Python is written in C language. Python is an object-oriented dynamically typed language. Its bottom layer is written in C language. Many standard libraries and third-party libraries are also written in C language. The Python interpreter is easy to expand and can use C language or C ( or other languages callable from C) extend new functionality and data types.

The operating environment of this tutorial: Windows 7 system, Python 3.9.1, DELL G3 computer.
Python is written in C language.
Python was designed in the early 1990s by Guido van Rossum of the Dutch Society for Mathematics and Computer Science as a replacement for a language called ABC. Python provides efficient high-level data structures and enables simple and effective object-oriented programming. Python's syntax and dynamic typing, as well as the nature of an interpreted language, make it a programming language for scripting and rapid application development on most platforms. With the continuous update of the version and the addition of new language features, it is gradually used for independent, large-scale Project development.
The bottom layer of Python is written in C language. Many standard libraries and third-party libraries are also written in C and run very fast.
The Python interpreter is easily extensible and can be extended with new functions and data types using the C language or C (or other languages that can be called through C). Python can also be used as an extension programming language in customizable software. Python's rich standard library provides source code or machine code suitable for each major system platform.
Python itself is designed to be extensible. Not all features and functionality are integrated into the language core. Python provides a wealth of APIs and tools so that programmers can easily use C language, C, and Cython to write expansion modules. The Python compiler itself can also be integrated into other programs that require a scripting language. Therefore, many people also use Python as a "glue language". Use Python to integrate and encapsulate programs written in other languages. Many projects within Google, such as Google Engine, use C to write parts with extremely high performance requirements, and then use Python or Java/Go to call the corresponding modules. Alex Martelli, author of "Python Technical Manual" said: "It's hard to say, but in 2004, Python was already used internally at Google. Google recruited many Python experts, but it had already decided to use Python before that. , their purpose is Python where we can, C where we must, use C when controlling hardware, and use Python during rapid development."
You can embed Python into C/C programs to provide program users with Provides scripting functionality.
Have you raised your interest in learning? Then go to the Python video tutorial on the PHP Chinese website to learn more!
The above is the detailed content of What language is python written in?. For more information, please follow other related articles on the PHP Chinese website!
Python vs. C : Learning Curves and Ease of UseApr 19, 2025 am 12:20 AMPython 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 ControlApr 19, 2025 am 12:17 AMPython 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 LookApr 19, 2025 am 12:15 AMPython'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 ToolApr 19, 2025 am 12:04 AMWhether 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 LearningApr 19, 2025 am 12:02 AMPython 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?Apr 18, 2025 am 12:22 AMIs 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 ApplicationsApr 18, 2025 am 12:20 AMKey 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 EfficiencyApr 18, 2025 am 12:20 AMPython 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.


Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

DVWA
Damn Vulnerable Web App (DVWA) is a PHP/MySQL web application that is very vulnerable. Its main goals are to be an aid for security professionals to test their skills and tools in a legal environment, to help web developers better understand the process of securing web applications, and to help teachers/students teach/learn in a classroom environment Web application security. The goal of DVWA is to practice some of the most common web vulnerabilities through a simple and straightforward interface, with varying degrees of difficulty. Please note that this software

Zend Studio 13.0.1
Powerful PHP integrated development environment

SublimeText3 Mac version
God-level code editing software (SublimeText3)

mPDF
mPDF is a PHP library that can generate PDF files from UTF-8 encoded HTML. The original author, Ian Back, wrote mPDF to output PDF files "on the fly" from his website and handle different languages. It is slower than original scripts like HTML2FPDF and produces larger files when using Unicode fonts, but supports CSS styles etc. and has a lot of enhancements. Supports almost all languages, including RTL (Arabic and Hebrew) and CJK (Chinese, Japanese and Korean). Supports nested block-level elements (such as P, DIV),

PhpStorm Mac version
The latest (2018.2.1) professional PHP integrated development tool






