What is Web Scraping?
Imagine you need to extract a huge amount of data from various websites and that too faster. You cannot do it manually by visiting each website and extracting the data. Well, Web Scraping is the solution to this problem. Web Scraping helps you to do this task easier and faster.
Web Scraping, also known as Web Harvesting, Web Data Extraction is a technique that involves various methods to extract the data from across the Internet. Web Scraping is an important part of Machine Learning which is quite trending these days. Web Scraping has become a popular way of collecting the desired information from the websites for Machine Learning Algorithms.
Why is Web Scraping Required?
Web Scraping means to extract a large amount of data from websites. But why are such large data required from websites? Well, there are some applications of Web Scraping that are listed below:
- Comparison of Price
- Gathering Email Addresses
- Research and Development
- Job Listings
Why is Web Scraping in Trend in 2019?
Computers can see and read a lot. The Internet provides access to millions of documents, most of them can be accessed freely without any restrictions. Web scraping helps machine learning algorithms to automatically feed data into their NLP processes and learn new capabilities by recognizing and analyzing the text. Developers have provided a great contribution in creating NLP systems that are capable of understanding textual information better by leveraging the richness of the web.
If you are in search of the best ways to do web scraping, you are in the right place because we can help you with our deep domain knowledge. Finding the best language to work is an important step in Web Scraping tasks.
Latest Trends in IT Sector in 2019
IT is a sector which sees numerous changes every year as the technology changes. IT sector has seen a rapid increase in demand of Data Analytics jobs in 2019 and Web Scraping is an important step of Data Analytics. These skills land you a great job and a successful career.
Which Language Should you Opt for Web Scraping?
People look out for the best programming language for any task, but what they forget is that the best language for any task, be it Web Scraping, is the one you already know and are familiar with. Your prior expertise in a language helps you to find the pre-built resources to support Web Scraping. When you are already having an experience in some language, you learn faster on how to do Web Scraping.
What Features Make a Programming Language The Best For Web Scraping?
Web Scraping involves many steps starting from finding and inspecting the required URL to extract and store the data in the required format. The language you use for Web Scraping should have the following features:
- Ease of Coding
- Flexibility
- Scalability
- Maintainability
- Ability to crawl websites effectively
- Ability to feed the database operation
Which Is The Best Programming Language For Web Scraping?
- C and C++: These are static languages and are not good for scraping because it is better to do web scraping using dynamic languages. Further, it will cost you a huge amount to do web scraping using C++. There is one advantage of using C/C++ that you can parallelize your scrapper in a comparatively easier way.
- JS: It supports distributed crawling and is an effective language for crawling the websites using dynamic coding methods. This language is not recommended for major projects as it has weaker communication stability.
- PHP: It is not easy to write a web crawler program using PHP. Although PHP scraping libraries are good but are the least recommended language for web scraping because it provides minute support to multi-threading. It has many drawbacks as it makes it difficult to do the queuing as well as task scheduling because of its async.
- Python: It is the best programming language to write web scraping programs. It is easy to write crawler programs using this language and can smoothly and easily handle the web crawling operations. It has a large number of libraries such as Numpy, Pandas and so on that provides various methods for the extraction of data and its manipulation.Python makes scraping easy because of its widely used frameworks named Scrapy and Beautiful Soup. It is a dynamic language and there is no need to define data types for variables as variables can be used directly. It saves a lot of time while writing web crawler programs using python as its syntax is easy to write and understand. It is as easy to read as English is, so it becomes easier to identify different blocks in the program. In python, you can do large tasks by writing the smaller codes.
Conclusion
After analyzing the features of different languages, the next step is to choose a programming language and Get Started with web scraping. However, it is also important to follow the best practices of web data extraction and hitting the servers at a perfect time.
