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In this article at OpenGenus, we have listed and explained 5+ unique ways Programming Students use Python Programming Language.
Python is the fastest growing Programming Language in this decade and despite the market hold and advantages of C, C++ and Java, Python has become the first choice for new developers for a wide range of tasks. The biggest strength of Python is its rich and wide library support which makes it simple to implement and develop applications.
Following are 5+ unique use of Python Programming Language for Programming Students in 2023:
- Secure Web Development
- Scientific Computing
- 3D printing and modeling
- Music Generation and Audio Processing
- Quantitative Finance and Algorithmic Trading
- Space Exploration
We will dive into each point further:
1. Secure Web Development
Python is a versatile Programming Language and is the first choice of a student to develop a web application. It is used for production level web applications as well. Popular web frameworks in Python like Django and Flask are the major driving force. Today it is important for every web application to be secure and Python has in-built ability of security.
The first step for Secure Web Development is to buy SSL certificate and install on your website. This is to ensure that the communication between the web server and client's browser is encrypted which protects sensitive information such as passwords, credit card numbers and other personal data from being intercepted by malicious actors.
Python has a rich library support for secure web development for encryption and decryption, SSL modules for secure socket, secure hashing libraries. Python has support for all security protocols like SSL, OAuth and JWT. All Python Web Framework has built-in support for User authentication, Cross Site scripting and other features which enable Student Programmers get a demo of common features easily in a secured approach.
Following are five standard libraries in Python that are frequently used for security features in Web Development:
- Flask-Security: Provides authentication, authorization, and password hashing for Flask web applications.
- PyJWT: Implements JSON Web Tokens for token-based authentication and authorization.
- Django-axes: Provides brute force protection, rate limiting, and IP banning for Django web applications.
- Django-csp: Implements Content Security Policy (CSP) for Django web applications to protect against cross-site scripting (XSS) attacks.
- Requests: A popular library for sending HTTP requests, with support for SSL/TLS encryption and certificate verification.
2. Scientific Computing
After Web Development, the most popular use of Python by Programming students is Scientific Computing. Students and Professors use Python as the first choice for research projects ranging from Computational modelling, Bioinformatics, Stimulation in Physics and much more.
The most popular Python libraries used for Scientific Computing are:
- NumPy: for efficient array operations and numerical computing.
- SciPy: for scientific operations including optimization, linear algebra and signal processing modules.
- Pandas: for data analysis and manipulation
- Matplotlib: for creating static, animated, and interactive visualizations.
- Scikit-learn: for machine learning tasks like regression, classification and clustering algorithms.
- SymPy: for symbolic mathematics like calculus, algebra and statistics.
- Seaborn: built on top of Matplotlib and provides more complex visualizations and statistical models.
Further more, all leading Deep Learning frameworks like TensorFlow and PyTorch provide stable Python APIs to use the state of the art Deep Learning techniques easily.
3. 3D printing and modeling
3D printers have become popular as it gives a practical experience. Unlike a normal inkjet printer, using a 3D printer is a technical skill and involves creation of 3D models. Programming students do create 3D models for stimulation and leverage their skill to use 3D printers.
In Python, students used OpenSCAD and PyCAM for 3D modelling and in addition, use NumPy, PyVista and Blender to create complex models ready for 3D printers. Many programming students have started businesses from their home by creating decorative items using 3D printers.
For example, Marching Cubes algorithm is a popular 3D modelling algorithm and in Python, it is available in scikit-image library. It has a method skimage.measure.marching_cubes_lewiner() which implements the algorithm to generate a triangular mesh for a 3D scalar field.
4. Music Generation and Audio Processing
Programming students with a passion for music get involved in audio processing and music generation. This is an inovation field and involves extensive programming skills. Python excels in this domain as well.
Python libraries like PyDub and Music21 is frequently used for manipulation of audio files and enable generation of new music using Machine Learning.
5. Quantitative Finance and Algorithmic Trading
Every student get excited to explore finance and trading. Programming students have an upper hand when they realize they can program for Quantitative Finance and Algorithmic Trading. They can build trading algorithms, analyze financial data and explore trading strategies.
PyAlgoTrade library is widely used in this domain and to analyze financial data, Machine Learning is used for which Python has a rich set of libraries like NumPy, Pandas, SciPy, PyBrain and much more.
6. Space Exploration
Python is used in space exploration for tasks such as controlling satellites and analyzing data from telescopes. NASA and ESA have reported to use Python for mission-critical applications due to its simplicity, flexibility and abundance of scientific libraries.
Programming Students targetting to do Space Exploration use Python to get a quick prototype of a space project.
These are the top Python libraries that are used for Space Exploration:
- Astropy: for astronomical calculations and analysis.
- PyEphem: for computing positions of astronomical objects.
- SunPy: for solar physics and solar data analysis.
- SpacePy: for space physics and analysis of space weather data.
- PyNASA: for accessing NASA's APIs and downloading data from various space missions.
- Poliastro: for orbital mechanics and analysis of trajectories in space.
- SPICEypy: for accessing data from the SPICE system developed by NASA for space exploration.
With this article at OpenGenus, you must have a strong idea of how Programming Students used Python for various tasks. You should find your ideas and explore how Python can help you.
