7 Reasons You Should Use Python Programming Language

7 Reasons You Should Use Python Programming Language

Python has been around in the IT programming spectrum since forty years and more. The language was created by developer named Guido Van Rossum in year 1991. Going by the statistics, the TIOBE programming community index lists Python as one of the top 10 programming languages of today. The stack overflow survey also shows that Python has taken over languages such as Java, C, C++ making its way to the top! From less popular to most popular, it has seen all lights of the day. With many programming language existing today, it has slowly gained a pace and achieved popularity over recent years. Python is a high level programming language which can be used for development of Graphical User Interface (GUI) applications, websites and web applications. However, additionally, it is also widely used for scientific applications which are traditionally dominated by languages like R, MATLAB, Stata, Sas and other commercial environments. Except for android application development, there is no battle which Python cannot fight and succeed! It is essential to understand the reasons behind this popularity.

We can keep writing unlimited blogs over the popularity of this language over other languages, however, it is necessary to be specific and crisp about the reason behind choosing Python as the language to marry with! As traditionally we believe in 7 ‘pheras’ for Indian weddings, for this marriage to happen, we are listing down 7 ‘reasons’ for choosing Python,

  1. Great for novice programmers
  2. Great Community Support
  3. Simplified Development
  4. Scientific Computing
  5. Great Compatibility
  6. Multiple Programming Paradigms
  7. Great Future

Let us see these reasons in detail,

1. Great for Novice Programmers:

Python as a programming language is extremely simple and easy to learn. Even for those who are not from the computing background or do not hold an engineering degree can still enjoy the flavour of development with Python at hand. Though it is a high level programming language, it is very powerful as it resembles English – a language which is universally dominant! The developer Guido Van Rossum who invented Python was learning a programming language called ABC which was specifically built for teaching. Later on he invented Python version 0.9.1 in 1991. Guido went ahead and also worked on a project called ‘Computer Programming for Everyone’ with a view of using Python as a way to develop curriculum intended to develop basic programming skills to people of all ages and backgrounds. For the same reason, many school kids are learning and programming in Python as enthusiasts. Python is a core part of a lot of beginner focused teaching projects consisting of microchips that have been given out to school children. Same language can be used by a teenager enthusiast to build hardware projects, by an IT employee to script and automate things or to build complex systems! Simplicity of python is inversely proportional to its capabilities as a programming language. More about coding simplicity is covered in pt no. 3.

2. Great Community Support:

Python simplicity is also directly related to the great developer community behind the language. It is an open source language with robust and standard libraries. This also helps to curtail the overall software development cost and saves time too. There are several Python frameworks, libraries and development tools. The developer can choose from a pool of frameworks and tools as per their precise needs. For e.g. for web application projects, we can use Python web frameworks like Flask, Django, Bottle etc. Similarly one can use GUI frameworks and tools like PyJs, PyGUI, Kivy etc. to accelerate the development of desktop GUI applications. Various ways to get Python community support is through online forums, mailing list, user contributed code documentation, stackoverflow etc. Due to its community support, it is also becoming popular among graduation and post graduation students for their project implementations.

  1. Simplified Development:

It is important to introduce the right programming language to a novice learner so that he is encouraged and motivated to adopt a career in programming if he wishes to do so. However, today’s popular programming languages like C, C++ and JAVA are too verbose as well as complicated with notational overhead. The abstract concept in these languages is difficult for most programmers to grasp, understand and implement.

One requires a core understanding of all basics of programming in order to use these languages. Syntax of Python language is more intuitive and clean. The language is also dynamically typed making it easy for a programmer to focus more on problem solving. The language is also known to be very expressive with data types like list, dictionary and tuple which can be learnt in parallel with primitive data types. The language nullifies the use of semicolons and extra brackets and introduces indentation resembling a pseudocode. A simple code for addition of 3 variables, if compared in C++ and Python as in snippet below, clearly shows how easy it is to code in Python language.

4. Scientific Computing:

Python is proving to be a great solution for scientific computing. It is extensively being used by data scientists for machine learning, data analysis and data visualization. The Python Package Index has more than 2 lakhs ready to use libraries, modules and scripts which can be readily used by the developers. It includes libraries for operating system interfaces, protocols, web service tools, machine learning, natural language processing, string operations, internet etc. While artificial intelligence is taking a world for a drive, python libraries like Keras and Tensorflow are at rescue of the developers giving them the ability to implement their functionalities without explicit programming. Libraries like OpenCV helps in image recognition and computer vision. The Tkinter library in Python is an easy way to develop GUI applications. It is also extensively used in game development. pandas is another library which is used for scientific computing. The name of this library is derived from two words i.e. panel data which is used for 3D data sets encountered in econometrics and statistics. The scikit libraries in Python are specifically used for statistical analysis and machine learning. Hence the python community is all over when it comes to the booming area of scientific computing!

5. Great Compatibility:

Python supports multiple operating systems. It is known as a cross platform language and can run on Windows, Linux, MacOS all at a time. For languages like C, C++ and JAVA, separate compilation steps are essential to convert the program into deployable format. Being an interpreted programming language, python can directly run the program from source code. Python internally converts in code into bytecode format which is further translated into native language of the computer. This eliminates the need of linking and loading the libraries explicitly. Python allows the user to run a piece of code on multiple platforms without the need of recompilation. Any alterations made to the code do not make it necessary to recompile it. This also reduces the development time to greater extent. The Python code can be embedded in C or C++ program to provide the user with a capability of executing a script. This adds to additional compatibility of Python with other languages.

6. Object Oriented and more:

Python, not only gives tough competition to C++ and JAVA due to its object oriented feature; however, it also supports many other programming paradigms. It charms the user the same way a snake charmer charms a snake. It does not compel a user to program in a particular manner. Rather it has a great ability to conform to the coding style of the developer. As per the category of the developer – beginner or advanced, the language let them choose their style as per the problem they wish to solve.

In addition to the object oriented paradigm, python supports 3 additional programming paradigms – imperative, functional and procedural. Python ensures that all these 4 programming paradigms are available to the developer and are working for them. For e.g. Machine learning uses imperative paradigm, deep learning can be well performed in a functional manner, data manipulation can be either functional or object oriented. This support of python for multiple programming paradigm acts as an important factor behind its popularity.

7. Great Future:

If you are a programmer and if you choose Python, your career will grow along with it every day! The jobs and careers are at boom when you work on python. Data Scientists widely use Python for their work. Domains like machine learning also use Python. Data Scientists and machine learning developers are highly paid for their jobs. The average salary of a Python Developer in the United States is approximately $117,000 per year. Python has been managing to be at the popularity spike for a year and more.

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