Programming languages are in plenty, and there is no shortage of options in the industry. But there are some languages that have held their ground firmly and continue to grow. Python, Java, JavaScript, Go, and PHP are some of these languages. With every new release of these languages, their user base increases, and more products are developed using these languages. While all these languages are old, it does not hinder their growth. Even today, there are millions of applications that are built on these technologies, and they are working fantastically across all conditions.
In today’s article, we will uncover everything about Python, its areas of application, and the reason to use Python over other programming languages. This is going to be an exciting topic to go through, so first, let’s get to know about Python.
Introduction to Python
Python is a high-level, general-purpose language developed by Guido Van Rossum and later open-sourced. It was developed and released in 1991, and it is a surprise to many when they know that this language is older than the highly popular Java language. Python has multiple features, and it has found its shot to fame with increased demand for AI, ML, Data Science, and Automation.
Python is primarily known for its easy-to-understand syntax and readability. Writing code in Python is similar to writing an algorithm to explain things in plain English. Its adoption is increasing rapidly, and today Python is used by large corporations and small companies alike. In the next section, we will find out some key reasons why Python is used heavily.
Reasons to Use Python Over Other Programming Languages
-
Simplicity
Python is such a simple language that anyone can understand it. If you know the basics of computer science and programming, you can understand the language pretty easily, even if you haven’t learned it yet.
Readability and simplicity were the core focus of Python’s inventors, and they’ve done a fantastic job on that. Natural keywords and commands that do just what you’d expect them to do based on their meaning make Python a relatively simple choice. It can be picked up and used anytime, anywhere, because of this simplicity only.
Moreover, there is documentation on the best practices of Python, and every Python developer follows it closely. So, no matter where you see the code, the zen of Python will be there, and it will keep the code simple for you.
-
Easy to Learn
No other backend language is as easy to learn as Python. It has many different things, but the basics are pretty easy to grab. Even if you don’t have any programming background, you can go through the documentation and understand things yourself.
It follows a simple syntax and does not haunt you with bracket errors. This makes the code clutter-free, and you just have to keep the indentation well to make the code run. Python scripts may be produced and perform significantly faster than other programming languages because they are straightforward to learn and use. Any amateur or expert can learn Python basics in a week and move ahead to implement their requirements.
-
Large Community
Python has been in the market since 1991, and it is more than 3 decades now. It is natural that a language this old will have a great community. Python has the best and most helpful community in programming languages. Everyone seems to be a contributor and helper to each other.
The community puts in efforts to increase the adoption of this language by developing guides, documentation, tutorials, and tips and trick videos to help each other. There is something for every user when it comes to community offerings in Python.
It is among the highest-ranked open-source projects, and the large community keeps on expanding the features to make the language more relevant to all its use cases.
-
Tons of Libraries
Python has created a massive collection of open-source libraries by having a large community behind it. All these libraries are built by corporations, individual contributors, and research teams that spend their time building the libraries and keeping them open-sourced. Python’s pip package manager and PyPI repository work together to bring the libraries to end users. Due to this, implementation of almost everything becomes easy with Python.
-
Object Oriented Language
Python is an object-oriented programming language, and that is another reason for businesses to use Python. It provides all features like polymorphism, inheritance, encapsulation, and abstraction that help you provide safer and better apps.
Being object-oriented, you can create classes and methods in Python. Once those are created, you can create multiple object instances of the class and call different methods defined in the class. This promotes code reusability and makes your code modular which in turn makes maintenance and development easier.
-
Interpreted
Every developer knows that interpreted languages run faster than compiled languages. This happens because compiled languages need to be compiled before they run, and interpreted languages run line by line and don’t need any compilation.
Moreover, interpreted languages are free from compile-time errors, so you can be sure that the code will run every time you press the run button. But you can face runtime errors when the code reaches a certain line. That, in turn, makes debugging easier and faster as you know where the error exactly resides in the code file.
Having known about the reasons to use Python, you might be excited to look at the different application areas of this excellent technology. So let’s explore them.
Application of Python In Different Areas
Backend Development
Python is heavily used in backend microservices and APIs by web app and mobile app development companies. With popular frameworks like Django and Flask, it can do almost everything in the backend with a breeze. While Django is an extensive framework with tons of different features, Flask is based on simplicity and provides enough features to develop and deploy apps.
Django provides an admin side pre-built in the framework, so you don’t have to write much code for admin activities, and you can easily focus on other sides. There are many other frameworks in Python for backend development, and all have one thing in common, which is usability and easy implementation.
Python offers significant performance too, so there are no performance constraints at any workload. This is why it is preferred in the development of APIs and backend services.
Data Science
One of the primary things where Python is used is Data Science. This domain involves lesser coding, and performance speed is not a constraint most times. But the people who become data scientists are often looking for easy-to-implement languages. Due to this one demand, Python has become the de-facto standard in data science projects.
Python has tons of libraries like Numpy, Pandas, Seaborn, Matplotlib, Scikit-learn, etc, that help in data science tasks, and these are just a few prominent ones. There are thousands of other libraries, and a data science workflow in Python is majorly comprised of different libraries and their implementations. Whether it is about data analysis, model building, validation, or gathering data and cleaning it, Python is used at scale in all processes.
The community often comes up with better and more effective libraries and code snippets for data science, and this keeps Python at the forefront.
Machine Learning & AI
Machine learning and AI are hot topics right now. Every company wants to use these two technologies to improve their business and get a competitive edge over others. Python is a language that is preferred in machine learning and AI projects. Developing prediction, classification, and clustering models with Python is effortless, and everything is available as a library, so you just have to put the puzzle pieces together and fine-tune the models to get the best results.
Every AI library is available in Python, and it is updated regularly with newer research. So using Python is the wise choice for companies who are looking to stay ahead of their competitors.
On the other hand, AI applications like sentiment analysis, natural language processing, etc., are done best with Python, as writing code for such things is easier.
DevOps
Infrastructure as Code, CI, and CD pipelines rely heavily on Python. Python has SDKs from all major cloud providers, so many businesses use Python for cloud computing tasks, as implementation is relatively easier. With Python, you can create DevOps pipelines easily and scale them to unbelievable levels without many changes.
Web Scraping & Automation Testing
Web scraping is a field where businesses and individuals use Python to gather openly available data. This is possible because of the powerful requests module and HTML parsers available in the language. These things make scraping large websites and finding relevant data effortless.
Automation testing he lps save tons of time, and Python leads here too. Python has multiple automation testing libraries that are used to test applications without any human intervention. Such testing ensures that no errors are left unseen due to human errors, and a lot of time is saved.
After knowing all these reasons and the application areas of Python, I am sure that you will be eager to try out this language. So hire python developer for your business and start using this language to the maximum limits today.
