Python is one of the most popular and widely used programming language in nowadays, because of its simplicity, extensive features and support of libraries. Python also have clean and simple syntax which makes it beginner-friendly, while it also provides powerful libraries and frameworks that makes it perfect for the developers.
Our Python tutorial thoroughly explains Python basics and advanced concepts, starting with installation, conditional statements, loops, built-in data structures, Object-Oriented Programming, Generators, Exception Handling, Python RegEx, and many other concepts. This tutorial is designed for beginners and working professionals.
What is Python?
Python is a general-purpose, dynamically typed, high-level, compiled and interpreted, garbage-collected, and purely object-oriented programming language that supports procedural, object-oriented, and functional programming.
Simple Python Program
print("Hello World!")
Why Should You Learn Python?
Python provides many useful features to the programmer. These features make it the most popular and widely used language. We have listed below few-essential features of Python.
Ease to use and Learn:
Python has a simple and easy-to-understand syntax, unlike other languages such as C, C++, Java, etc., which makes it easier for the beginners to learn.
Object-Oriented Language:
It supports object-oriented programming, making writing reusable and modular code easy.
GUI Programming Support:
Python provides several GUI frameworks, such as Tkinter and PyQt, which allows developers to create desktop application easily.
Dynamic Memory Allocation:
Python automatically manages memory allocation which makes it easier for developers to write complex programs without worrying about memory management.
Wide Range of Libraries and Frameworks:
Python has a vast collection of libraries and frameworks, such as NumPy, Pandas, Django, and Flask, that can be used to solve a wide range of problems.
Versatility:
Python is a universal language in various domains such as web development, machine learning, data analysis, scientific computing, and more.
Where is Python Used?
Python is a general-purpose, popular programming language, and it is used in almost every technical field. The various areas of Python use are given below.
Data Science: Data Science is a vast field, and Python is an important language for this field because of its simplicity, ease of use, and availability of powerful data analysis and visualization libraries like NumPy, Pandas, and Matplotlib.
Artificial Intelligence: AI is an emerging Technology, and python is a perfect language for the artificial intelligence and machine learning because of the availability of powerful libraries such as TensorFlow, Keras, and Pytorch.
Machine Learning: Python is also widely used for machine learning because of its simplicity, ease of use and the availability of powerful machine learning libraries.
Data Analysis: Python is also used to create visualizations of data. It is also used to analyze the price trends and market predictions and automate workflows across multiple data sources.
Web Development: Python is used to develop websites and web applications. There are several popular frameworks like Django and Flask which are used to build web applications.
Python Popular Frameworks and Libraries
Python has wide range of libraries and frameworks widely used in various fields such as machine learning, artificial intelligence, web applications, etc. We define some popular frameworks and libraries of Python as follows.
Web development (Server-side) - Django Flask, Pyramid, CherryPy
GUIs based applications - Tkinter, PyGTK, PyQt, PyJs, etc.
Machine Learning - TensorFlow, PyTorch, Scikit-learn, Matplotlib, Scipy, etc.
Mathematics - NumPy, Pandas, etc.
BeautifulSoup: a library for web scraping and parsing HTML and XML
Requests: a library for making HTTP requests
SQLAlchemy: a library for working with SQL databases
Kivy: a framework for building multi-touch applications
Pygame: a library for game development
Pytest: a testing framework for Python Django
REST framework: a toolkit for building RESTful APIs
FastAPI: a modern, fast web framework for building APIs
Streamlit: a library for building interactive web apps for machine learning and data science
NLTK: a library for natural language processing