If you’re thinking of learning Python — or if you recently started learning it — you may be asking yourself:

“What exactly can I use Python for?”

Well that’s a tricky question to answer, because there are so many applications for Python.

But over time, I have observed that there are 3 main popular applications for Python:

  • Web Development
  • Data Science — including machine learning, data analysis, and data visualization
  • Scripting
 
Let’s talk about each of them in turn.

Web Development

Web frameworks that are based on Python like Django and Flask have recently become very popular for web development.

These web frameworks help you create server-side code (backend code) in Python. That’s the code that runs on your server, as opposed to on users’ devices and browsers (front-end code). If you’re not familiar with the difference between backend code and front-end code, please see my footnote below.

Data Science

I think the best way to explain what machine learning is would be to give you a simple example. Let’s say you want to develop a program that automatically detects what’s in a picture. Yes, you can do it with Python. Machine learning typically implements an algorithm that automatically detects a pattern in the given input. You can give, say, 1,000 pictures of a dog and 1,000 pictures of a table to a machine learning algorithm. Then, it will learn the difference between a dog and a table. When you give it a new picture of either a dog or a table, it will be able to recognize which one it is.

You can apply the same idea to:

  • recommendation systems (think YouTube, Amazon, and Netflix)
  • face recognition
  • voice recognition
  • among other applications.

Popular machine learning algorithms you might have heard about include:

  • Neural networks
  • Deep learning
  • Support vector machines
  • Random forest

Scripting

What is scripting?
Scripting usually refers to writing small programs that are designed to automate simple tasks.

What about embedded applications or IOT?
I’m not an expert on embedded applications, but I know that Python works with Rasberry Pi. It seems like a popular application among hardware hobbyists.

What about gaming?
You could use the library called PyGame to develop games, but it’s not the most popular gaming engine out there. You could use it to build a hobby project, but I personally wouldn’t choose it if you’re serious about game development.

What about desktop applications?
You could make one with Python using Tkinter, but it doesn’t seem like the most popular choice either.

So,  you can use Python any applications in computer science. Start exploring Python  and keep watching this space for updates. Write us your experiences at vaguefoundation@gmail.com.

Source: Medium