Python Applications 2020: Features, Advantages, Types, Scope

Python for app development was introduced in 1991 as a high-level programming language, based on the interpreter, for creating general-purpose dynamic applications focused on code readability. It is comparable to Java/C++, is object-oriented, has multiple programming paradigms, and is convenient for large organizations. It features a comprehensive standard library with automated memory management and dynamic features that are further helpful in software development, web development, system scripting, and mathematics. Some of the best examples of Python-based applications are YouTube, Bit Torrent, DropBox, YouTube, Amazon, Google, Facebook, IBM, NASA and Netflix.

Features and Advantages: What Does Python Offer?

  • Interpreter: It is executable on the interpreter system, which produces a .exe that can be instantly run.
  • Easy Syntax: Syntax is as easy as the English language.
  • Functions vs. Procedural: Python can be used functionally or procedurally.
  • Less Coding Required: The program only requires a few lines of code.
  • Frameworks: Python offers frameworks like Django and Pyramid.
  • Micro-Frameworks: It also offers micro-frameworks such as Flask and Bottle.
  • Third-Party Modules: Python Package Index lists many third-party modules.
  • Content Management System: It comes with Enterprise CMS like Plone and Django content management system.
  • Standard Library: Python’s standard library does support quite a few Internet protocols: HTML, XML, JSON, E-mail processing, ETP, IMAP and other Internet protocols.
  • Socket Interfaces: Python comes with easy-to-use socket interfaces.
  • Libraries: Python package index has yet more libraries like ‘Requests’ – a powerful HTTP client library, ‘Beautiful Soup’ – an HTML parser capable of handling all sorts of oddball HTML, ‘Feedparser’ – for parsing RSS/Atom feeds, ‘Paramiko’ – to implement the SSH2 protocol, ‘Twisted Python’ – a framework to allow asynchronous network programming.
  • Science and Math Applications: Python is also used to develop scientific and mathematical applications. For this, it comes with ‘SciPy’ which is a collection of packages for mathematics, science and engineering; It has ‘Pandas’ as data analysis and modelling library; IPython is an interactive shell with easy editing and recording of a work session, supporting all kinds of visualizations and parallel computing.
  • Libraries: Python also combines some ‘Tk’ GUI libraries in its binary distributions.
  • Toolkit: It has some toolkit that is usable on certain platforms like wxWidgets, Kivy, Qt via pyqt or PySide.
  • Platform Specific Tools: Python also contains certain platform-specific tools like GTK+, Microsoft Foundation Classes through the win32 extensions.
  • Software Development: Python makes use of SCons for build control, Buildbot and Apache Gump for automated continuous compilation and testing, Roundup for bug tracking and project management.

Types: Build Applications In Python

Applications that use Python include Web Development, Game Development, Machine Learning and Artificial Intelligence, Data Science and Data Visualization, Desktop GUI, Web Scraping Applications, Business Applications, Audio and Video Applications, CAD Applications, Calculators, To-Do apps and Embedded Applications etc. 8 specific application types that can be built by Python are discussed here:

  1. Cross-Platform App Development: Python can be used to develop applications across Mac, Linux, Windows, Raspberry Pi and more.
  1. ERP/e-commerce Apps: Python can as well be used to develop ERP and e-commerce system applications. E.g: Odoo, Tryton etc.
  1. Quick Web Apps: Python can be used to develop quick web applications as it has frameworks (Django, Flask, Pyramid) and several libraries that can help integrate protocols such as HTTPS, FTP, SSL that can help in processing JSON, XML, E-Mail and much more.
  1. Create Gaming Apps: Python can be used to create interactive games due to the presence of libraries like PySoy which is a 3D game engine supporting Python 3. It also supports PyGame which provides functionality and library game development.
  1. Machine Learning/Artificial Intelligence: Python can be used to create machine learning and artificial intelligence applications due to the presence of libraries such as Pandas, Scikit-Learn, NumPy etc.
  1. Data Science: Python can be used to create applications to perform serious data interpretations, operations and extractions with the presence of libraries such as Pandas, NumPy etc.
  1. Graphs Based Apps: Libraries such as Matplotlib, Seaborn can be used to create complex graph-based applications.
  1. Desktop GUI: Python can be used to program desktop applications with the help of the Tkinter library that can be used to create user interfaces. Additionally, the availability of toolkits like wxWidgets, Kivy, PYQT can be used to create applications on several platforms.
  1. Web Scrapping Applications: Python is capable of extracting a large amount of data from the websites and uses it across to create real-world processes like price comparison, research and development and job listings etc.

Scope: Why Should We Prefer Python App Development?

Developers can integrate Python with any available technologies. It is a modular programming approach and the community is vast. It is popular, simple, and efficient. Python can be used for testing complex applications, web scraping, data analysis, machine learning, computer graphics, and the Internet of Things etc. It is convenient to code with the presence of multiple frameworks, has lots of templates, and creates rules to adapt a universal language to a particular task. Contact us for more details on how to make an app with python.

About Author

Neeti Kotia

Neeti Kotia

Neeti got her master’s degree in software engineering in 2009 and has been working since for software companies of all sizes as a technical writer. What started as a high school passion has now been converted into a serious profession. She has a special knack of learning from all verticals and imbibing the extracts into her writing. She enjoys learning technical aspects of writing from her tasks where her experience and understanding are most impactful.

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