Semalt Expert: Data Scraping – 4 Amazing Python Applications

Data scraping, also known as data extraction and web scraping, is the technique of extracting data from websites. Every site hosts information in the form of HTML or some static texts. If you want to scrape these texts properly, you have to use a data scraping tool. Scrapy, for instance, is a Python-based data extraction software that scrapes information from various sites and converts the unstructured data to the structured form. On the other hand, BeautifulSoup is the Python library that is designed for different web scraping and data mining projects. Both Scrapy and BeautifulSoup automatically convert the unorganized data into an organized form and give you readable and scalable information instantly.

An overview of Python:

Python is a general-purpose programming language. The idea of Python originated in 1989 when Guido van Rossum was confronted by the shortcomings of the ABC language. He started developing a new programming language that could scrape data from dynamic and complicated sites. Today, Python has different implementations such as Jython, IronPython and the PyPy version.

Programmers and web developers prefer Python due to its versatile features and easy-to-learn programming codes. Some of the most amazing applications of Python have been discussed below.

1. Presence of the Third Party Modules:

BeautifulSoup and Python Package Index (PyPI) contain various third-party modules that are used to scrape data from a large number of sites. One of the major benefits of Python is that you can develop a large number of tools easily and conveniently.

2. An extensive range of libraries:

You can get benefited from the different Python libraries and scrape as many web pages as you want. For instance, Scrapy makes it easy for you to scrape data in real-time. First of all, this tool will navigate through different sites and collect useful information for you. In the next step, this Python-based tool will scrape data as per your requirements. Various high-profile data extraction tasks can be accomplished with Python and its libraries.

3. An open-source language:

Python was developed under the OSI-approved open source license. This language is suitable for programmers, coders, developers, and enterprises. The development of Python is driven by the community which collaborates for its codes through the mailing lists and hosting conferences.

4. Python as a productive language:

Python has an extensive range of frameworks, libraries, and software to choose from. It helps increase a programmer's productivity while interacting with JavaScript, Perl, VB, C, C++, and C#. You can use Python to scrape data from HTML files, PDF documents, images, audio and video files.

Conclusion:

As compared to JDBC and ODBC, Python's database is found to be bit underdeveloped and primitive. That is why this language is suitable for beginners and webmasters only. If you want to use Python to handle complex sites, it may not be the right language for you. Instead, you can opt for PHP or C++ and scrape data from complex sites easily. It's true that Python has an object-oriented design, but PHP and C++ are far better than this language because you don't need to learn too many codes.