Why Python is the best programming language
Python is one of the most commonly used programming languages today, and with good reason — its syntax makes it one of the easiest to pick up and learn, it’s free to use, and it has many applications in almost every industry you can think of.
Moreover, with the help of Python developer libraries and frameworks like TensorFlow or Django, there are very few software problems that Python can’t solve! So why Python?
Numbers
To start, python can be learned quickly. In only 15 minutes, someone could have it downloaded and writing a Hello World program. Not only does this make it easy to get started, but that also means there is more time for coding with less time spent hunting around for libraries and tutorials.
Number 2 — It’s flexible:
Python was designed from the ground up to be both object-oriented and fast. There are a variety of tools in place that allow you to build anything from simple data analysis programs or scripts all the way up to web services like Google Maps or YouTube.
Lists
In this tutorial, we’ll talk about two important features of Python, lists and tuples. Lists are a very versatile data structure that can store just about any type of data.
Tuples are also a data structure, but they only allow us to store one type of data per list. We’ll look at examples in both cases and see when it makes sense to use each one.
List item #1: apple
List item #2: banana
List item #3: grape
Tuples are made by putting parentheses around what you want to save.
Strings
string1 = I love cookies!
string2 = They are so yummy!
str3 = string1 + string2
print(str3) # Displays I love cookies! They are so yummy! Python’s strings can contain almost any type of text, including numbers, letters, and symbols. The second sentence in this blog post is an example of a string that contains a sentence.
The first sentence in this blog post also has a string: Strings:.
The quotes show that it is a string. You can use single quotes or double quotes to create strings in Python.
Single quotes are good for short strings or one-line strings while double quotes are better for longer or more complex strings with variables and other expressions inside them.
A string can be any length and you do not need to worry about where to put line breaks inside your strings if you want to put one there; python will automatically add them for you as needed when it evaluates your code.
Indentation
One of the first things people notice about Python when they first come across it is that indentation matters. Indentation? What does that mean? It means you have to be consistent in how you indent your code and if you are not, then Python will raise an error, just like every other language.
However, it turns out this single aspect of Python has many benefits. There are actually more reasons than we have time for in this blog post. So what are some other ways indentation can help you as a programmer? Well, one example is something called white space sensitivity.
You might already know what whitespace sensitivity means, but in case you don’t, it basically tells the computer which statements or blocks of code should go together with each other on a line.
The difference between whitespace sensitivity and languages that use braces or parentheses to indicate block starts is that there’s no need for those extra characters with Python (which keeps lines shorter).
And whitespace can also show where each statement begins (rather than using curly brackets).
So these two examples make up two different types of indentation: block and statement. When do you use each type?
Functionalities
Python has a large set of functionality that makes it one of the most useful and versatile programming languages.
It can be used to do anything from create video games, design websites, scrape data, or calculate complex mathematical equations.
With over one million lines of code and more than 5,000 libraries on its site (including libraries for 3D graphics), there is pretty much any tool you could need to get your work done.
It’s versatile enough to even be able to create an environment for visually impaired people using ultrasonic waves.
In order to cover its versatility comprehensively, we will list some use cases in each category:
Verdict
For many, picking a programming language comes down to personal preference. But, the simple truth is that there are many types of programs for solving many different problems. It’s about finding which one fits your needs and sticking with it.
The best way to decide whether or not python will be a good fit for you, is to understand why it has so much popularity in the field of data science.
One thing to keep in mind when picking python for data science: even though it was built for efficiency and simplicity when solving data problems, you don’t have to know much about coding!
What most programmers need to do instead is think through their problem’s data structures, which then translates into code.
