Our world revolves around the development. development of humans which leads to technological progress, and this, in turn, results in new innovations and programming advancements. Our entire lives are governed by technology in the modern era, the technological devices becoming an attachment to our limb. This is an insightful indicator of the extent to which human lives have been integrated with technology. And the backbone of this important asset to humankind are the people in the back-end aspect of this process, orchestrating this behemoth that we know as the Digital Age. One of the programming languages that champion creative growth, speedy adaptability, and maximum accessibility is Python. To show you the versatility of the Python programming language, in this article, we will provide the answer to the question, “What is Python used for?” Let us get straight to it.
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What can Python be used for
There are so many applications for the Python programming language. However, over time, we have seen that Python is mostly used for 4 main applications. We will go through all of them one by one.
1. Web Development:
Web frameworks such as Django and Flask which are based on Python have consistently become popular for use in web developments. These web frameworks help you build and create server-side codes, which are the codes that run on your server as opposed to the code that runs on the viewers’ devices, which is front-end code. “Why do I need a web framework in the first place?” you may ask. Well, that is because using a web framework makes it easier to make common back-end logic. This includes mapping URLs to Python code, different chunks of Python Code, dealing with databases. Also generating HTML files that users see on their browsers. As a beginner, Django and Flask are the recommended web frameworks,
Flask is a smaller framework, which has fewer components built into the framework itself. This makes Flask much easier to learn and makes it more flexible. On the other hand, Django has more components and a very specific way to deal with databases. With Flask, you can choose what kind of database you want to use and how you wish to interact with it. Therefore, we believe that Flask is the go-to framework if you want it to be much more customizable and interactive. Django should be used if you want to make a more-straightforward application with no frills (blog, news website).
2. Machine Learning:
Before we ask “What can Python be used for, in the context of machine learning?” we must ask ourselves, “what is, in fact, machine learning?” To explain using an example, suppose you wanted to develop a program to recognize the contents of a picture. You will end up optimizing your code so that it learns to detect patterns within that image which it can then use to recognize what the picture actually contains. This kind of approach gets tricky and confusing. This is where machine learning comes in. Machine learning automatically detects more discernible patterns in the given input by implementing an algorithm.
You can use this philosophy to apply machine learning to recommendation systems (Netflix, Amazon), voice, and face recognition. Popular machine learning algorithms that you may have heard about are neural networks, deep learning, support vector machines, and random forest. There are a few popular machine learning frameworks and libraries for Python. Two of them are a) scikit-learn and b) TensorFlow. Scikit-learn comes with some of the most powerful machine learning algorithms built-in. TensorFlow is a type of low-level library that lets you customize your algorithms.
For a beginner, if you already know the basics of how to use Python, we would recommend starting with scikit-learn and if you start running into efficiency issues, then you could switch to Tensor-Flow. After you have learned how you can use Python in machine learning, you can even compete to build the best algorithm to solve a problem on a website called Kaggle. They have some easy-to-follow tutorials for beginners too.
3. Data Analysis & Data Visualisation
To help comprehend this, let us use another example. Suppose you are a data analyst at a big company that sells products online. You may draw up simple graphs to demonstrate your findings and extract plausible explanations through them. Of course, any other data analyst looking at the same data may draw a different explanation for the event. The ideal thing to do here is to make graphs that represent multiple levels of different factors that may be present in the data. Data science in the real world though is not as simple. If you are still wondering how and what is Python used for, in the context of data visualization, look no further.
One of the most popular data visualization libraries available for Python is called ‘matplotlib.’ It is one of the most known and used Python libraries and is equally easy to get started with. Additionally, most other Python data visualization libraries are based on matplotlib. Thus, if you were to learn matplotlib, it would get much easier and quicker to learn other such libraries as well, such as seaborn. After you have learned how to use python in data analysis and visualization, you can proceed to learn Python in statistics as well.
4. Scripting
“What is scripting?” you may ask. Scripting usually refers to writing small programs used to automate simple tasks. Scripting automates functions so that tasks that would take a long time to do manually, can be done in a few minutes through the right code. Python is specifically suited for scripting as it has relatively simple syntax, it is easy to learn, use, and test programs using the Python programming language.
These are the 4 main popular applications of Python.
What can Python be used for, apart from these applications?
Now, you may wonder, this cannot be it. This cannot be the end of all the uses of Python. And you would be absolutely right, it is not. Let us briefly go through some other applications of Python and what is Python programming used for otherwise.
Game Development: For a beginner, you could use a coding library called PyGame. PyGame is generally used to make hobby projects or starter games. High-end, graphically intense games can be made using the C# coding language, with an engine called Unity, which is one of the most popular gaming development software out there. Desktop Applications: You could make desktop applications using Python, even though it is not the most popular coding language to do so. With the help of engines and frameworks like QT or Tkinter, you can create basic, rudimentary desktop applications.
Programming languages like C++, C#, and Java are much more widely used in order to make desktop applications. Hopefully, all your questions regarding what is Python programming used for, have been answered. The world of Python might be a tricky one to navigate, especially for a beginner. However, knowing how your Python code can be used in real-life applications helps make the goal clear. After you have learned the fundamentals of how to use Python, you can proceed to learn so much more and become an expert in the field of coding.