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PyWebIO v1.3.0 Documentation

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02 HTML 杨亮《PHP语⾔程序设计》

f/97afc4c0014943db941db1c2eba5e144/p7_2.jpg) 检索网页内容的搜索引擎 ![Image](/uploads/documents/9/7/a/f/97afc4c0014943db941db1c2eba5e144/p7_3.jpg) 将HTML变成网页的浏览器 ## HTML代码要做到 - 只是代表内容和结构，和表现无关 - 清晰的结构性 - 充分的语义性 jpg) ## 网页的头部 1、你要告诉浏览器此网页的基本信息 2、你要告诉搜索引擎的基本信息 3、需要包含的其他的脚本，如CSS、JS 4、不包含任何要显示的内容网页的主体部分 1、所有网页中的具体内容网页文件名字：字母、数字、下划线网页文件后缀：.htm或.html 默认首页：index.htm或index.html ## 网页头部存放信息 Tianjin content="php,html,stefyang"/> <meta http-equiv="Content-Type" content="text/html; charset=utf-8"/> ## <mark>网页</mark>主体部分 ## 基础文字显示部分 |1|<html>| |---|---| |2|<head></head>| |3|<body>| |4|This</div> <div class="doc-info" data-v-2d813be8><span data-v-2d813be8>0 码力 | 20 页 | 2.44 MB <span class="hidden-xs-only" data-v-2d813be8>| 2 年前</span></span> <div role="slider" aria-valuenow="3" aria-valuetext="3" aria-valuemin="0" aria-valuemax="5" tabindex="0" class="el-rate float-right" data-v-2d813be8><span class="el-rate__item" style="cursor:auto;"><i class="el-rate__icon el-icon-star-on" 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style="cursor:auto;"><i class="el-rate__icon el-icon-star-on" style="color:#EFF2F7;"></i></span><span class="el-rate__item" style="cursor:auto;"><i class="el-rate__icon el-icon-star-on" style="color:#EFF2F7;"></i></span><span class="el-rate__text" style="color:#ff9900;">3</span></div></div></li><li data-v-2d813be8><h3 class="doc-title" data-v-2d813be8><a href="/document/0a5c3ad7415b1e94" target="_blank" class="el-link el-link--primary" data-v-2d813be8><img src="/static/images/pdf_24.png" alt="pdf文档" data-v-2d813be8> <span data-v-2d813be8>Julia 1.7.0 DEV Documentation</span></a></h3> <div class="doc-desc" data-v-2d813be8></div> <div class="doc-info" data-v-2d813be8><span data-v-2d813be8>0 码力 | 1399 页 | 4.59 MB <span class="hidden-xs-only" data-v-2d813be8>| 2 年前</span></span> <div role="slider" aria-valuenow="3" aria-valuetext="3" aria-valuemin="0" aria-valuemax="5" tabindex="0" class="el-rate float-right" data-v-2d813be8><span class="el-rate__item" style="cursor:auto;"><i class="el-rate__icon el-icon-star-on" style="color:#F7BA2A;"></i></span><span class="el-rate__item" style="cursor:auto;"><i class="el-rate__icon el-icon-star-on" style="color:#F7BA2A;"></i></span><span class="el-rate__item" style="cursor:auto;"><i class="el-rate__icon el-icon-star-on" style="color:#F7BA2A;"></i></span><span class="el-rate__item" style="cursor:auto;"><i class="el-rate__icon el-icon-star-on" style="color:#EFF2F7;"></i></span><span class="el-rate__item" style="cursor:auto;"><i class="el-rate__icon el-icon-star-on" style="color:#EFF2F7;"></i></span><span class="el-rate__text" style="color:#ff9900;">3</span></div></div></li><li data-v-2d813be8><h3 class="doc-title" data-v-2d813be8><a href="/document/be2ed06f574839fb" target="_blank" class="el-link el-link--primary" data-v-2d813be8><img src="/static/images/pdf_24.png" alt="pdf文档" data-v-2d813be8> <span data-v-2d813be8>Julia 1.12.0 DEV Documentation</span></a></h3> <div class="doc-desc" data-v-2d813be8></div> <div class="doc-info" data-v-2d813be8><span data-v-2d813be8>0 码力 | 2009 页 | 6.72 MB <span class="hidden-xs-only" data-v-2d813be8>| 2 年前</span></span> <div role="slider" aria-valuenow="3" aria-valuetext="3" aria-valuemin="0" aria-valuemax="5" tabindex="0" class="el-rate float-right" data-v-2d813be8><span class="el-rate__item" style="cursor:auto;"><i class="el-rate__icon el-icon-star-on" style="color:#F7BA2A;"></i></span><span class="el-rate__item" style="cursor:auto;"><i class="el-rate__icon el-icon-star-on" style="color:#F7BA2A;"></i></span><span class="el-rate__item" style="cursor:auto;"><i class="el-rate__icon el-icon-star-on" style="color:#F7BA2A;"></i></span><span class="el-rate__item" style="cursor:auto;"><i class="el-rate__icon el-icon-star-on" style="color:#EFF2F7;"></i></span><span class="el-rate__item" style="cursor:auto;"><i class="el-rate__icon el-icon-star-on" style="color:#EFF2F7;"></i></span><span class="el-rate__text" style="color:#ff9900;">3</span></div></div></li><li data-v-2d813be8><h3 class="doc-title" data-v-2d813be8><a href="/document/4e6a1248d8b8f155" target="_blank" class="el-link el-link--primary" data-v-2d813be8><img src="/static/images/pdf_24.png" alt="pdf文档" data-v-2d813be8> <span data-v-2d813be8>4 【王琼】容器监控架构演进王琼 YY直播 </span></a></h3> <div class="doc-desc" data-v-2d813be8>监控维度更多，除了传统物理集群的监控，还包括核心服务监控（API server，Etcd等）、容器监控、Pod监控、Namespace监控等 ● 监控对象<mark>动态</mark>可变，在集群中容器的销毁创建十分频繁，无法提前预置监控指标随着容器规模爆炸式增长，如何处理及展示大量监控数据随着集群<mark>动态</mark>增长，监控系统必须具备<mark>动态</mark>扩缩的能力 ## 监控遇上 Kubernetes 目前容器云平台提供的k8s集群包括： 10+集群（云+物理机房+边缘） resource_requests_memory:label_biz_type ## Thanos + Kvass ## Kvass是一个Prometheus横向扩缩容解决方案他使用Sidecar<mark>动态</mark>得根据Coordinator分配下来的target列表来为每个Prometheus生成只含特定target的配置文件，从而将采集任务分散到各个Prometheus分片。 Coordinator用于 et的时候，会根据target的实际规模来，而不是通过hashmod来，所以每个分片的总负载会被控制在一个阈值以下，不会出现某个分片OOM的情况。 ● 自动扩缩容：Kvass会根据当前集群的规模，<mark>动态</mark>调整分片个数 ![Image](/uploads/documents/b/2/d/7/b2d703128539524d374d63151f676cb3/p13_1.jpg) ## Thanos +</div> <div class="doc-info" data-v-2d813be8><span data-v-2d813be8>0 码力 | 23 页 | 2.17 MB <span class="hidden-xs-only" data-v-2d813be8>| 2 年前</span></span> <div role="slider" aria-valuenow="3" aria-valuetext="3" aria-valuemin="0" aria-valuemax="5" tabindex="0" class="el-rate float-right" data-v-2d813be8><span class="el-rate__item" style="cursor:auto;"><i class="el-rate__icon el-icon-star-on" style="color:#F7BA2A;"></i></span><span class="el-rate__item" style="cursor:auto;"><i class="el-rate__icon el-icon-star-on" style="color:#F7BA2A;"></i></span><span class="el-rate__item" style="cursor:auto;"><i class="el-rate__icon el-icon-star-on" style="color:#F7BA2A;"></i></span><span class="el-rate__item" style="cursor:auto;"><i class="el-rate__icon el-icon-star-on" style="color:#EFF2F7;"></i></span><span class="el-rate__item" style="cursor:auto;"><i class="el-rate__icon el-icon-star-on" style="color:#EFF2F7;"></i></span><span class="el-rate__text" style="color:#ff9900;">3</span></div></div></li><li data-v-2d813be8><h3 class="doc-title" data-v-2d813be8><a href="/document/919817273bc11d12" target="_blank" class="el-link el-link--primary" data-v-2d813be8><img src="/static/images/pdf_24.png" alt="pdf文档" data-v-2d813be8> <span data-v-2d813be8>Hello 算法 1.0.0 Golang版</span></a></h3> <div class="doc-desc" data-v-2d813be8>学批评指正。本书中的代码附有可一键运行的源文件，托管于 github.com/krahets/hello-algo 仓库。动画在 PDF 内的展示效果受限，可访问 hello-algo.com <mark>网页</mark>版以获得更优的阅读体验。 ## 推荐语 “一本通俗易懂的数据结构与算法入门书，引导读者手脑并用地学习，强烈推荐算法初学者阅读！” ——邓俊辉，清华大学计算机系教授 “如果我当年学数据结构与算法的时候有《Hello 第13章回溯 13.1 回溯算法 13.2 全排列问题 13.3 子集和问题 13.4 n 皇后问题 13.5 小结第14章 <mark>动态</mark>规划 14.1 初探<mark>动态</mark>规划 14.2 <mark>动态</mark>规划问题特性 14.3 <mark>动态</mark>规划解题思路 14.4 0-1 背包问题 14.5 完全背包问题 14.6 编辑距离问题 14.7 小结第 15 章贪心 15.1 贪心算法等。数据结构：基本数据类型和数据结构的分类方法。数组、链表、栈、队列、哈希表、树、堆、图等数据结构的定义、优缺点、常用操作、常见类型、典型应用、实现方法等。 · 算法：搜索、排序、分治、回溯、<mark>动态</mark>规划、贪心等算法的定义、优缺点、效率、应用场景、解题步骤和示例问题等。 ![Image](/uploads/documents/3/e/b/2/3eb28f4b59465ff9d753a268eab4c5b5/p9_1</div> <div class="doc-info" data-v-2d813be8><span data-v-2d813be8>0 码力 | 382 页 | 17.60 MB <span class="hidden-xs-only" data-v-2d813be8>| 2 年前</span></span> <div role="slider" aria-valuenow="3" aria-valuetext="3" aria-valuemin="0" aria-valuemax="5" tabindex="0" class="el-rate float-right" data-v-2d813be8><span class="el-rate__item" style="cursor:auto;"><i class="el-rate__icon el-icon-star-on" style="color:#F7BA2A;"></i></span><span class="el-rate__item" style="cursor:auto;"><i class="el-rate__icon el-icon-star-on" style="color:#F7BA2A;"></i></span><span class="el-rate__item" style="cursor:auto;"><i class="el-rate__icon el-icon-star-on" style="color:#F7BA2A;"></i></span><span class="el-rate__item" style="cursor:auto;"><i class="el-rate__icon el-icon-star-on" style="color:#EFF2F7;"></i></span><span class="el-rate__item" style="cursor:auto;"><i class="el-rate__icon el-icon-star-on" style="color:#EFF2F7;"></i></span><span class="el-rate__text" style="color:#ff9900;">3</span></div></div></li><li data-v-2d813be8><h3 class="doc-title" data-v-2d813be8><a href="/document/1f1da4abc88ed60e" target="_blank" class="el-link el-link--primary" data-v-2d813be8><img src="/static/images/ppt_24.png" alt="ppt文档" data-v-2d813be8> <span data-v-2d813be8>C++高性能并行编程与优化 - 课件 - 08 CUDA 开启的 GPU 编程</span></a></h3> <div class="doc-desc" data-v-2d813be8>进一步：核函数调用核函数从 Keller 架构开始，___global___ 里可以调用另一个 ___global___，也就是说核函数可以调用另一个核函数，且其三重尖括号里的板块数和线程数可以<mark>动态</mark>指定，无需先传回到 CPU 再进行调用，这是 CUDA 特有的能力 kernel: Thread 0 of 3 kernel: Thread 1 of 3 kernel: Thread 2 of of 5 another: Thread 3 of 5 another: Thread 4 of 5 常用于这种情况：需要从 GPU 端<mark>动态</mark>计算出 blockDim 和 gridDim，而又不希望导回数据到 CPU 导致强制同步影响性能。这种模式被称为<mark>动态</mark>并行（dynamic parallelism），OpenGL 有一个 glDispatchComputeIndirect 的 API 和这个很像，但毕竟没有 65532 arr[65533]: 65533 arr[65534]: 65534 ## 网格跨步循环：应用于线程和板块一起上的情况 - 网格跨步循环实际上本来是这样，利用扁平化的线程数量和线程编号实现<mark>动态</mark>大小。 - 同样，无论调用者指定每个板块多少线程（blockDim），总共多少板块（gridDim）。都能自动根据给定的 n 区间循环，不会越界，也不会漏掉几个元素。 - 这样一个 for 循环非常符合</div> <div class="doc-info" data-v-2d813be8><span data-v-2d813be8>0 码力 | 142 页 | 13.52 MB <span class="hidden-xs-only" data-v-2d813be8>| 2 年前</span></span> <div role="slider" aria-valuenow="3" aria-valuetext="3" aria-valuemin="0" aria-valuemax="5" tabindex="0" class="el-rate float-right" data-v-2d813be8><span class="el-rate__item" style="cursor:auto;"><i class="el-rate__icon el-icon-star-on" style="color:#F7BA2A;"></i></span><span class="el-rate__item" style="cursor:auto;"><i class="el-rate__icon el-icon-star-on" style="color:#F7BA2A;"></i></span><span class="el-rate__item" style="cursor:auto;"><i class="el-rate__icon el-icon-star-on" style="color:#F7BA2A;"></i></span><span class="el-rate__item" style="cursor:auto;"><i class="el-rate__icon el-icon-star-on" style="color:#EFF2F7;"></i></span><span class="el-rate__item" 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APISIX",14,"Docker","Hadoop","Harbor","Istio","Serverless","云原生CNCF","机器学习","边缘计算","Angular","Dart","Electron","Flutter","HTML\u002FCSS",393,"PWA","TypeScript","Android","DevOps","iOS","Jenkins",422,"Linux",794,"Cilium","Nginx","Shell","Windows","Zabbix",658,"Blender","Krita",454,"人工智能",795,"DataEase","Server","_self","default",806,"PyWebIO",52,429,23,500,458,400,24,461,30,507,437,525,"算法","Spark",25,Array(6),"",2026,"后端开发",2590,"\u002F\u002Fwenku.it\u002Fuploads\u002Ff\u002F0\u002Fb\u002F8\u002Fa\u002Ff0b8aacdb939e3a464cb3568d136b744.jpeg","\u002F\u002Fwenku.it\u002Fuploads\u002F7\u002Ff\u002Ff\u002Ff\u002F8\u002F7fff8eee8d7d3c729ac86eee0a87062f.png","后端开发是指在构建网站或应用时负责处理服务器端逻辑、数据库管理和与前端交互的程序员工作领域。",441,".Net",".NET平台开发，包括ASP.NET、.NET Core、C#及相关框架与运行时。","C#语言语法、核心特性、面向对象编程及在.NET中的应用。","C++","C++语言特性、STL、内存管理、多线程及高性能编程相关内容。",802,"Conan","Conan 是一个开源的、去中心化的 C\u002FC++ 包管理器，它在所有平台和所有构建系统及编译器中都能工作。\n",443,"Crystal 是一种性能卓越的静态类型编程语言，它结合了Ruby的语法优雅和C语言的执行效率，适用于构建高效且易于维护的软件应用。",442,"C语言","C语言是一种通用、过程式的计算机编程语言，支持结构化编程、词汇变量作用域和递归等功能，是众多编程语言的基础，广泛应用于系统软件和应用软件的开发。",445,"Deno是由Node.js的创始人Ryan Dahl开发的一款现代的、安全的JavaScript和TypeScript运行时，具有内置的依赖管理和更强调安全性的特点。",792,"ffmpeg","FFmpeg多媒体处理工具，涵盖音视频编解码、转码、滤镜及命令行使用。",216,"Go语言（Golang）是一门由Google开发的开源编程语言，以简洁、高效、并发支持和内置垃圾回收等特性而闻名，适用于构建可靠、高性能的软件应用。",418,"GraphQL","GraphQL查询语言、服务端实现、客户端库、Schema设计及性能优化。",455,"Idris","Idris是一种函数式编程语言，它支持类型推断和强类型系统，特别强调可证明的正确性。","Java是一种通用的、跨平台的、面向对象的编程语言，广泛应用于企业级开发、移动应用开发、网络编程和大数据处理等领域。",791,48,"Apache ActiveMQ是Apache软件基金会所研发的开放源码消息中间件；由于ActiveMQ是一个纯Java程序，因此只需要操作系统支持Java虚拟机，ActiveMQ便可执行。","Apache Unomi","Apache Unomi™（发音为“You know me”）是一个Java开源客户数据平台，一个旨在管理客户、潜在客户和访客数据的Java服务器，并帮助个性化客户体验，同时还提供尊重访客隐私规则（如GDPR）的功能。\n\n",788,"Apacke Wicket","Apache Wicket是一个基于Java的开源、面向对象的Web应用程序框架，它强调视图与业务逻辑的分离，提供组件化的开发模型，使得Web应用程序的开发更加简单、快速和可维护。",782,"Spring",327,"Spring框架及其生态，包括Spring Boot、Spring Cloud、IoC\u002FAOP及配置。",122,"Julia是一种高性能、通用、动态编程语言，特别适用于科学计算、数据分析和高性能计算领域。",398,"Kotlin",15,"Kotlin是一种由JetBrains开发的静态编程语言，旨在提供更简洁、更安全的代码，与Java完全互操作，并已成为Android官方支持的开发语言之一。",508,"Lean","Lean 是一种强大且灵活的函数式编程语言，它以简洁的语法、严格的类型检查和高效的编译器为特点，特别适用于形式化验证和定理证明等领域。",505,"Makefile","Makefile是一个工程化的编译方法，它通过一个文本文件来描述源文件之间的依赖关系以及编译和链接的规则，使得编译工作可以自动化进行。",801,37,"Nim 是一种静态类型的、编译型、系统编程语言，它结合了 Python、Ada 和 Modula 等成熟语言的成功概念。\n","Node.js 是一个基于 Chrome V8 引擎的 JavaScript 运行环境，允许开发者在服务器端运行 JavaScript，构建高效、可扩展的网络应用。",415,"Express.js","Express.js 是一个基于 Node.js 平台的轻量级、快速、无开销的 Web 应用开发框架，用于构建 Web 服务器和 API。",513,"Pascal","Pascal是一种过程式编程语言，具有结构化、强类型等特点，适用于教学和学术领域，以及编写应用程序和系统软件。",99,"PHP 是一种创建动态交互性站点的强有力的服务器端脚本语言，广泛用于 Web 开发以生成动态网页内容。",448,"CakePHP","CakePHP是一个快速、安全的PHP框架，用于构建高效、可靠且易于维护的Web应用程序。",486,"Falcon","Falcon是一个高效、轻量级的PHP框架，它提供了一整套开发Web应用程序所需的工具和功能，帮助开发者快速构建稳定、可扩展的应用程序。",456,"Laravel","Laravel 是一个由Taylor Otwell所建立，自由开源的 PHP Web 框架，旨在实现的Web软件的MVC架构，并作为CodeIgniter的替代方案。","Python 是一种解释型、高级编程、通用编程语言，以简洁易读、功能强大、应用广泛和拥有丰富库支持而著称。",783,51,"Celery是一个简单、灵活且可靠的分布式任务队列，用于处理大量消息和异步任务调度，支持在多个机器、进程或线程上执行任务，并提供了丰富的异常处理和结果存储功能。\n\n",809,"Conda",33,"Conda包与环境管理工具，用于Python\u002FR等科学计算环境的创建与维护。",411,95,"Django是一个高级的Python Web框架，它快速、安全且易于维护，适用于各种Web应用程序的开发。",412,"Flask是一个基于Python的轻量级Web应用框架，它简单易用，功能强大，支持扩展，适合快速构建Web服务和RESTful API。",503,"Jupyter","Jupyter是一个开源的交互式Web应用程序，支持运行多种编程语言，让用户能够创建和共享包含实时代码、方程、可视化和文本的文档，广泛应用于数据科学、机器学习和数据分析等领域。",798,"ORM","ORM 就是通过实例对象的语法，完成关系型数据库的操作的技术，是\"对象-关系映射\"（Object\u002FRelational Mapping）的缩写",786,"PyMuPDF","PyMuPDF是一个用于处理PDF文件的强大Python库，它提供了丰富的功能来解析、操作和生成PDF文档，包括数据提取、文本分析、图像处理等，且支持跨平台使用。",86,"PyWebIO 提供了一系列命令式的交互函数来在浏览器上获取用户输入和进行输出，将浏览器变成了一个“富\n文本终端”，可以用于构建简单的 Web 应用或基于浏览器的 GUI 应用。使用 PyWebIO，开发者能像编写终端脚本一样 (基于 input 和 print 进行交互) 来编写应用，无需具备 HTML 和 JS 的相关知识；PyWebIO 还可以方便地整合进现有的 Web 服务。非常适合快速构建对 UI 要求不高的应用。\n",504,"Scrapy","Scrapy是一个用于网络爬取的快速、高级的Python框架，能够方便地从网站上抓取结构化数据。",487,"Tornado","Tornado是一个用Python编写的轻量级Web服务器和Web应用框架，它采用异步非阻塞IO的处理方式，具有出色的抗负载能力和优异的性能，旨在解决C10K问题，即处理大于或等于一万的并发连接。",485,"RISC-V","RISC-V是一个基于精简指令集原则的开源指令集架构，简易解释为与开源软件运动相对应的一种“开源硬件”。","Ruby 是一种优雅的、面向对象的、简洁易学的动态编程语言，以其高效的开发效率和独特的元编程功能而广受欢迎。",413,"Rails","Ruby on Rails（简称 Rails）是一个基于 Ruby 语言的 Web 应用开发框架，以其简洁、优雅和高效的开发方式，帮助开发者快速构建复杂的 Web 应用程序。",493,79,"Rust是一种高效、安全且并发的系统编程语言，特别适用于构建高性能、低开销的软件，包括操作系统、网络应用、嵌入式设备等。",397,"Swift编程语言，用于iOS\u002FmacOS开发，包括语法、SwiftUI及框架。",477,"UML",98,"UML是一种广泛使用的软件建模语言，全称是Unified Modeling Language，是面向对象开发中一种通用的图形化建模语言。它综合了面向对象的建模语言、方法和过程，为软件开发的所有阶段提供模型化和可视化支持。",447,"其它语言","除主流语言外的其他编程语言，如Go、Rust、Ruby、Kotlin等话题。",491,"区块链是一种分布式数据库技术，它允许网络中的参与者在不需要中心化信任机构的情况下进行安全、可追溯、不可篡改的数据交换和传输。",467,"开发测试","软件测试方法、自动化测试框架、测试驱动开发及质量保证相关内容。",417,"微服务","微服务是一种将大型复杂应用程序拆分成多个小型、独立、可单独部署和扩展的服务的方法，每个服务都运行在自己的进程中，并使用轻量级通信机制进行通信。",785,"敏捷开发","敏捷开发是一种以人为核心、迭代、循序渐进的开发方法，它强调在快速变化的需求中通过高度的协作和灵活的响应来交付高质量的软件。",784,"架构设计","架构设计是指在软件或计算机系统的开发过程中，对系统进行整体的规划和设计，以满足特定需求和功能，并关注系统中各个组件之间的相互关系和交互方式，以降低系统的复杂性，提高系统的可理解性和可维护性。",481,"汇编语言","汇编语言是一种低级编程语言，它使用助记符（mnemonics）来代替机器语言中的二进制代码，使得程序员能够更容易地编写、理解和修改计算机程序。","\u002F\u002Fwenku.it\u002Fuploads\u002Fe\u002F0\u002Fc\u002Fe\u002F9\u002Fe0ce9096954e23a1a28197002e989b5f.jpg","\u002F\u002Fwenku.it\u002Fuploads\u002F7\u002Ff\u002F2\u002Fb\u002F9\u002F7f2b927210effe33346b9c827311e854.png","数据库是一种结构化组织和存储数据的系统，可方便地进行数据管理、检索和更新，提供有效的数据存储和访问机制。",506,"Apache Doris","Apache Doris是一个基于MPP架构的高性能实时分析数据库，以其亚秒级响应时间和支持超大数据集的能力，为实时数据分析提供了强大支持。",497,"Apache HBase","Apache HBase是一个开源的、分布式的、可扩展的、大数据存储系统，它利用Hadoop的HDFS作为其文件存储系统，并提供了类似于Google Bigtable的列式存储、高可靠性以及实时读写的能力。","Apache Cassandra是一套开源分布式NoSQL数据库系统。它最初由Meta开发，用于改善电子邮件系统的搜索性能的简单格式数据，集Google BigTable的数据模型与Amazon Dynamo的完全分布式架构于一身。",789,"ClickHouse是Yandex开源的一个高性能列式数据库管理系统，专为在线分析处理（OLAP）设计，能够使用SQL进行实时数据分析并生成报告。",430,"Firebase","Firebase云服务平台，包括数据库、认证、托管、函数及分析等功能。",446,"Firebird是一个开源的关系型数据库管理系统（RDBMS），具有高性能、轻量级和跨平台特性，适用于各种应用开发场景。",494,"Greenplum",43,"Greenplum数据库是一个基于PostgreSQL的分布式数据仓库，采用MPP架构，提供强大的并行计算能力和海量数据管理能力，适用于大数据分析和数据科学应用。",427,"MongoDB是一个高性能、开源的、无模式的文档型数据库，使用类似于JSON的BSON格式存储数据，提供灵活的数据结构和水平扩展能力。",425,"MySQL是一个开源的关系型数据库管理系统（RDBMS），现属于Oracle旗下，因其高性能、易用性和可靠性而广泛应用于各种数据存储和管理需求中。",800,"PieCloudDB","PieCloudDB是杭州拓数派科技发展有限公司（OpenPie）推出的云原生虚拟数仓数据库产品，它以云原生技术重构数据存储和计算，实现数据的高效管理、安全加密和弹性伸缩，支持AI和数据科学，为企业用户提供强大的数据计算基础设施。\n",426,76,"PostgreSQL是一个开源的关系型数据库管理系统，具有强大的扩展性和支持复杂数据类型的特点。",428,"Redis是一个开源的高性能内存数据库，以键值对存储数据，并支持丰富的数据结构和高级缓存功能。",468,"SQL语言基础、查询优化、数据库操作及常见关系型数据库使用技巧。",501,"SQLite是一款轻量级的关系型数据库管理系统，它不需要独立的服务器进程或操作系统支持，直接读写磁盘上的数据库文件，适用于嵌入式系统和移动应用。",492,"TiDB 是一个开源的分布式关系型数据库，兼容 MySQL 协议，设计目标是为云而生，提供高性能、水平扩展、高可用、易运维的分布式数据库解决方案。",499,"Vitess","Vitess是一个用于部署、扩展和管理大型MySQL实例集群的数据库解决方案。Vitess集MySQL数据库的很多重要特性和NoSQL数据库的可扩展性于一体。它的架构设计使得您可以像在物理机上一样在公共云或私有云架构中有效运行。它结合并扩展了许多重要的MySQL功能，同时兼具NoSQL数据库的可扩展性。 ","人大金仓(Kingbase)","Kingbase是一款面向大规模并发交易处理的企业级关系型数据库。该产品支持严格的ACID特性、结合多核架构的极致性能、行业最高的安全标准，以及完备的高可用方案，并提供可覆盖迁移、开发及运维管理全使用周期的智能便捷工具。产品融合了人大金仓在数据库领域几十年的产品研发和企业级应用经验，可满足各行业用户多种场景的数据处理需求。\n",451,34,"数据库中间件是位于应用程序和数据库管理系统之间的软件层，用于提供数据访问、连接管理和查询优化等功能，以简化数据库操作和提高系统性能。",432,"数据库优化","数据库性能调优，包括索引、查询计划、缓存、分区及配置优化方法。","数据库工具是用于管理、开发、迁移、备份和恢复数据库的软件工具。",512,"DBeaver","DBeaver是一款免费且开源的多平台数据库管理工具，支持多种数据库并具备丰富的数据库管理功能。",511,"Navicat是一款功能强大的数据库管理工具，支持多种数据库系统，提供直观易用的界面，帮助用户轻松管理、开发和维护数据库，适用于数据库管理员、开发人员及中小企业等多种用户群体。",787,"phpMyAdmin","phpMyAdmin是一个基于Web的MySQL数据库管理工具，它提供了友好的图形界面，帮助用户轻松进行数据库的查询、创建、修改和删除等操作。",431,"数据库设计","数据库模式设计、ER建模、规范化、反规范化及数据架构最佳实践。",816,"\u002F\u002Fwenku.it\u002Fuploads\u002Ff\u002F0\u002Fa\u002Fd\u002F2\u002Ff0ad2c0a9e46ee63f65bd12dadd14e12.jpeg","包括云服务、虚拟化、分布式存储、数据处理与分析等云计算和大数据技术。",779,"Apache APISIX API网关，动态路由、插件、负载均衡及微服务集成。",496,"Apache Flink","Apache Flink是一款高性能、通用的大数据处理引擎，用于进行实时数据流处理和批处理，具备精确一次的状态一致性语义和容错能力。",805,"Apache Karaf","Karaf是Apache旗下的一个开源项目。 Karaf同时也是一个基于OSGi的运行环境，Karaf提供了一个轻量级的OSGi容器，可以用于部署各种组件，应用程序。\n",495,"Apache Kyuubi","Apache Kyuubi 是一个为 Apache Spark 设计的多租户、高性能的 JDBC 网关服务，它提供了安全、可靠和高效的 Spark SQL 查询接入能力。",797,"Apache Ozone","Apache Ozone 是 Hadoop 的分布式对象存储系统，具有易扩展和冗余存储的特点。",462,"dapr","Dapr分布式应用运行时，提供微服务构建块如状态管理、发布订阅等。",457,"Docker容器技术，包括镜像构建、容器编排、Dockerfile及仓库管理。",473,"Hadoop是一个用于处理大数据的分布式计算框架，它可以在大规模集群上存储和处理数据，并提供了可扩展、可靠和高容错性的数据存储和处理能力。",799,"Harbor 是一个开源的注册表，它通过策略和基于角色的访问控制来保护工件，确保镜像被扫描且无漏洞，并作为可信的签名。作为 CNCF 毕业项目，Harbor 提供了合规性、性能和互操作性，帮助您在 Kubernetes 和 Docker 等云原生计算平台上一致且安全地管理工件。\n\n",460,"Istio服务网格，流量管理、安全策略、可观测性及多集群部署等。",87,"Kubernetes容器编排，Pod、Service、部署、存储及集群管理最佳实践。",484,"OpenShift",75,"OpenShift是红帽公司（Red Hat）开源的容器云平台，基于主流的容器技术Docker和Kubernetes构建。",488,"Pandas","Pandas是一个强大且灵活的Python数据分析库，提供了数据结构（如Series和DataFrame）和数据分析工具，使数据清洗、处理和分析变得快速而简单。",463,"rancher","Rancher Kubernetes管理平台，多集群管理、应用商店及运维工具。",479,"RocketMQ","RocketMQ，一个分布式消息和流数据平台，具有低延迟、高性能、高可靠性、万亿级容量和灵活的可扩展性。",466,"无服务器计算，函数即服务（FaaS）、事件驱动架构及云函数部署。",810,"Service Mesh","服务网格技术，如Istio、Linkerd，实现微服务间通信、安全与监控。",478,"VirtualBox",114,"VirtualBox是一款强大且易于使用的开源虚拟机软件，支持多操作系统，具备卓越性能，可在不同硬件和操作系统上进行无缝测试和调试，降低运行成本，简化安装流程，并提供灵活的资源管理选项。",459,"VMWare","VMware虚拟化产品，包括vSphere、ESXi、虚拟机管理及数据中心方案。",489,39,"CNCF云原生生态，涵盖Kubernetes、Prometheus、Envoy等开源项目与实践。",480,171,"机器学习算法、模型训练、特征工程、TensorFlow\u002FPyTorch及实战案例。",803,"边缘计算架构，将计算与存储靠近数据源，减少延迟，适用于IoT等场景。","前端开发",137,"\u002F\u002Fwenku.it\u002Fuploads\u002Fd\u002Fb\u002F7\u002Fa\u002Ff\u002Fdb7af4e4c196f184dcb5ac9bd00ba568.png","\u002F\u002Fwenku.it\u002Fuploads\u002F7\u002Ff\u002F5\u002Fa\u002Fa\u002F7f5aa5248f17ac352e3f66d1a8319b3d.png","涵盖网页前端技术，包括HTML、CSS、JavaScript及相关框架，实现用户界面与交互体验。",403,"Angular框架相关，包括组件、路由、服务、依赖注入及最佳实践等前端开发内容。",444,"Dart编程语言，用于Flutter开发、服务端或Web，涵盖语法、库及工具。",490,"Electron是一个开源框架，允许开发者使用Web技术（HTML、CSS和JavaScript）构建跨平台的桌面应用程序。",471,9,"Flutter是一个由谷歌开发的开源跨平台应用软件开发工具包，用于为Android、iOS、Windows、macOS、Linux Desktop、Google Fuchsia开发应用。 ",401,"网页结构标记语言HTML与样式语言CSS，包括布局、响应式设计及预处理器等。",49,"JavaScript语言核心、ES6+新特性、DOM操作、异步编程及常见库与工具。",790,"NativeScript","NativeScript是一个开源框架，它允许开发人员使用JavaScript或TypeScript以及XML和CSS来构建跨平台本地移动应用程序，无需学习每个平台的特定语言或工具，同时提供与原生API的深度集成，实现高性能和优质的用户体验。",407,"渐进式Web应用，包括Service Worker、离线缓存、推送通知及原生体验优化。",402,"React库相关，涵盖组件、Hooks、状态管理、路由及生态系统工具。",469,"Svelte","Svelte是一种现代的JavaScript框架，通过在构建时将代码转换为高效的原生JavaScript，实现在客户端以更少的运行时负担创建响应式、快速且轻量级的Web应用。","TypeScript类型系统、编译配置、高级类型及在项目中的实践应用。",404,"Vue.js","Vue.js框架，包括响应式数据、组件、路由、Vuex\u002FPinia及生态系统。",406,"前端测试","前端单元测试、集成测试、端到端测试工具与方法，如Jest、Cypress等。",470,"构建工具","前端构建工具如Webpack、Vite、Rollup等，包括配置、优化及自动化流程。","系统运维",328,"\u002F\u002Fwenku.it\u002Fuploads\u002Fd\u002Fc\u002Fe\u002F7\u002F5\u002Fdce756afdfe873c14750c733e23fff73.jpg","\u002F\u002Fwenku.it\u002Fuploads\u002Fb\u002F6\u002Fd\u002F1\u002F3\u002Fb6d13efc4e52255c8384796b4b5cc861.png","涉及服务器部署、监控、故障排查、自动化运维及系统稳定性保障等相关工作。",419,"Android平台开发，包括Java\u002FKotlin、UI组件、系统API及发布流程。",424,"Darwin","Darwin操作系统相关，macOS\u002FiOS底层、XNU内核及Unix环境与工具。",465,36,"开发与运维融合实践，涵盖CI\u002FCD、容器化、监控、自动化部署与文化。",808,"httpd","HTTP服务器软件如Apache httpd，配置、模块、性能优化及安全设置。",420,"iOS平台开发，包括Swift\u002FObj-C、UIKit、SwiftUI、App Store发布等。","Jenkins是一个开源的自动化服务器，用于自动执行软件构建、测试和部署任务。",145,"Linux操作系统使用、命令、系统管理、内核、Shell脚本及服务器运维。","eBPF",31,"eBPF 是一项革命性的技术，起源于 Linux 内核，它可以在特权上下文中（如操作系统内核）运行沙盒程序。它用于安全有效地扩展内核的功能，而无需通过更改内核源代码或加载内核模块的方式来实现。",804,"Cilium 是一种用于网络、可观察性和安全性的云原生技术。它基于内核技术 eBPF，最初是为了更好的网络性能，现在针对不同的用例利用了许多附加功能。",483,"Nginx Web服务器与反向代理，配置、负载均衡、缓存及性能调优。","Prometheus是一款开源的监控和警报工具，用于收集和存储系统和服务的性能数据，并支持动态查询和告警规则配置。",423,"Shell脚本编程，Bash\u002FZsh语法、命令行工具、自动化任务及系统管理。",482,"Traefik","Traefik反向代理与负载均衡器，配置、中间件、动态路由及云原生集成。",421,"Windows操作系统使用、管理、服务器配置、PowerShell及脚本自动化。",476,29,"Zabbix 是一个开源的 IT 基础设施监控软件，用于监控各种网络服务、网络硬件、网络设备以及其他网络节点。",811,"存储","存储技术与方案，包括SAN\u002FNAS、分布式存储、对象存储及数据备份恢复。",781,"网络与安全","计算机网络、协议、防火墙、加密、身份验证及安全策略与漏洞防护。","综合其他","\u002F\u002Fwenku.it\u002Fuploads\u002F4\u002F4\u002Fc\u002F2\u002Fe\u002F44c2ed0c098bd2357e61c2636e66b1b0.png","\u002F\u002Fwenku.it\u002Fuploads\u002F0\u002Fe\u002Ff\u002F9\u002F9\u002F0ef9992efeb2af816b83eb04f3e8fd4b.png","包含未归类到其他分类的技术、工具或话题，如通用编程、跨领域内容等。",472,41,"Blender是一款自由和开源的三维计算机图形软件，它可以用于创建和渲染三维模型、动画、游戏、视觉效果等。",510,"GIMP","GIMP是一款开源免费的图像处理软件，提供了丰富的图像编辑和创作功能，类似于专业的Photoshop，但更轻便易用。","KiCad",132,"KiCad 是一个开源软件工具，用于创建电子原理图和 PCB 图形。 ",509,"Krita是一款强大的开源数字绘画和动画软件，专为艺术家和创作者设计，提供丰富的绘画工具和高效的工作流程，助力创意无限发挥。","Weblate",302,"Weblate是一款易于使用的开源在线协作翻译平台，支持多种格式文件的翻译管理，让团队协作翻译变得更加高效便捷。","产品与服务","产品设计、项目管理、用户体验、服务架构及商业分析与运营相关。",793,"Apache OFBiz","Apache OFBiz是一个开源的企业资源计划系统。它提供了一套企业应用程序，它们集成并自动化了企业的许多业务流程。",65,"AI技术包括机器学习、深度学习、自然语言处理、计算机视觉及算法应用。",502,"亿图","亿图是一款功能强大的图形图表设计软件，支持创建各种流程图、组织结构图、思维导图、UML图、ER图等多种图表类型，广泛应用于商业、教育、科研等领域。","数据可视化","数据图表绘制、可视化工具（如D3、ECharts）、仪表盘及信息呈现设计。",796,"DataEase 是开源的数据可视化分析工具,帮助用户快速分析数据并洞察业务趋势,从而实现业务的改进与优化。DataEase 支持丰富的数据源连接,能够通过拖拉拽方式快速制作图表,并可以方便地与他人分享。",474,"版本控制","版本控制软件工具，如Git、SVN等",438,"笔试面试","编程面试准备、算法题、系统设计题、技术面试经验及求职技巧。","前端","\u002F\u002Fwenku.it\u002Fuploads\u002Fc\u002F9\u002F6\u002Fa\u002F8\u002Fc96a81f58f7cc0a441d5b7c477c9e535.png",524,"Ant 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HTML代码要做到\n\n- 只是代表内容和结构，和表现无关\n\n- 清晰的结构性\n\n- 充分的语义性 jpg)\n\n\n## \u003Cmark\u003E网页\u003C\u002Fmark\u003E的头部\n\n1、你要告诉浏览器此\u003Cmark\u003E网页\u003C\u002Fmark\u003E的基本信息 \n\n2、你要告诉搜索引擎的基本信息\n\n\n\n3、需要包含的其他的脚本，如CSS、JS\n\n4、不包含任何要显示的内容\n\n\u003Cmark\u003E网页\u003C\u002Fmark\u003E的主体部分\n\n1、所有\u003Cmark\u003E网页\u003C\u002Fmark\u003E中的具体内容\n\n\u003Cmark\u003E网页\u003C\u002Fmark\u003E文件名字：字母、数字、下划线 \n\n\u003Cmark\u003E网页\u003C\u002Fmark\u003E文件后缀：.htm或.html \n\n默认首页：index.htm或index.html\n\n\n\n\n## \u003Cmark\u003E网页\u003C\u002Fmark\u003E头部存放信息\n\n\n\u003Ctitle\u003ETianjin content=\"php,html,stefyang\"\u002F\u003E\n\u003Cmeta http-equiv=\"Content-Type\" content=\"text\u002Fhtml; charset=utf-8\"\u002F\u003E\n\n## \u003Cmark\u003E网页\u003C\u002Fmark\u003E主体部分\n## 基础文字显示部分\n\n\n|1|<html>|\n|---|---|\n|2|<head><\u002Fhead>|\n|3|<body>|\n|4|This","zh","2024-03-02T15:11:30Z","监控维度更多，除了传统物理集群的监控，还包括核心服务监控（API server，Etcd等）、容器监控、Pod监控、Namespace监控等\n\n● 监控对象\u003Cmark\u003E动态\u003C\u002Fmark\u003E可变，在集群中容器的销毁创建十分频繁，无法提前预置\n\n监控指标随着容器规模爆炸式增长，如何处理及展示大量监控数据\n\n随着集群\u003Cmark\u003E动态\u003C\u002Fmark\u003E增长，监控系统必须具备\u003Cmark\u003E动态\u003C\u002Fmark\u003E扩缩的能力\n## 监控遇上 Kubernetes\n\n目前容器云平台提供的k8s集群包括：\n\n10+集群（云+物理机房+边缘） resource_requests_memory:label_biz_type\n## Thanos + Kvass\n\n## Kvass是一个Prometheus横向扩缩容解决方案\n\n他使用Sidecar\u003Cmark\u003E动态\u003C\u002Fmark\u003E得根据Coordinator分配下来的target列表来为每个Prometheus生成只含特定target的配置文件，从而将采集任务分散到各个Prometheus分片。\n\nCoordinator用于 et的时候，会根据target的实际规模来，而不是通过hashmod来，所以每个分片的总负载会被控制在一个阈值以下，不会出现某个分片OOM的情况。\n\n● 自动扩缩容：Kvass会根据当前集群的规模，\u003Cmark\u003E动态\u003C\u002Fmark\u003E调整分片个数\n\n![Image](\u002Fuploads\u002Fdocuments\u002Fb\u002F2\u002Fd\u002F7\u002Fb2d703128539524d374d63151f676cb3\u002Fp13_1.jpg)\n\n## Thanos +","学批评指正。\n\n本书中的代码附有可一键运行的源文件，托管于 github.com\u002Fkrahets\u002Fhello-algo 仓库。动画在 PDF 内的展示效果受限，可访问 hello-algo.com \u003Cmark\u003E网页\u003C\u002Fmark\u003E版以获得更优的阅读体验。\n\n## 推荐语\n\n“一本通俗易懂的数据结构与算法入门书，引导读者手脑并用地学习，强烈推荐算法初学者阅读！”\n\n——邓俊辉，清华大学计算机系教授\n\n“如果我当年学数据结构与算法的时候有《Hello 第13章回溯 \n13.1 回溯算法 \n13.2 全排列问题 \n13.3 子集和问题 \n13.4 n 皇后问题 \n13.5 小结 \n \n第14章 \u003Cmark\u003E动态\u003C\u002Fmark\u003E规划 \n14.1 初探\u003Cmark\u003E动态\u003C\u002Fmark\u003E规划 \n14.2 \u003Cmark\u003E动态\u003C\u002Fmark\u003E规划问题特性 \n14.3 \u003Cmark\u003E动态\u003C\u002Fmark\u003E规划解题思路 \n14.4 0-1 背包问题 \n14.5 完全背包问题 \n14.6 编辑距离问题 \n14.7 小结\n第 15 章贪心 \n15.1 贪心算法等。\n\n数据结构：基本数据类型和数据结构的分类方法。数组、链表、栈、队列、哈希表、树、堆、图等数据结构的定义、优缺点、常用操作、常见类型、典型应用、实现方法等。\n\n· 算法：搜索、排序、分治、回溯、\u003Cmark\u003E动态\u003C\u002Fmark\u003E规划、贪心等算法的定义、优缺点、效率、应用场景、解题步骤和示例问题等。\n![Image](\u002Fuploads\u002Fdocuments\u002F3\u002Fe\u002Fb\u002F2\u002F3eb28f4b59465ff9d753a268eab4c5b5\u002Fp9_1","进一步：核函数调用核函数\n\n从 Keller 架构开始，___global___ 里可以调用另一个 ___global___，也就是说核函数可以调用另一个核函数，且其三重尖括号里的板块数和线程数可以\u003Cmark\u003E动态\u003C\u002Fmark\u003E指定，无需先传回到 CPU 再进行调用，这是 CUDA\n\n特有的能力\n\nkernel: Thread 0 of 3\n\nkernel: Thread 1 of 3\n\nkernel: Thread 2 of of 5\n\nanother: Thread 3 of 5\n\nanother: Thread 4 of 5\n\n常用于这种情况：需要从 GPU 端\u003Cmark\u003E动态\u003C\u002Fmark\u003E计算出 blockDim 和 gridDim，而又不希望导回数据到 CPU 导致强制同步影响性能。这种模式被称为\u003Cmark\u003E动态\u003C\u002Fmark\u003E并行（dynamic parallelism），OpenGL 有一个 glDispatchComputeIndirect 的 API 和这个很像，但毕竟没有 65532\n\narr[65533]: 65533\n\narr[65534]: 65534\n## 网格跨步循环：应用于线程和板块一起上的情况\n\n- 网格跨步循环实际上本来是这样，利用扁平化的线程数量和线程编号实现\u003Cmark\u003E动态\u003C\u002Fmark\u003E大小。\n\n- 同样，无论调用者指定每个板块多少线程（blockDim），总共多少板块（gridDim）。都能自动根据给定的 n 区间循环，不会越界，也不会漏掉几个元素。\n\n- 这样一个 for 循环非常符合",".pptx","v3.5.0-beta.10","zh-TW","中文（简体）","fr",57,"书栈网","https:\u002F\u002Fwww.bookstack.cn",{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},"文曲猩AI助手","\u002Farticle\u002Fabout",1000,"\u002F","_blank"));</script><script 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02 HTML 杨亮 《PHP语⾔程序设计》

02 HTML 杨亮《PHP语⾔程序设计》