Hello, World! No, I am not about to give you a narrative of why you should pick up your biology textbook, right now, and start learning about that bulky snake with triangular-shaped head. Rather, I am about to tell you the merits of learning the programming language that, weirdly, bears the same name as that snake – Python.

Python programming language bears a name that makes it seem like it has something to do with the Python snake. However, interestingly, the name actually refers to a comedy series, not a snake!

Yes, when Guido van Rossum began implementing the programming language – between 1989 and 1990 – he happened to also be reading scripts from the popular BBC Comedy series known as Monty Python’s Flying Circus.

As a result, the name, “Python” was in his subconscious mind. So when he started thinking of a name for his new language, “Python” appealed to him as a perfect name. He was drawn to the name because, according to him, he thought it was “short, unique and slightly mysterious.”

That was how the programming language he developed came to be known as Python. Over the years, Python has successfully carved for itself a niche in the world of programming languages. Today, it is one of the most popular programming languages in the World.

So, if you are thinking of learning Python, you are thinking in the right direction. However, before you finalize your decision to learn Python, consider the three points I have provided below on why you should learn it.

#1 Python’s Syntax is Extremely Simple and Easy to Learn

This is, perhaps, the primary reason for Python’s is popularity today. Python is designed to be extremely simple and readable. Several constructs, that make other high-level languages somewhat cryptic, do not exist in Python.

For example, in many high-level languages, logical operators such as AND, OR, NOT are represented with symbols such as &&, ||, !, respectively. In Python, however, these logical operators are simply represented with explicit keywords: and, or, not, respectively.

Furthermore, the concept of declaring variables with cryptic keywords, such as int, bool, char, var, and so on, is absent in Python. Instead, variables in Python are created by simply assigning values to them just like is natural in algebraic expressions.

Several other features of Python, such as the use of indentation as a nesting structure, the absence of semi-colon as statement terminator, and so on, also contribute to Python’s simple syntax.

It is little wonder, then, that Python is a first choice among beginner programmers. If you are a novice to programming, maybe you should consider learning Python as your first language.

#2 Python Has a Very Large Library

In programming, the term, library, refers to codebase that has been pre-written to enable programmers write complex programs with a few lines of code. Libraries help boost productivity because, with them, programmers can easily write complex applications with minimal effort.

Many programming languages have large libraries. However, there is probably no programming language that has a library larger than Python’s.

Python’s library is so large that Python is one of the few languages that can be described as truly general-purpose.

From django that enables Python to be used for web development, to SciPy and sci-kit-learn for scientific applications, to numpy and pandas for data science, to matplotlib and PyTorch for data visualization, the range of Python’s library seems inexhaustible.

What does this mean to you as a programmer? Well, it means that if you learn Python, the range of applications that you can develop with it will be endless – literally.

Python’s extremely large library has another advantage: it makes it possible for learners of Python to write realistic applications while still learning the fundamentals of the language. This makes the experience of learning Python a satisfying one, as learners are learning the language “in context” rather than “out of context.”

#3 Python is the Data Scientist’s Best Choice

In spite of the fact that Python is general purpose, it has its special niche, namely data science.

Many of Python’s library packages, such as numpy, pandas, SciPy, matplotlib, and so on, are designed and perfectly suited for data science. What’s more, Python’s extremely simple syntax collaborates with these library packages to make it as easy as ABC to use Python to develop complex data science applications.

Furthermore, a wide range of data science applications need to manipulate large data sets known as big data. In such applications efficiency is premium and Python is the superior choice.

This is because Python’s interpreter, and most of Python’s library, is implemented in the highly efficient C language. As a result, data science applications written in Python are far more efficient than those written in other languages.

So, if you want to be a data scientist, Python is just what you need.

Having said all these, should you go ahead and learn Python? Well, it depends on the decision you make. But before you make your decision, check out my other posts in the “Why You Should Learn…” Series so that you can make a more informed decision.