Saying that there’s hype about Python is pretty much the same as describing fire as warm. Let us give you by the numbers:
Yes, the statistics are spectacular. However, it’s not just about these numbers. There is a vast ecosystem of features and insights that make this language so utterly powerful.
This language is practically everywhere. It is on the rise, to say the least. During the last five years, it jumped over C languages, PHP, and Java, and it already leaves them behind. And that’s not going to stop or reverse any time soon.
To find the first proof, let's take a look at what kind of companies have decided to rely on Python. The list is impressive - YouTube, Instagram, Netflix, Reddit, Quora, Pinterest, Dropbox, and it goes on. Web giants have built their platforms on Python. They all used this engine to get their complex websites and solutions up and running. Also, motion picture business titans like Lucas Film or Disney have adapted this language and made the most of it for their purposes.
Where is this enthusiasm coming from? Mainly because Python is dynamic, simple to code, easy to learn, super scalable, and full of potential for use in various fields.
It’s best to start with the basics. More and more web development projects go for Python, mostly because this back-end language is much easier than C or Java. Powered up with front-end frameworks like Flask, Django, or Pyramid, it plays a huge role in building mobile and desktop apps.
Python evangelists highlight the fact that it is super small and it can be embedded on every device, and on most of the servers. Its elegance and simplicity delight not only the top business and product owners, who tend to use “Python where they can, and C where they must”.
Another industry that discovered tremendous potential of Python is higher education and e-learning sector. It’s one of the most growing and definitely the easiest programming language to learn, and more and more universities take advantage of it. The effect – students begin their educational coding path with Python.
And how about e-learning platforms? Just take a look at Udemy or Coursera where you will find hundreds of Python online courses. The simplicity and reasonably low entry threshold are two reasons why students gravitate to those courses. The other – possibly even more enticing – is what you can do with Python. The perspective of building top-notch, scalable applications, prototyping games, creating 3D animations is indeed tempting. But there’s more. The real magic happens when we take a look at libraries.
Apart from the libraries commonly used by developers and data analysts, there are others that bring its significance to a higher level. These libraries hold great value for scientific computing, which is crucial in various fields.
EarthPy serves earth sciences by helping analyze the sea ice thickness in the Arctic, enabling scientists to generate online maps and spot any alarming symptoms. SunPy, on the other hand, provides the software dedicated for observing solar wind and energy bursts on the Sun, whereas Astropy delivers packages for astronomical purposes. That’s not all – Biopython addresses the needs of molecular biology and the future of bioinformatics, and PsychoPy package answers the calls of modern neuroscience, psychology, and psychophysical experiments.
In every corner of scientific research today, there is Python. As you can see, Python and its libraries can do things that really matter.
One of the hottest topics within technology today, Artificial Intelligence, Machine Learning, Deep Learning are gradually taking over the tech world. It’s fascinating and scary at the same time, but one thing’s for sure – AI is the future, and this future is written in Python.
Python extends across AI/ML, from face and voice recognition, to virtual assistants, chatbots in B2B and B2C, automation processes on e-commerce platforms, and finally – coding robots to think and learn for themselves.
The most impactful web platforms and mobile apps utilize Machine Learning-based recommendation systems to help them better reach their customers. Amazon, YouTube, Spotify, Netflix – they all suggest us products, clips, movies, based on the user’s previous preferences and actions taken online.
Machine Learning’s popular algorithms: Deep Learning and Neural Network make computers observe data on their own, learn from it, and come up with solutions to certain pain points. This means gathering and processing oceans of data and taking actions based on that data. It’s not a mystery that tech giants like Microsoft, Google, and Facebook use these algorithms on a large scale, but that’s a separate story.
Narrowing it down to a developers point of view, Python brings limitless possibilities to the table – when you combine Machine Learning paradigms with web development, you can build and scale amazing products.
Python provides us with endless possibility, which is why it’s one of the most sought after languages by businesses and developers alike - and one of our favorite languages here at VentureDevs.