"详细完整版 Python.ppt,开源、面向对象编程语言值得借鉴下载使用"
171 浏览量
更新于2024-03-11
收藏 286KB PPT 举报
Python.ppt is a detailed and complete document that provides an introduction to Python programming language. It is a valuable resource that can be used for reference and is available for download, with the author offering assistance for any questions that may arise.
The document begins by introducing Python as an open-source, high-level, and object-oriented programming language. It highlights the elegant syntax and strong readability of Python, making it a popular choice for developers. The language's support for features such as classes and multiple inheritance in object-oriented programming is also emphasized.
Furthermore, Python's compatibility with various computer platforms and operating systems, including Unix, Windows, MacOS, and OS/2, is described. The process of installing Python is outlined, with users directed to the official Python website for guidance. Additionally, the document provides instructions for running Python scripts, including interactive running on Windows platforms with a graphical user interface, executing Python script files, and running programs in a Linux/UNIX environment.
In summary, Python.ppt is a comprehensive resource for those seeking to learn about Python programming. Its thorough coverage of the language's features and functionality, along with its availability for download, make it a valuable tool for both beginners and experienced programmers. With the author's willingness to provide assistance, this document serves as a valuable resource for anyone interested in learning and using Python.
2021-11-10 上传
2022-10-20 上传
2023-06-12 上传
2021-11-12 上传
是空空呀
- 粉丝: 192
- 资源: 3万+
最新资源
- MATLAB实现小波阈值去噪:Visushrink硬软算法对比
- 易语言实现画板图像缩放功能教程
- 大模型推荐系统: 优化算法与模型压缩技术
- Stancy: 静态文件驱动的简单RESTful API与前端框架集成
- 掌握Java全文搜索:深入Apache Lucene开源系统
- 19计应19田超的Python7-1试题整理
- 易语言实现多线程网络时间同步源码解析
- 人工智能大模型学习与实践指南
- 掌握Markdown:从基础到高级技巧解析
- JS-PizzaStore: JS应用程序模拟披萨递送服务
- CAMV开源XML编辑器:编辑、验证、设计及架构工具集
- 医学免疫学情景化自动生成考题系统
- 易语言实现多语言界面编程教程
- MATLAB实现16种回归算法在数据挖掘中的应用
- ***内容构建指南:深入HTML与LaTeX
- Python实现维基百科“历史上的今天”数据抓取教程