search

Why is it called Python?

Jun 27, 2019 am 11:06 AM
python

Why is it called Python?

The founder of Python is the Dutchman Guido van Rossum. During the Christmas period of 1989, in Amsterdam, Guido decided to develop a new script interpreter as an inheritance of the ABC language in order to kill the boredom of Christmas.

The reason why Python (meaning boa constrictor) was chosen as the name of this programming language was taken from the British TV comedy "Monty Python's Flying Circus" that premiered in the 1970s. (Monty Python's Flying Circus).

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 believed that the reason was due to its non-openness. 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. Since 2004, python usage has grown linearly. Python 2 was released on October 16, 2000, and the stable version is Python 2.7. Python 3 was released on December 3, 2008 and is not fully compatible with Python 2.

In January 2011, it was named the 2010 Language of the Year by the TIOBE Programming Language Ranking.

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 adopted 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.

For example, the following three very classic scientific computing extension libraries: NumPy, SciPy and matplotlib.

They 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.

In March 2018, the language author announced on the mailing list that Python 2.7 would end support on January 1, 2020. Users who want to continue to receive support related to Python 2.7 after this date will need to pay a commercial provider.

Related recommendations: "Python Tutorial"

The above is the detailed content of Why is it called Python?. For more information, please follow other related articles on the PHP Chinese website!

Statement
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn
Python vs. C  : Learning Curves and Ease of UsePython vs. C : Learning Curves and Ease of UseApr 19, 2025 am 12:20 AM

Python is easier to learn and use, while C is more powerful but complex. 1. Python syntax is concise and suitable for beginners. Dynamic typing and automatic memory management make it easy to use, but may cause runtime errors. 2.C provides low-level control and advanced features, suitable for high-performance applications, but has a high learning threshold and requires manual memory and type safety management.

Python vs. C  : Memory Management and ControlPython vs. C : Memory Management and ControlApr 19, 2025 am 12:17 AM

Python and C have significant differences in memory management and control. 1. Python uses automatic memory management, based on reference counting and garbage collection, simplifying the work of programmers. 2.C requires manual management of memory, providing more control but increasing complexity and error risk. Which language to choose should be based on project requirements and team technology stack.

Python for Scientific Computing: A Detailed LookPython for Scientific Computing: A Detailed LookApr 19, 2025 am 12:15 AM

Python's applications in scientific computing include data analysis, machine learning, numerical simulation and visualization. 1.Numpy provides efficient multi-dimensional arrays and mathematical functions. 2. SciPy extends Numpy functionality and provides optimization and linear algebra tools. 3. Pandas is used for data processing and analysis. 4.Matplotlib is used to generate various graphs and visual results.

Python and C  : Finding the Right ToolPython and C : Finding the Right ToolApr 19, 2025 am 12:04 AM

Whether to choose Python or C depends on project requirements: 1) Python is suitable for rapid development, data science, and scripting because of its concise syntax and rich libraries; 2) C is suitable for scenarios that require high performance and underlying control, such as system programming and game development, because of its compilation and manual memory management.

Python for Data Science and Machine LearningPython for Data Science and Machine LearningApr 19, 2025 am 12:02 AM

Python is widely used in data science and machine learning, mainly relying on its simplicity and a powerful library ecosystem. 1) Pandas is used for data processing and analysis, 2) Numpy provides efficient numerical calculations, and 3) Scikit-learn is used for machine learning model construction and optimization, these libraries make Python an ideal tool for data science and machine learning.

Learning Python: Is 2 Hours of Daily Study Sufficient?Learning Python: Is 2 Hours of Daily Study Sufficient?Apr 18, 2025 am 12:22 AM

Is it enough to learn Python for two hours a day? It depends on your goals and learning methods. 1) Develop a clear learning plan, 2) Select appropriate learning resources and methods, 3) Practice and review and consolidate hands-on practice and review and consolidate, and you can gradually master the basic knowledge and advanced functions of Python during this period.

Python for Web Development: Key ApplicationsPython for Web Development: Key ApplicationsApr 18, 2025 am 12:20 AM

Key applications of Python in web development include the use of Django and Flask frameworks, API development, data analysis and visualization, machine learning and AI, and performance optimization. 1. Django and Flask framework: Django is suitable for rapid development of complex applications, and Flask is suitable for small or highly customized projects. 2. API development: Use Flask or DjangoRESTFramework to build RESTfulAPI. 3. Data analysis and visualization: Use Python to process data and display it through the web interface. 4. Machine Learning and AI: Python is used to build intelligent web applications. 5. Performance optimization: optimized through asynchronous programming, caching and code

Python vs. C  : Exploring Performance and EfficiencyPython vs. C : Exploring Performance and EfficiencyApr 18, 2025 am 12:20 AM

Python is better than C in development efficiency, but C is higher in execution performance. 1. Python's concise syntax and rich libraries improve development efficiency. 2.C's compilation-type characteristics and hardware control improve execution performance. When making a choice, you need to weigh the development speed and execution efficiency based on project needs.

See all articles

Hot AI Tools

Undresser.AI Undress

Undresser.AI Undress

AI-powered app for creating realistic nude photos

AI Clothes Remover

AI Clothes Remover

Online AI tool for removing clothes from photos.

Undress AI Tool

Undress AI Tool

Undress images for free

Clothoff.io

Clothoff.io

AI clothes remover

AI Hentai Generator

AI Hentai Generator

Generate AI Hentai for free.

Hot Tools

Notepad++7.3.1

Notepad++7.3.1

Easy-to-use and free code editor

SecLists

SecLists

SecLists is the ultimate security tester's companion. It is a collection of various types of lists that are frequently used during security assessments, all in one place. SecLists helps make security testing more efficient and productive by conveniently providing all the lists a security tester might need. List types include usernames, passwords, URLs, fuzzing payloads, sensitive data patterns, web shells, and more. The tester can simply pull this repository onto a new test machine and he will have access to every type of list he needs.

PhpStorm Mac version

PhpStorm Mac version

The latest (2018.2.1) professional PHP integrated development tool

Atom editor mac version download

Atom editor mac version download

The most popular open source editor

ZendStudio 13.5.1 Mac

ZendStudio 13.5.1 Mac

Powerful PHP integrated development environment