Across the coding and Data Science communities, Python is well-known as a popular programming language. In addition to combining the features of object-oriented, structural, and functional programming, Python is a free, open-source language that is excellent for general-purpose programming. The Python programming language was created in 1989 by Guido Van Rossum and adheres to the DRY (Don’t Repeat Yourself) principle. A variety of applications can be developed using Python since it is cross-platform.
Why you should choose Python?
Professionals of all levels will find Python to be a valuable tool because of the following features:
- Easy to use and implement
- Freely available to the public
- User friendly
- Executes the code line by line
- Functional and object-oriented
- Flexible and the same code can be used for different machines
- Extensive collection of libraries
Python Applications in the Real World
- The development of software
Software development can be simplified with Python packages and applications. It is possible to automate the compilation and testing of code using SCons, Buildbot, and Apache Gump. Trac and Roundup are helpful for managing bugs and projects. This process is further simplified by Python’s ability to analyze and visualize data.
- Website development
Security, scalability, and flexibility are the hallmarks of Python web frameworks. Python’s Package Index offers a wide range of useful libraries and modules that can be used to build web frameworks and advanced content management systems like Plone and Django CMS.
- Applications in Science and Mathematics
There are many mathematical and scientific applications based on Python. The Python programming language is used to develop 3D modeling software like FreeCAD and finite element method software such as Abaqus. There are several Python packages that are useful for scientific and numeric computations, including SciPy (scientific numeric library), Pandas (data analytics library), IPython (command shell), and Numeric Python (fundamental numeric package).
- I. and machine learning
Data Science professionals have embraced Python as one of their preferred programming languages. There are many Python packages for AI and ML, including SciPy for advanced computing, Pandas for general-purpose data analysis, Keras, TensorFlow, and Scikit-learn.
- A business/enterprise application
There are many differences between enterprise-level applications and standard applications. A business application is designed to meet the needs of an organization rather than an individual client. In comparison with other programming languages like C and Java, Python can make a significant difference in this area.
- Courses and education programs
There are a lot of similarities between Python’s syntax and English’s. For beginners, it is an excellent choice because of its short learning curve. Educational programs commonly use Python as a programming language. Python is a highly popular introductory language, even among professional developers.
- Desktop Graphical User Interface
GUIs (graphical user interfaces) can be developed using Python on a desktop computer. Developers benefit from the language’s modularity and rich text-processing tools. Python-based GUIs such as PyQt, PyGtk, Kivy, Tkinter, WxPython, PyGUI, and PySide are some of the best on the market.
As you can see from all these versatile and diverse real-world Python applications, Python is capable of handling nearly all development requirements. In recent years, Data Science is becoming increasingly popular with Python applications, especially machine learning.