Nowadays, the tandem of Python and Django is extremely popular: just take a look at some examples of apps built with Django! Let’s try to figure out where they can be used.
So, Django is the most famous and very popular framework for Python. Here are its top advantages.
- Provides full functionality for creating web applications and websites. Provides ready-made admin interface, comments, and user management capabilities.
- Django offers a convenient template system with inheritance, built-in authentication capabilities, easy routing, and much more.
- This framework works with databases such as PostgreSQL, MySQL, SQLite, and Oracle.
- Contains a web server for the development stage.
In general, the framework is easy to learn and use and is suitable for creating projects of various scopes and purposes.
The main applications of Python are:
- AI and machine learning.
- Statistics and data analysis.
- Web development.
- Scripts and task automation.
- Desktop applications.
Python has enjoyed extraordinary popularity in recent years. And no wonder. It is the perfect language for novice programmers. Also, it has many applications in numerous developmental fields.
Python itself is an excellent introduction to the world of programming. It has a simple syntax and is perfect as the first language to start with.
We now have the introduction behind us, so we will try to look at the different areas where Python can be used.
Artificial intelligence and machine learning
Machine learning includes systems that learn by themselves. The more data they get at the entrance, the better results they can achieve over time.
Perhaps you have heard such a term as Neural Networks. These are systems and algorithms that are supposed to resemble the human brain. Python is often used to create such networks.
Many examples of applications in the real world could be given. For example, algorithms recommending content. Surely you associate how it works – the application tries to predict content that you will like based on your previous behavior. There are also more advanced applications, e.g., algorithms used in autonomous vehicles. Machine learning also plays an important role there.
Python has many tools to facilitate the creation of this type of system. It is worth mentioning here, for example, the popular TensorFlow library. This field is growing very fast and has a great future ahead of it. At this stage, we don’t even quite know how much this topic can develop – probably even more than we think.
Statistics and data analysis
Data is everywhere. We are inundated with countless data, charts, and tables. Python has many applications related to collecting, processing, and presenting various types of data.
In practice, we use Python to cope with the following tasks:
- Statistical calculations.
- Data visualization, and charting.
- Various types of scientific calculations.
The most popular tools to facilitate work with data are Matplotlib, NumPy, and Pandas.
This field includes the development of web applications. Think of a typical app: logging in and displaying content, making a purchase, etc. Python also has many applications in this field.
Popular tools for Python are Flask and Django (we have mentioned it already). These are the so-called frameworks to facilitate the creation of web applications. Such frameworks provide predefined functionalities, thanks to which you can easily build the main blocks of the application – login, communication with the database, notifications, etc.
Scripts and automation
Python, at the root, is a relatively simple scripting language. With its help, you can quickly write simple programs (scripts) that facilitate everyday work. Think of tasks such as searching text, moving files to a specific place, sending various notifications, etc.
Imagine backing up important data every day. Every day you laboriously copy files to the server. Instead of doing it manually, you can write a simple script in Python that will do all the work for you. Sometimes a few lines of code can make your life significantly easier.
The possibilities are endless. Think of any tedious task you do regularly. You can automate most such tasks using Python.
Traditional window/desktop applications can also be written in Python. Perhaps the market for this type of application is getting smaller every year, but there is still such a possibility.
Python has tools such as the popular Tkinter library. Thanks to them, you can build an application interface fairly quickly, i.e., all these windows, buttons, drop-down menus, etc. Perhaps this language is not the perfect choice for writing super powerful, complex desktop applications. On the other hand, if you have to create something relatively simple, you can safely do it with Python.
Python, as a simple language, is widely used to learn to program. We already mentioned this at the beginning of the article. It is simply more beginner-friendly than other popular languages.
The simple syntax allows easy learning. And the multitude of educational materials naturally promotes Python as a language for learning programming from scratch. That’s why Python finds wide applications in education: both formal (school) and unofficial/personal.
If you feel you can’t cope with Python/Django development yourself, contact a professional development team: experienced guys will help you cope with any challenges, from the project discovery phase to finding clients. All in all, Python is a simple, friendly language. It is ideal for beginners. And powerful enough to have many professional uses. No other language has had such a great increase in popularity as Python in recent years. This is normal because no other language can so neatly combine simplicity with great possibilities.