The Python programming language is truly universal. It is applicable in many areas of information technology, development and programming, so it is used in many areas, and QIT specialists skilfully use it to create a quality product.
The most obvious task for Python is automation. The language will allow you to quickly adapt workflows using the available libraries. Even novice programmers will find it easy to master them, and then apply them in their work. Now you can forget about routine, repetitive tasks by writing simple code for automation.
There is a definition for collecting data from various sites – web scraping. The process is most often used in their work by analysts of various profiles. But data is all around us today, so it needs to be collected by specialists in many professions. A tool to facilitate this process and offers the programming language Python. It is called a scraper - an automatic bot that is able to quickly and reliably copy a huge stream of data from sites and paste them into a specific table.
Implementing a scraper with Python is easy, and the benefits are enormous. Imagine that you no longer need to manually collect and spend several hours in a row, everything is available automatically. Get millions of data points from the internet in just a few minutes and use it to your advantage. And if the flow is small, the scraper will be able to complete the task in just a couple of seconds.
Data Analysis and Data Science
The Internet is filled with a huge flow of data, users share any information with each other every second. Every even a small company stores and constantly uses hundreds of terabytes of information. Many even equate the latter with oil for its value in today's realities. And according to forecasts, by 2025 the amount of data generated in the world can grow by 530%.
The Python programming language makes it possible to process, clean and visualize data. All this is available using various libraries, such as Numpy, Seaborn, etc. It is also used for machine learning. Data science professionals use Python to run models that predict a certain response after analysing the information provided.
To work with the backend, Python has several suitable frameworks at once. With Django and Flask, you can create a great back-end site. But for the frontend, you need to turn to the good old JS, HTML and CSS. The simplest of them is, of course, HTML, and when using CSS and JS, it is enough to simply use Bootstrap so as not to prescribe code from scratch.
Today, Python is used by many websites from small to large as a great back-end development tool.
Machine learning and AI
Machines are already fully capable of learning when conducting automated analysis of a certain amount of data. At the same time, the need for programming is minimized in the process of machine learning.
Many libraries are suitable for the implementation of such tasks, for example, Numby, PyTorch, Pandas, etc. With their help, you can easily carry out all mathematical calculations, because they are able to do them automatically without human assistance. It will be enough to create an algorithm and everything is ready. It remains only to analyse the results obtained and choose the optimal solution for further tasks.
However, the question may arise: what should not be done with Python? Despite the large-scale use of Python in various areas of IT, it is still not an ideal solution for some tasks.
Yes, we also know that Python has the Pygame library, which is suitable for game development, but the question is «what»?. With its help, you can create a primitive «Snake», but it is not capable of anything more.
The library does not even have a quarter of the functions that are needed, at least for an ordinary arcade game or a little shooter.
For gamedev, C++ will be the ideal tool. Today, it is the most demanded language for the implementation of game engines. It also has all the tools for great graphics and sound. Even AI-powered bots can be easily integrated into a game written in C++.
In addition, Java, JS, and C# are all suitable for creating a complete life path for the game.
And for the implementation of desktop applications, there are libraries like Tkinter. The latter allows you to make some kind of GUI – a graphical user interface, but it will have nothing to do with a high-quality advanced product. An application can only be implemented with a standard and primitive interface.
For something more global and worthwhile, it's better to use:
Also, Python is not the best solution for implementing projects that require high code execution speed. If every second counts, it is better to use other faster programming languages. Yes, it isn’t recommended to use it specifically for large-scale products such as OS, microprocessors, but for the rest it is quite good.