4Geeks logo
4Geeks logo


Explore our extensive collection of courses designed to help you master various subjects and skills. Whether you're a beginner or an advanced learner, there's something here for everyone.

Coding Bootcamp

Learn live

Join us for our free workshops, webinars, and other events to learn more about our programs and get started on your journey to becoming a developer.

Upcoming live events

Learning library

For all the self-taught geeks out there, here is our content library with most of the learning materials we have produced throughout the years.

It makes sense to start learning by reading and watching videos about fundamentals and how things work.

Data Science and Machine Learning - 16 wks

Full-Stack Software Developer - 16w

Search from all Lessons

LoginGet Started
← Back to Lessons
Edit on Github

What is Python used for?

What are the uses of Python?

Python has become one of the most widely used programming languages in the world mainly because it is extremely powerful, simple and has very good libraries that simplify development. But what is python, Python is a high-level, interpreted, object-oriented programming language. It was created by Guido van Rossum in 1991 and has become one of the most popular languages today due to its simplicity, readability and versatility.

Python is used in a wide variety of applications, including web development, data analysis, artificial intelligence and machine learning. In addition, Python has a large number of libraries and frameworks that facilitate the development of complex applications.

What are the uses of Python?

Python for web development

Python, among many of the areas in which it has been developed, is the development of web applications. Python in this area is mainly used for the development of the Back End (the server side) with different specialized libraries that are free to use.

Among the most outstanding libraries we have for this undertaking are:

  • Flask
  • Django
  • Pyramid
  • Web2Py

Python for machine learning

The objective of machine learning is to create algorithms that allow the system to learn by itself from the data that is given to it, to specialize in this branch there are Machine Learning Engineer courses. These applications are not composed of the same type of development where we tell the program what and how to do what it should do, but the algorithms are improved from the data we feed it.

The Neural Networks are the processing units and try to simulate the behavior of our neurons. In this network the information will be received, they will learn to process it and this will allow them to generate results based on their learning.

A more practical example is when we receive ads depending on what we have consumed, either on YouTube, Facebook and other platforms, these networks are the ones that make the recommendations.

This machine learning process has several libraries that make the job much easier, such as:

  • TensorFlow
  • Keras
  • PyTorch

Python for Data Science

In recent years the use of Python for Data Science has increased and has become one of the main languages for visualization and data processing today, which is to be expected. Py has extremely powerful libraries that allow the generation of visual representations such as the following:

  • Lines, bars and markers.
  • Subcharts and axes.
  • Statistics with box plots, histograms and bar charts.
  • 3D graphs.
  • Pie charts.

The most used libraries for data analysis would be NumPy (the one used by most scientists who use Python to record their research) and Pandas (open source, fast and powerful tool that allows to analyze and manipulate data in a flexible and easy way).

For graph visualization we have a larger collection of libraries:

  • Pandas -> It has tools for data analysis and visualization.
  • Matplotlib -> A very complete library for creating static, animated and even interactive visualizations!
  • Bokeh -> An interactive library for data visualization more focused on modern web browsers.
  • Seaborn -> It is based on Matplotlib and is also used for data visualization.
  • ggplot2 -> Allows to create graphs in a declarative way. You will have to insert the data and tell the library how to transform the variables to the presentation, the primitives of the graphics to use and ggplot2 will take care of the rest.

Python for video game development

Python has also made its entry into the world of video games thanks mainly to the following libraries:

  • pygame -> The most active package for video game development within Python. With this library, Py can communicate with SDL (Simple DirectMedia Layer) to access multiple platforms. There may be a delay when updating the Python version as it must be compiled for each Python version and platform.

  • pyglet -> Based on OpenGL, this library makes up for the difficulties of pygames in the sense that, being completely written in Python, it does not need to be compiled every time there is a version change (except for the jump from Python 2 to Python 3).

  • turtle -> a module that comes with Python once you install it on the system and allows the creation of video games with simpler graphics and user interface.

Python for medicine

Python has been used in medical research and data processing for the detection of diseases or anomalies in the patient's health.

Making use of different application branches that we have already mentioned, in the field of medicine and pharmacology, Python is capable of:

  • Creating and updating models for the development of new drugs.
  • Diagnose based on medical history and symptoms.
  • Analysis of medical data.

Among the libraries for the treatment and analysis of medical data, we find:

  • pyGeno: Open source library for working with reference and customized genomes.
  • MedPy: Open source library for processing medical images.

If we keep looking we will find that it can be used in many more branches, as can be, to mention a few:

  • Robotics
  • Astronomy
  • Neurosciences
  • Unmanned vehicles
  • Meteorology

As you can see, thanks to its power and flexibility, Python is rightly one of the most widely used programming languages in different branches of development and knowledge, ranging from purely technology-related functionalities to health and human welfare. Undoubtedly a language to be taken into account, if not mandatory, if we are in the world of programming.