排序算法

说明：  使用Python语言在数字设计中，有很多优势比如算法建模，RTL模板生成等优势(Use Python in ASIC design)

利用python编程应用在社交网络算法在金融反欺诈中，在社区内使用最短路径算法来发现失联用户与一个正常还款用户的关系链 分析指标：degree、closeness centrality、betweenness centrality、cluster coefficient、triangle count、connected components算法：PageRank社区发现：GN、FastUnfolding、LPA、SLPA、WalkTrap

基于python开发环境，再哈工大LTP语义依存分析的基础之上抽取出知识三元组（主，谓语，宾）

一个仿照网易云音乐的音乐播放器，?pyQT6 +python3.6，谢谢支持(A replica of the wangyiyun music music player, pyQT6 +python3.6, thank you for your support)

运用python进行模糊聚类分析步骤如下：建立数据矩阵；数据标准化；建立模糊相似矩阵；改造相似关系为等价关系；确定分类数(The steps of Python fuzzy clustering analysis are as follows: establishing data matrix; standardizing data; establishing fuzzy similarity matrix; transforming similarity relation into equivalence relation; determining classification number.)

说明：  新闻发布系统是一个新闻单位不可缺少的部分,它的内容对于新闻的决策者和管理者来说都至关重要,所以新闻发布系统应该能够为用户提供充足的信息和快捷的查询手段。但一直以来人们使用传统人工的方式管理文件档案，这种管理方式存在着许多缺点,如:效率低、保密性差,另外时间一长,将产生大量的文件和数据,这对于查找、更新和维护都带来了不少的困难。 本系统功能的设计与实现，包括新闻创建、新闻浏览、新闻发布、撤销，新闻删除有，方便用户上手使用。本系统具有很好的外部接口，能够很好的配合站点的其它子系统服务于web新闻发布。(Press release system is an indispensable part of a news unit. Its content is very important for news decision-makers and managers. Therefore, news release system should be able to provide users with sufficient information and fast means of inquiry. But people have been using the traditional manual way to manage documents and archives, which has many shortcomings, such as low efficiency, poor confidentiality, and a long time, will produce a large number of documents and data, which brings many difficulties to search, update and maintain. The design and implementation of the system functions, including news creation, news browsing, news release, cancellation, news deletion, user-friendly use. The system has a good external interface, and can cooperate with other subsystems of the site to serve the web news release.)

注意：请勿用于商业目的，仅供学习参考！！！python自动化测试开发框架

说明：  可以简单地走一个小迷宫，程序尚不完善,希望收到指导意见(can simply walk through a small maze, and the procedure is not perfect yet.)

说明：  经典书籍，think python,第二版。(think python, second edition. written by Allen B. Downey.)

 ------------| EnhanceNet | ------------This is a pre-trained reference implementation of ENet-PAT from "EnhanceNet:Single Image Super-Resolution through Automated Texture Synthesis" for amagnification ratio of 4.It comes with a script which takes care of installing all necessary packagesinside a virtual environment, i.e. all installations take place inside thefolder and can be simply uninstalled by deleting the folder. Advanced usersmay install the packages directly (see FAQ section).Please note that the code has only been tested on Linux and OS/X.If you use this code as part of a publication, please cite:@inproceedings{enhancenet,  title={{EnhanceNet}:         Single Image Super-Resolution through Automated Texture Synthesis},  author={Sajjadi, Mehdi~S.~M. and Sch{"o}lkopf, Be