Year of Python



When in 1989 Guido van Rossume created a programming language that was easy for students to learn, he probably never imagined that three decades later it would be used to mass-produce websites, web and mobile applications and even complex data processing systems for artificial intelligence, at that time a completely futuristic entity.

What made Python dominate the IT world? Van Rossume relied on simplicity. If you are brought up in a Polish-speaking family and want to learn English or German as your second language, then in addition to learning vocabulary, you also need to understand grammar and syntax rules. It is only when words are properly combined that they form meaningful statements, the intention of which may be to convey some information to someone (I'm coming tommorow) or a call to action (Could you pick me up from the airport?). Like any programming language, Python was intended to be used to communicate between humans and machines. To make it easy to master, van Rossume minimised the number of rules governing it. However, so as to retain the capabilities of existing languages such as Perl, Basic and Lisp. 

However, he waited years for success. Although Phython had been on the list of most popular programming languages since the beginning of the 21st century, it was closing it rather than opening it. The acceleration came in 2018. The next five years have been a frantic rally towards the top of the rankings. Python suddenly emerges from the shadow of C#, C++, PHP, and then chases C and Java like mad. And finally, in 2021, it reaches the peaks of popularity, where it continues to this day. 


The TIOBE Index measures this popularity by the number of engineers working in a given environment, job advertisements with a language requirement or the offer of courses and studies teaching it. At the same time, it stipulates that leadership does not mean that it is the best language or that the most lines of code have been written in it. However, when one realises that NASA and Google work in Python, and that Meta (Facebook and Instagram apps) and Uber have built their applications in Python, it seems unnecessary to doubt its quality. There are good prospects ahead for Python. The year 2023 should consolidate its lead over other languages. Why? Here are our predictions.

Artificial intelligence
GPT chat is the tip of the mountain... of possibilities that artificial intelligence (AI) presents. And with its development, Python's popularity will grow. This is because it allows advanced algorithms to be built to process powerful databases. It is already powering deepfake, which involves replacing an actor's face with another person's face, or voice recognition, which is sound recognition technology.
Models built in Python have the ability to interpret the surrounding reality by recognising images and sounds, comparing, segmenting and classifying them. Based on in-depth analysis, they can also make predictions, helping us to prepare for the future.
We will therefore prepare ourselves for the fact that the development of AI and Python will be highly correlated. Also because many advanced algorithms for processing millions of data are provided by Python in its libraries. This makes it easier to build efficient models and drives AI development.

Talking to machines
I have mentioned voice recogniton. However, the potential of this technology needs a little more attention. The correct recognition by computers of human spoken language represents a breakthrough in human-machine communication. We already communicate in this way with smartphones, tablets and laptops, but also with televisions or cars. It is a technology that will change our daily habits and transform many industries with entertainment, education, banking, sales and customer service at the forefront.
And in this sphere Python is once again rising to the challenge. Its ability to build advanced algorithms, is accelerating the pace at which we start talking to machines. It allows us to recognise the building blocks of the language and learn the rules for combining them logically. And thanks to widely available frameworks, programmers can quickly create applications in Python that interact with humans in a way that is natural to them.

Scalability of projects
The principle of project scalability is becoming commonplace in the digital marketplace. Founders increasingly understand the sense of limiting the functionality of applications produced in the first phase of project development. Creating an MVP (Minimum Viable Product) allows costs to be reduced. At the same time, a well-prepared prototype provides an opportunity to verify business assumptions.
Python responds perfectly to these needs. It allows single functions to be programmed and collated into larger sets. Applications built in this way gain in reliability and efficiency. Python is also suitable for parallel work carried out in several teams, and therefore fits perfectly into distributed production models. These are becoming increasingly important not only because of international cooperation, but also because of the post-pandemic hybrid working model that is becoming popular.

Cloud applications
The widespread availability of stable clouds (such as Microsoft Azure or Google Cloud Platform) reduces the cost of running applications. Their owners, using cloud solutions, pay for the resources actually used, whereas traditional hosting requires charges irrespective of the scale of server space occupied or the use of available transfer.
The migration of applications to the cloud goes hand in hand with Python's readiness for scalability. This allows developers to focus on their software development work without getting wrapped up in infrastructure issues. As a result of this symbiosis, companies can quickly and cost-effectively increase the functionality of their shared applications while being ready to handle increased user traffic. Advanced cloud automation, in turn, speeds up the deployment of successive versions of applications written in Python.

Fewer bugs
Finally, Python allows developers to work in the TDD testing model. In practice, this means that before writing the code, a test of the desired behaviour that it should produce is prepared. This approach avoids errors and increases the stability of the applications being built. It is ideally suited to the model of building scalable applications. This is because it provides guarantees that new added functionalities will integrate correctly with the existing corpus. And this is another argument in favour of choosing Python.



I predict that Python will remain a star among programming languages in 2023. This is because it is flexible and agile. We have been successfully using it for years in projects for high-tech marketing campaigns, an example of which is the deepfake-based Tymbark juice campaign. Thanks to advanced algorithms, each user was able to perform on the Tymbark stage in a video with the most popular Polish pop musicians. We also used Python, among other things, to build a mobile application and a guest management system for Poland's largest music festival Open'er Festival or a content-personalising portal for the magazine "Kukbuk".

What speaks in favour of Python is its readiness to analyse powerful databases. So it will continue to drive cutting-edge technologies such as deepfake, voice recognition or metaverse. And if you want to know the predictions for their development, take a look at the trendbook prepared by the Panowie Programiści – 

Adrian Hołota

Co-founder of digital production house Panowie Programiści ( and UX design agency and product strategy Sparing Digtal ( He advises clients on how to create digital products wisely, which he then builds and develops with his team. He is the creator and owner of the first Polish digital fashion house Nueno Digital Fashion ( He has won many industry awards, including Innovation, KTR, EFFIE, Mobile Trends Awards, Mixx Awards, AWWWARDS. He was a member of the Innovation by SAR competition jury. 

The article appeared at