In 2022, Python has further cemented its place on top by being number one in the PYPL Index and TIOBE Index rankings. If you want to make money as an aspiring developer, these rankings are good suggestions of what to learn because they indicate what languages are in high demand.
However, before you pay for that course and jump on the Python bandwagon, it’s also essential to know what you can do with the programming language.
What is Python Used for?
Python is beloved by developers for several reasons: its ease to learn, relatable syntax, supportive community, efficiency, and versatility. Unlike some programming languages, Python is highly versatile and can be used to achieve many purposes with your computer. One of the ways Python can be so versatile is through the various libraries and frameworks available in the language for various purposes.
1. Machine Learning
Computers are machines made to accept and process data; they rely on instructions given by the user to out information and work strictly on GIGO (Garbage In Garbage Out). Everything meaningful that a computer does is usually the result of manual human input; in summary, computers are naturally NOT intelligent!
However, it is possible to program some semblance of intelligence into computers using machine learning. Machine learning is the study and creation of computer algorithms that collect past data to try and predict future outcomes.
Machine learning is an essential part of User Experience enhancement on most applications, and you would observe its use in areas such as:
- Friends, followers, feed, or content suggestions on social media platforms.
- Keyboard autocomplete features.
- Robotics and self-driving vehicles.
- Fraud and spam detection.
- Language detection and translation.
- Face or voice recognition.
- Ad generation and suggestions.
Some popular machine learning algorithms include:
- Neural networks
- Support vector machines
- Deep learning
- Random forest
You can use Python for machine learning through frameworks such as scikit-learn and TensorFlow. While TensorFlow is a low-level framework that allows you to build custom algorithms from scratch, scikit-learn comes inbuilt with some of the most popular machine learning algorithms.
2. Data Analysis and Visualization
Data collection is a prevalent practice in various works of life, whether it’s the forms you fill physically in schools and offices or the ones you fill online. Data analysis is the process of inspecting, cleansing, ordering, and modeling this collected data into useful information. The end goal of data analysis is to use the analysis as a benchmark for discovering useful information, leading to better decision-making.
Data visualization puts data into a visual format such as a chart or graph. Data visualization is often the first step of data analysis because visualizing data helps you have an intuitive understanding of it. Visualizing data also helps you see patterns that would be hard to observe by looking at figures and data entries alone.
You can use the Python library known as matplotlib for data analysis and visualization– static, animated, and interactive. Matplotlib is so popular that libraries such as seaborn are written based on it, making it easy to learn them.
3. Web Development
Web development is the process of building and maintaining websites and web applications. As the worldwide web and internet have grown, so has the demand for front-end and back-end web developers.
Front-end development deals with the appearance and behavior of the visible parts of a website– such as images, links, taskbars, etc. A back-end developer handles the website’s functionality under the hood and deals primarily with databases, back-end logic, APIs, and Servers.
Python is more popular as a back-end development tool through frameworks like Django and Flask; these tools allow you to create code that runs on the server. Flask offers more flexibility, as it contains fewer components, unlike Flask, which also has a more rigid method of communicating with databases.
The most notable name in full-stack Python web development is Anvil; it is a platform for building and hosting full-stack web apps written entirely in Python.
Scripting is the process of writing small programs to automate simple tasks. For instance, a company can create a script that looks through customer emails for specific keywords. You could handle the process of filtering manually, but scripting will make the task easier, faster, and less repetitive.
Scripts don’t require compilers to be used by the computer; they can be interpreted quicker and easier by writing them unto the machine you need them to run on. A script is different from a regular program because it does not prepare for any uncertainties; it specifically looks out for a particular scenario. On the other hand, a computer program covers a broader base of use cases.
Creating and running scripts using Python does not require any frameworks. First, you create your script and save it as a “.py” file; next, you open a Command Line Interface and type the word
python followed by the path to your script file; for example:
5. Desktop Application Development
While mobile development is thriving more than desktop development, there’s still a massive market for the latter. It is not common to see desktop applications created using Python, but it is possible through frameworks such as Tkinter and QT.
6. Game Development
You can also use Python for game development using the Pygame framework. While the functionality of the framework isn’t as robust as traditional game development languages, it includes features such as:
- Vector math
- Collision detection
- 2D sprite scene graph management
- MIDI support
Games programmed using Pygame are cross-platform and can run on Android phones and tablets using pgs4a, a Pygame subset for Android.
As with desktop development, this is not an advisable path to pursue professionally and instead should be used for hobbyist programming.
7. Software Testing
In between the moment applications are wholly developed and when they are released is a testing phase. During testing, software testers use every aspect of the software to see what works and what doesn’t, providing feedback to the developers. Some companies use trial or “beta” versions to get existing users to try new features, while others hire people who test the software.
Python can be a helpful tool in automating the software testing process. Python’s use in software testing could be for tasks like running simultaneous processes to test the program’s ability to handle the load or its speed.
Many companies are moving away from manual testing and are incorporating automated testing with Python. While automated testing will not completely replace manual testing because of user experience feedback, it’s an edge if you learn how to do both.
Read More: 4 Ways To Get Python Length Of String
It’s easy to see the allure of Python when you understand all that it can do and the career opportunities of learning the language. Many companies use Python for various aspects of development so learning the language gives you an edge, as you’ll likely encounter other Python developers in other areas working on the same project.