Reasons Behind the Popularity of Python
The technology is ideal for enterprises, regardless of whether you want to build a solution powered by a machine language or an internal web application. Presently, a large segment of software developers is using Python. It has got fewer programming codes and the features are versatile enough to develop any type of software.
The silent feature of python is given below: -
1. Easy to learn
2. Modular
3. Object-oriented
4. Interpreted
5. Dynamic
6. Portable
7. Extensible in C and C++
8. High level
- Easy to learn: Python offers excellent readability and uncluttered simple-to-learn syntax which helps beginners to utilize this programming language. The code style guidelines, PEP 8, provide a set of rules to facilitate the formatting of code.
- Modular:- A module is a file consisting of Python code. A module can define functions, classes, and variables. A module can also include runnable code. A module allows you to logically organize your Python code. Grouping related code into a module makes the code easier to understand and use.
- Object-Oriented: - It allows us to develop applications using an Object-Oriented approach. In Python, we can easily create and use classes and objects.
- Interpreted: - Python is called an interpreted language because it goes through an interpreter, which turns code you write into the language understood by your computer's processor.
- Dynamic: - It is called dynamic because it doesn’t know about the type of the variable until the code is run. So, the declaration is of no use. What it does is, It stores that value at some memory location and then binds that variable name to that memory container. And makes the contents of the container accessible through that variable name. So the data type does not matter.
- Portable: - it runs on many Unix variants, on the Mac, and on Windows 2000 and later.
- Extensible in C and C++:- we can write some python code into c or c++ language and also we can compile that code in c/c++ language.
- High Level: - Python is an example of a high-level language other high-level languages you might have heard of are C++, PHP, and Java.
Instead of this features some popular library also supports python and these are as given below: -
- Pandas: High-performance data structures are present in this library and the developers can use various analysis modules
- Numpy: This particular library is used for mathematical and scientific computing with Python
- Keras: The Keras library is used in Python for writing neural networks, and developers use it for machine learning
- Tensorflow: This library was released by Google and allows the developers to create Deep Learning features and modules like image recognition and detection
- Scikit-learn: This is a useful library for data analysis, machine learning and mining