Why is python called python?

The founder of Python is Guido van Rossum. During the Christmas period of 1989, in Amsterdam, in order to kill the boredom of Christmas, Guido decided to develop a new script interpreter as an inheritance of the ABC language. The reason why he chose Python (meaning Python) as the name of the program was because he was a fan of a comedy group called Monty Python.

ABC is a teaching language designed by Guido. In Guido's own opinion, ABC is a very beautiful and powerful language that is specially designed for non-professional programmers. However, the ABC language did not succeed. Guido believes that the reason is due to non-open label opening. Guido is determined to avoid this mistake in Python. At the same time, he wanted to achieve something that had been glimpsed in ABC but never came to fruition.

In this way, Python was born in the hands of Guido. It can be said that Python developed from ABC and was mainly influenced by Modula-3 (another very beautiful and powerful language designed for small groups). And combines the habits of Unix shell and C.

Python has become one of the most popular programming languages. In January 2011, it was named the 2010 Language of the Year by the TIOBE Programming Language Ranking. Since 2004, the usage of python has grown linearly.

Due to the simplicity, readability and scalability of the Python language, there are an increasing number of research institutions using Python for scientific computing abroad. Some well-known universities have used Python to teach programming courses. For example, the basics of programming at Carnegie Mellon University and the introduction to computer science and programming at MIT are taught using the Python language. Many open source scientific computing software packages provide Python calling interfaces, such as the famous computer vision library OpenCV, the three-dimensional visualization library VTK, and the medical image processing library ITK. There are even more scientific computing extension libraries dedicated to Python, such as the following three very classic scientific computing extension libraries: NumPy, SciPy and matplotlib, which provide fast array processing, numerical operations and drawing functions for Python respectively. Therefore, the development environment composed of the Python language and its numerous extension libraries is very suitable for engineering and scientific researchers to process experimental data, make charts, and even develop scientific computing applications.

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