Areas of application of the Python language

Python is not just a programming language. This is a whole world with its own opportunities, difficult tasks and ways to solve them. It is quite difficult for a beginner who has just begun to get acquainted with the language, in which areas his knowledge can be useful.

In fact, the choice is quite huge. Python is conquering the market more and more actively every day, and today it occupies one of the leading positions among all other languages, competing for primacy with the “monoliths” of the industry. Here, by the way, you can find experienced Python developers

Of course, Python will never be able to replace low-level C and C ++, because they are able to almost completely control the processor, they will not take the place of Java, designed to develop complex applications. Also, Python cannot be called an analogue of JavaScript, which is supported by a huge proportion of sites.

But why is Python still moving towards its Olympus? Why hasn't it been pushed out by competitors? After all, even the creator of Python, Guido van Rossum, back in 1989, said that he did not predict popularity in the market for his language.

In fact, with Python, everything is as transparent as possible - it is simple and versatile, so it can be used to work in many areas.

web development
In Python, you can make the entire backend of an Internet resource that will be executed on the server. This is done using special frameworks (Django and Flask) written in this language. With their help, the process of processing addresses, accessing databases, and creating HTML that is displayed on user pages is simplified.

To date, third-party developers have written a large number of additional tools aimed at implementing network applications. For example, the HTMLGen tool allows you to create ready-made classes for an HTML page using the Python language for this. And the mod_python package makes it easy to run Apache scripts while keeping Python Server Pages templates running smoothly.

If we talk about the visual component in the field of IT, then here Python can show itself as a very effective tool that solves a lot of problems. By creating modern graphical interfaces in Python, you can easily adapt to the style of the OS in which the application is being created. Especially for these purposes, additional libraries were created for building the interface - PythonCard and Dabo, which facilitate the work process.

The developers of the modern version of Python have created the simplest and most understandable access to almost any database. So, today, in the working environment of the language there is a programming interface that allows you to use the databases directly from the script using SQL queries. Also, code written in Python can be used for MySQL and Oracle databases with minimal modifications.

System Programming
Another coin in the treasury of Python's features is the language interfaces that allow you to control the services of the Windows, Linux, and other operating systems. Thanks to this, Python opens up a lot of opportunities for creating portable programs. It's no secret that this language is used to write applications used by system administrators. In this way, Python makes it faster to find and open files, launch applications, make calculations easier, and more.

Complex computing processes
This is the very area where Python can compete in its capabilities with FORTRAN or C ++. A special NumPy extension written for mathematical calculations works great with arrays, equation interfaces, and other data. As soon as the extension is installed on the computer, Python seamlessly integrates with formula libraries.

But NumPy isn't just for computing. In addition to its main task, it can be used to create animated elements and draw objects in a 3D environment, while performing parallel calculations. For example, the popular ScientificPython add-on boasts its own libraries that are designed for computing processes in the field of science.

In addition to calculations, Python allows you to visualize the received data, which is quite convenient.

Machine learning
In addition to the main toolkit, Python has additional libraries and frameworks that allow you to work in the field of machine learning. Scikit-learn and TensorFlow are especially popular. Scikit-learn is different in that the most common learning algorithms are already built into it. TensorFlow, in turn, is a low-level library that opens up possibilities for creating user algorithms.

Machine learning processes based on the Python programming language help implement face and voice recognition systems, build neural networks, deep learning, and more.

Process Automation
Today, one of the most popular ways to use the Python language is to create small scripts that automate some workflows. For example, you can write quite simple code that will "independently" work with emails. If a person needs to sort out letters with certain keywords or phrases, then manually doing this is quite problematic, but the script will cope with this task without problems.

Why is it best to use Python for this? First, it has a very simple syntax that makes scripting easy. And secondly, the code itself is not compiled before being run, which greatly simplifies the debugging process.

Game industry
In vain, many people underestimate the gamedave, because it was thanks to him that so many gadgets, developments appeared and the graphics improved significantly. Of course, Python is hardly suitable for large projects, its tools in this area are somewhat limited, but for fans of this language, building small applications and indie toys is not such a difficult task. For multi-platform games, the Unity engine, controlled using the C# language, is best suited. This tool is just created for such purposes.

Roman 4711

2 Blog posts

Nadia 6 w