby language has a simple syntax that lets users develop scrapers efficiently. Imperative and functional programming combined with a large community makes it perfect for beginners looking to create scraping tools.
Also Read: Key Differences Between C and C++ : The Widely Used Coding Languages
What Is a Python Requests Library, and How Does It Work
Source: medium.com
Python is the number one option for many reasons, the main one being the wide choice of libraries designed to give easier and more accurate access to web pages. The Python Requests library is an HTTP library that offers many simple functionalities.
It has simple commands that let you download content from a page. However, it can also post to forms and access various APPs. It can work with international URLs and domains with proper authentication and allows HTTPS proxy usage.
Conclusion
We hope this post has helped you understand the role of coding languages and helped you get interested in Python. Sometimes the most obvious answer is the best, and that’s the case of using Python for scraping.
