Applications of Python

There is no comparison of this language with other languages like Java and C++ as this language but it’s totally different from others as this language focuses more on automation, data extraction, and scientific usage and is famous for its easy syntax as well. Today, we will try to find some of the most common, and important Applications of Python.

Python was conceived in 1991 by mathematician and computer programmer Guido Van Rossum as a high-level, dynamic typing programming language.

Over the years, this language has conquered the job market and attracted several programmers around the world, and this can basically be translated by one fact: a large number of projects and companies have been betting heavily on Python to obtain the most results efficient.

It is a language directly related to the readability of the code: an extremely concise and clear syntax. With a library that has powerful resources, as well as modules and frameworks, giving Python a chance, especially in 2020, can be a great move also for those who are starting in the programming industry and want to conquer their opportunity in the labor market for this technology.

Main Applications of Python

Here are some of the main applications of Python:

  1. Data Science
  2. Automation
  3. Application Development
  4. Artificial Intelligence
  5. Machine Learning
  6. Web development
  7. Business applications
  8. Image Processing
  9. Desktop GUI
  10. Audio/Video Applications
  11. Scientific Calculations
  12. Embedded Application

All this charm and elegance of Python, although seductive, only really makes sense if you know where you want to go, that is, the applications of this technological resource can indicate if (or how) you can reach your goal. And that is what we are going to talk about now. Let’s have a look at this image, which shows Big Tech giants using Python

Data Science

Data Science is one of many Applications of Python constituted through studies and data analysis, which makes it an essential tool for several companies. If you have only information, you have no intelligence. Intelligence comes from the retention of these data, organization, and efficient processing. Therefore, the correct analysis through this programming branch is very requested and important.

All of this consists of analyzing and synthesizing a series of data in business insights, in order to assist these companies in their decision-making, obtaining the best result and profit.

When it comes to that, Python is one of the main technologies. This is largely due to its libraries specially dedicated to data analysis and relative simplicity of handling. Among these libraries, we can mention Pandas, one of the main ones in the market.

Machine Learning

Well, machine learning is also one of many Applications of Python which we can try just because there is enough support of Python libraries for machine learning which nowadays is so booming that even in a sneaky way, we have contact with this resource much more than we can tell and this shows itself more and more as the market trend. Of course, this is structured by all analytical mathematics for the construction of these models, but basically, we can see this tool as an “umbrella” that houses several niches.

Fraud Detection, Customer Service Bots, Video Surveillance Systems, Financial Negotiation, and Autonomous Vehicles, among others.

We are talking about artificial intelligence, making machines capable of performing tasks that would normally be performed by people: this is done by obtaining data and analyzing patterns. This learning can be characterized by several different categories such as supervised, unsupervised learning, and reinforcement learning. Where, respectively, there is a need for a “teacher” programmer for the alignment of results, a system that develops its own conclusions through a set of data, or the combination of these two methods.

Python is one of the main technologies to work with, in addition to Big Data, Machine Learning, an area of great growth in recent years.

Big Data

As we were talking about data, Big Data is related to the mass analysis of that information. It is an extremely valuable resource so that, for example, companies can acquire competitive advantages in different market segments.

This term has been used since the ’90s to name the extravagant and disorderly amount of vine data being generated every fraction of a second. Nowadays it is a more than essential resource within the market, having its essential functions for the resolution of, for example, marketing strategies. These strategies aim to reduce costs and increase productivity through intelligent decision-making, valuing the business in question.

As well as, for Data Science and Machine Learning, Python is also ready and has several libraries to work with Big Data, as these areas are closely related.

There are several libraries for working with Big Data in Python, such as Pandas (mentioned earlier), NumPy, Matplotlib, and Scikit-Learn, among others.

Web development (Django and Flask)

When we need to access data directly through the web browser, through computers or even smartphones, we make use of structures that are produced through this concept and resources.

In spite of all the other applications that we have already mentioned in Python, we can also consider that this is a language that presents itself as an excellent alternative for the development and web application in a relatively simple and powerful way. All this is because the Python language has two of the main frameworks used in the market for web development: Django and Flask.

With these two tools, it is possible to produce web applications supported by an infinity of resources that, for sure, will meet all the expectations and demands of the market.

Job market

There are many Applications of Python but also when it comes to the job market, Python was identified by Stack Overflow as one of the main programming languages for 2019. This is due to the high demand for work that the resources of this language can supply.

A crucial point is that, due to its easy syntax, many automation engineering, economics, betting analysis, and finance companies have been investing in computer programming, popularizing and increasing demand even beyond the information technology sector.


As we explored in this article, we can see that Python is one of the main languages to work with nowadays. Its versatility makes it a very effective alternative for different scenarios and terrains such as in the most booming areas such as Machine Learning, Big Data, Data Analysis, Web Development, or even for people who simply seek to optimize some process of their daily routine.

The fact that this language is also used widely for scientific studies is also related to this ease of handling that popularizes it as being of general use. Even in a scientific application, where the line of reasoning is extremely complicated, the automation of several processes that this language has allows the user to remain focused only on solving the problem, without the need to pay attention to parallel situations such as memory allocation, for example.