What is Python? Powerful, intuitive programming

Dating from 1991, the Python programming language was considered a gap-filler, a way to write scripts that “automate the boring stuff” (as one popular book on learning Python put it) or to rapidly prototype applications that will be implemented in other languages.

However, over the past few years, Python has emerged as a first-class citizen in modern software development, infrastructure management, and data analysis. It is no longer a back-room utility language, but a major force in web application creation and systems management, and a key driver of the explosion in big data analytics and machine intelligence

Python an ideal teaching language, and it lets newcomers pick it up quickly. As a result, developers spend more time thinking about the problem they’re trying to solve and less time thinking about language complexities or deciphering code left by others.

Python is not a “toy” language

Even though scripting and automation cover a large chunk of Python’s use cases (more on that later), Python is also used to build professional-quality software, both as standalone applications and as web services. but what it lacks in speed, it makes up for in versatility.

Data science and machine learning with Python

Sophisticated data analysis has become one of fastest-moving areas of IT and one of Python’s star use cases. The vast majority of the libraries used for data science or machine learning have Python interfaces, making the language the most popular high-level command interface to for machine learning libraries and other numerical algorithms.

Web services and RESTful APIs in Python

Python’s native libraries and third-party web frameworks provide fast and convenient ways to create everything from simple REST APIs in a few lines of code to full-blown, data-driven sites. Python’s latest versions have strong support for asynchronous operations, letting sites handle?with the right libraries.

Glue code” in Python

Python is often described as a “glue language,” meaning it can let disparate code (typically libraries with C language interfaces) interoperate. Its use in data science and machine learning is in this vein, but that’s just one incarnation of the general idea.?If you have applications or program domains that you would like to hitch up, but cannot talk to each other directly, you can use Python to connect them.

Where Python falls short

Also worth noting are the sorts of tasks Python is?not?well-suited for.

Python is a high-level language, so it’s not suitable for system-level programming—device drivers or OS kernels are out of the picture.

It’s also not ideal for situations that call for?cross-platform?standalone binaries. You could build a standalone Python app for Windows, MacOS, and Linux, but not elegantly or simply.

Finally, Python is not the best choice when speed is an absolute priority in every aspect of the application. For that, you’re better off with C/C++ or another language of that caliber.What is Python? Powerful, intuitive programming