Python is an interpreted, interactive, object-oriented programming language. It incorporates modules, exceptions, dynamic typing, very high-level dynamic data types, and classes. It supports multiple programming paradigms beyond object-oriented programmings, such as procedural and functional programming. Python combines remarkable power with very clear syntax. It has interfaces to many system calls and libraries, as well as to various window systems, and is extensible in C or C++. It is also usable as an extension language for applications that need a programmable interface. Finally, Python is portable: it runs on many Unix variants including Linux and macOS, and Windows.
Python has many advantages:
It's easy to learn, easy to use, simple, free to use, has a large community, a lot of libraries ready to implement, and a high-level, object-oriented scripting language. It's of the fastest-growing and most popular programming languages. With built-in data structures, object-oriented and highly interpreted makes it suitable for rapid application development.
Multi-purpose usage of Python includes machine learning, building websites, software testing, automating tasks, and prototyping. Its versatility and beginner-friendliness make Python one of the most used programming languages. As it is general purpose language it is not specialized for any specific problem.
The syntax is similar to the English language and that makes it easy to learn and use for faster programming. Also, helps in reading and understanding code.
It is compatible with various platforms including the most popular such as Linux, macOS, and Windows.
Very productive language due to its simple syntax developers can focus on solving problems and not on syntax and behaviour.
Python comes with an OSI-approved open-source license. It is free to use and distribute. This reduces costs significantly.
Efficient and rich libraries allow easy data processing so it is very handy in data science calculations and complex numeric operations.
- For data analysis and exploration, there are Pandas, NumPy, and SciPy.
- Data visualization: Mathplotlib, Seaborn, Datashader, and others.
- Machine learning: Scikit-Learn, StatsModels.
- Deep learning: Keras, TensorFlow, and others.
- Natural language processing, and image manipulation: OpenCV/cv2, Scikit-image, Cython, Nltk, Spacy.
A web framework is a pre-made template for a website. Python is very popular and widely used in web development. To name some frameworks: Flask, Django, FastApi, Bottle, Dash, CherryPy and more.
Web scraping with Python is easy as it has plenty of libraries ready for usage. Python is good for web scraping due to its dynamic type system and automatic memory management. The most popular are:
Building APIs with python. There are many frameworks to build APIs, and everyone has their pros and cons but is easy to decide which one to use. Depending on the project's demands more than one will be sufficient. Top Python REST API frameworks: Requests, Faster Than Requests, PycUrl, Flask, Tornado, FastAPI, Sanic, Falcon, Bottle, Hug, Eve, Django, TurboGears, web2py, Pyramid.