search
HomeBackend DevelopmentPython TutorialPython is a cross-platform, open source, free high-level dynamic programming language, right?

Python is a cross-platform, open source, free high-level dynamic programming language, right?

Jul 08, 2020 pm 02:35 PM
pythonfreeOpen sourceprogramming languageCross-platform

Python is a cross-platform, open source, free high-level dynamic programming language, yes. Python has the advantages of simplicity, easy to learn, fast speed, free, open source, portability, scalability, and rich libraries. The Python language is extremely easy to get started. It is a language that represents simplicity.

Python is a cross-platform, open source, free high-level dynamic programming language, right?

Python is a cross-platform, open source, free high-level dynamic programming language, yes.

(Recommended tutorial: python tutorial)

Related introduction:

Advantages of python:

Simple: Python It is a language that represents the idea of ​​simplicity. It allows you to focus on solving problems rather than figuring out the language itself.

Easy to learn: Python is extremely easy to get started because Python has extremely simple documentation.

Fast speed: The bottom layer of Python is written in C language, and many standard libraries and third-party libraries are also written in C, which runs very fast.

Free and open source: Python is one of FLOSS (Free/Open Source Software). Users are free to distribute copies of this software, read its source code, make changes to it, and use parts of it in new free software. FLOSS is based on the concept of a group sharing knowledge.

Portability: Due to its open source nature, Python has been ported on many platforms (with modifications to enable it to work on different platforms).

Interpretability: A program written in a compiled language such as C or C can be converted from a source file (i.e. C or C language) into a language used by your computer (binary code, i.e. 0s and 1s) . This process is done through the compiler and different flags and options.

Object-oriented: Python supports both procedural and object-oriented programming. In "procedural-oriented" languages, programs are built from procedures or simply functions that are reusable code.

Scalability: If you need a critical piece of code to run faster or you want some algorithms not to be public, you can write part of the program in C or C and then use them in a Python program.

Embeddability: Python can be embedded into C/C programs to provide scripting functions to program users.

Rich library: The Python standard library is indeed huge. It can help with various tasks including regular expressions, document generation, unit testing, threading, databases, web browsers, CGI, FTP, email, XML, XML-RPC, HTML, GUI (Graphical User Interface), Tk and other system-related operations. In addition to the standard library, there are many other high-quality libraries, such as wxPython, Twisted, and the Python imaging library, among others.

Standardized code: Python uses forced indentation to make the code more readable. Programs written in Python do not need to be compiled into binary code.

The above is the detailed content of Python is a cross-platform, open source, free high-level dynamic programming language, right?. 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

Video Face Swap

Video Face Swap

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

Hot Tools

SublimeText3 Linux new version

SublimeText3 Linux new version

SublimeText3 Linux latest version

Dreamweaver Mac version

Dreamweaver Mac version

Visual web development tools

ZendStudio 13.5.1 Mac

ZendStudio 13.5.1 Mac

Powerful PHP integrated development environment

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.

SublimeText3 Mac version

SublimeText3 Mac version

God-level code editing software (SublimeText3)