Python: Stellar advantages and why you should consider it

Did you know that Python is one of the most commonly used programming languages today? 

Most Popular Software Development Technologies
Source: Stack Overflow Developers Survey

On average, the number of languages for programming exceeds 700. Released in the nineties, Python is one of the oldest ones. Yet, today it is winning increasingly wider acceptance. So what makes Python stand out? Python has become one of the most popular programming languages in the world due to its ease of use, power, and versatility.

Let's delve deeper and consider the whys and the hows that make Python a fantastic option for your business idea. First, we'll explore why Python is a good choice for businesses and look at some things that Python can be used for. We'll also take a look at the companies that have already adopted it.


Stellar advantages

In recent years Python experienced a great boost in popularity due to the easy learning curve, speedy web development and AI utilisation. At the present time it is edging ahead of its competitors. 

Python is a general-purpose programming language being used broadly by the AI and scientific communities.

Python is one of the best languages for writing readable and well structured code due to strict indentation and lean syntax.

Speed of Development
Python’s Django framework comes with many reusable components and out-of-the-box architecture solutions. Together with tools like DRF, Django-admin, Swagger and many others it allows for an outstanding development speed. Also it has excellent documentation.

Python has a phenomenal community. Its community offers a variety of resources, such as code libraries containing chunks of pre-written code that you can easily integrate into your project. It helps accelerate development and explains why Python is so immensely popular.

Learning Curve
Python is one of the easiest languages to learn due to the readable code and lean syntax.

AI and Data Science
Python is an undisputed winner in any AI and Data Science related tasks.
Its libraries rooted for specific data science jobs makes it a perfect fit.

Libraries like NumPy, SciPy, and pandas make data cleaning, data analysis, data visualisation, and machine learning tasks easier. Some of the most popular libraries include:

  • NumPy: NumPy is a Python library that supports many mathematical tasks on large, multi-dimensional arrays and matrices.
  • Pandas: The Pandas library is one of the most popular and easy-to-use libraries. It allows for easy manipulation of tabular data for data cleaning and analysis.
  • Matplotlib: This library provides simple ways to create static or interactive boxplots, scatterplots, line graphs, and bar charts. It helps simplify your data visualisation tasks.
  • Scipy: Scipy is a library used for scientific computing that helps with linear algebra, optimization, and statistical tasks.

Big Data
Big Data is most closely associated with Python among various implementation spheres. For example, many data processing workloads in organisations are powered by Python only. Furthermore, most of the research and development takes place in Python due to its many applications, including ease of analysing and organising usable data.

Python supports a threading library but it suffers from limitations due to the
Global Interpreter Lock and therefore it is not a top choice for multi-threading applications.

Even though Python is an interpreted language, it is considered to have decent performance because of the bytecode.


What is Python good for?

  • Web development

  • Data Science

  • AI & ML applications

  • Automation scripting


Top apps built with Python

There are hundreds of companies using Python for app development in multiple industries. Here is an overview of the different kinds of applications developed with Python. Some of these names may include your long-term favourites.


Python is one of Google's true server-side programming languages, alongside C++, Java, and Go. Peter Norvig, the head of the examination at Google and previous overseer of search quality, keeps up with that, "Python has been a significant component of Google from the start and remains so as the technology develops and advances." 


The music streaming company is an immense defender of Python, utilising the language for data examination and back-end services. The services are written in Python because Spotify likes how quick the improvement pipeline is while composing and coding in Python. 


Netflix implements Python very much like Spotify, depending on the language to control its data analysis on the server side. It doesn't stop there, nonetheless. Netflix allows its developers to pick what language to code in and has seen a considerable upsurge in the quantity of Python applications.


The company is an excellent example of a giant tech company using Python in combination with the Django framework. They built their photo-sharing social media platform on top of Django. 

It's worth mentioning that Instagram succeeded in making a smooth upgrade from Python 2.7 to Python 3. They did it after they had moved from Django 1.3 to Django 1.8 in 2016. Instagram has 400 million active users per day. They proved that Python is great in many ways and can scale massively.


Stripe is a fintech startup giving companies the ability to accept online payments. Stripe built its application programming interface (API) for cross-compatibility with mobile applications and websites using Python. 


NASA, or the National Aeronautics and Space Administration, primarily uses Python in their Workflow Automation System (WAS) for shuttle mission planning and data management. NASA also uses Python for a number of other projects which can be found on their website summarising NASA’s open-source projects. 



The choice of technology mostly depends on individual needs and the type of the project. 

However, the current trends of growing the popularity of Python indicate that Python is the future. No matter the project's size or type - Python is believed to be a fit for an app that scales horizontally, takes advantage of the cloud, comprises ML and data science.

If you are unsure which technology to pick, turn to our team. We can provide you with top-notch technical consultancy, after which you'll have a firm idea of what developers would better suit your product. Fill out our contact form; we'd love to speak with you. 


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