Introduction to Python – A developer perspective

We choose to develop our code base in Python. Most of our applications are built in the backend using Python. There are several advantages for hosting the application in python. Some of them worth mentioning are given below:

1. Learning curve – It is one of the most simple yet powerful language ever developed. The learning curve when compared to Java or C++ is not that steep in Python. In fact, you can learn the syntax in just 3 weeks. You don’t need to be an expert in programming language. But you can become one. Python allows you to express ideas in a much simpler manner. No need of any complex verbosity. Just print statement is enough to print the statement. If you are a Java programmer, you will understand the pain that comes with expressing even a simple idea.
2. Easy to develop/deploy/maintain – It is much easier to develop in Python. It is a dynamically typed language. That gives the greater flexibility to assign variables without worrying about the types. However, it is recommended to follow standard naming procedure. A good programmer must follow them regardless of which programming language they develop. Python is no exception to that. Also, it is easy to deploy in the test/production environment. We use applications developed on top of Python. Some of our applications are extremely scalable and use APIs to serve millions of requests. We have proven solution for scalable applications.
3. Supports lot of ML libraries / Data Analysis projects – The core of ML libraries are built around Python. Some of the libraries worth mentioning are numpy, scipy, sklearn, tensorflow for building machine learning models are developed in Python. Though the backend numerical computing libraries are optimized in C/C++, it is easier to call them from Python. When it comes to Data Analysis, we extensively use Pandas for Slicing/Dicing. This is highly recommended for Exploratory Data Analysis which is very important pre-processing step in selecting right variables.
4. Easy to deploy as Rest APIs – We have scaled up for millions of requests using powerful backend applications. Our architecture are all well built and runs on nginx and wsgi. But the backend code is entirely developed in Python and wrapped in FastAPI/Flask. All these lightweight APIs are highly useful for packaging machine learning libraries for the end user.
5. Maintaining a heck lot of codes especially in the production server – Python is easy to develop and maintain in the production environment. When it comes to maintaining the codebase, we have seen “n” number of issues right from customer escalations. Some of our common problems are API failures, spike in CPU utilization, database session timeouts. Any production environment will be a nightmare to deal, if the technology is even more complex and challenge. But it is as simply as it get to code maintenance in Python. We have quickly resolved the customer issues without facing any further escalations.

We have seen the demand for customer’s preference in Python application. This is lately due to evolution of AI/ML world. All of our customers rightfully engage with us to create end-to-end applications.

Our primary goal has been to enrich customer experience by bringing cutting-edge technologies. In this era of AI and ChatGPT, we are deeply committed to address customer’s problems through technological solution. Python is the right choice to radically transform the business world.

We are proud to say that we are a team of Pythonistas !