From ef422bbc35f7a6b1c9b2634d87f207c84a11dd19 Mon Sep 17 00:00:00 2001 From: aaaa-j Date: Thu, 25 Aug 2022 09:58:15 +0800 Subject: [PATCH 1/2] =?UTF-8?q?=E6=8F=90=E4=BA=A4=E6=96=87=E6=A1=A3?= =?UTF-8?q?=E4=BF=AE=E6=94=B9,=E4=B8=BB=E8=A6=81=E4=BF=AE=E6=94=B9?= =?UTF-8?q?=E9=83=A8=E7=BD=B2=E7=9B=B8=E5=85=B3=E5=92=8C=E9=A6=96=E6=AC=A1?= =?UTF-8?q?=E5=88=86=E6=9E=90=E7=9B=B8=E5=85=B3?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- doc/.vuepress/configs/navbar/zh.ts | 13 +- doc/.vuepress/configs/sidebar/zh.ts | 32 +--- doc/README.md | 49 +----- doc/images/codelint_04.png | Bin 0 -> 319620 bytes doc/images/create_team_group.png | Bin 203839 -> 185246 bytes doc/zh/README.md | 2 +- ...06\346\236\220\345\267\245\345\205\267.md" | 2 +- doc/zh/community/changelog.md | 146 ++++++++++++++---- doc/zh/guide/README.md | 13 +- ...23\346\236\234\346\237\245\347\234\213.md" | 11 +- ...36\346\200\247\351\205\215\347\275\256.md" | 10 +- ...02\347\202\271\347\256\241\347\220\206.md" | 78 +++------- ...66\344\273\226\351\205\215\347\275\256.md" | 28 ++++ ...02\347\202\271\345\210\206\346\236\220.md" | 71 ++++++--- ...54\345\234\260\345\210\206\346\236\220.md" | 92 +++++++---- ...15\347\275\256\350\257\246\346\203\205.md" | 26 ---- ...43\347\240\201\345\210\206\346\236\220.md" | 38 ++--- doc/zh/quickStarted/FAQ.md | 18 +-- doc/zh/quickStarted/README.md | 21 +++ doc/zh/quickStarted/codeDeploy.md | 110 +++++++------ doc/zh/quickStarted/dockerDeploy.md | 70 +++++++++ doc/zh/quickStarted/dockercomposeDeploy.md | 46 ++++-- doc/zh/quickStarted/enhanceDeploy.md | 49 +++--- 23 files changed, 547 insertions(+), 378 deletions(-) create mode 100644 doc/images/codelint_04.png create mode 100644 "doc/zh/guide/\345\256\242\346\210\267\347\253\257/\345\205\266\344\273\226\351\205\215\347\275\256.md" delete mode 100644 "doc/zh/guide/\345\256\242\346\210\267\347\253\257/\351\205\215\347\275\256\350\257\246\346\203\205.md" create mode 100644 doc/zh/quickStarted/README.md create mode 100644 doc/zh/quickStarted/dockerDeploy.md diff --git a/doc/.vuepress/configs/navbar/zh.ts b/doc/.vuepress/configs/navbar/zh.ts index 5a5974b7f..8d16435d3 100644 --- a/doc/.vuepress/configs/navbar/zh.ts +++ b/doc/.vuepress/configs/navbar/zh.ts @@ -2,8 +2,8 @@ import type { NavbarConfig } from '@vuepress/theme-default' export const zh: NavbarConfig = [ { - text: '快速入门', - link: '/zh/quickStarted/deploySever.md', + text: '快速部署', + link: '/zh/quickStarted/', }, { text: '帮助文档', @@ -19,14 +19,17 @@ export const zh: NavbarConfig = [ { text: '深入', children: [ - '/zh/advanced/任务分布式执行.md', '/zh/advanced/集成代码分析工具.md', ], }, { - text: '文章', + text: '依赖安装参考', children: [ - + '/zh/quickStarted/references/install_python37_on_centos.md', + '/zh/quickStarted/references/install_python37_on_ubuntu.md', + '/zh/quickStarted/references/install_mysql_on_centos.md', + '/zh/quickStarted/references/install_redis_from_source.md', + '/zh/quickStarted/references/install_redis_on_centos.md', ], }, ] diff --git a/doc/.vuepress/configs/sidebar/zh.ts b/doc/.vuepress/configs/sidebar/zh.ts index a64c388a8..d6e693276 100644 --- a/doc/.vuepress/configs/sidebar/zh.ts +++ b/doc/.vuepress/configs/sidebar/zh.ts @@ -18,7 +18,7 @@ export const zh: SidebarConfig = { ] }, { - text: '代码检查', + text: '分析结果', children: [ '/zh/guide/代码检查/分析结果查看.md', '/zh/guide/代码检查/添加规则配置.md', @@ -66,9 +66,9 @@ export const zh: SidebarConfig = { { text: '客户端', children: [ - '/zh/guide/客户端/配置说明.md', '/zh/guide/客户端/本地分析.md', '/zh/guide/客户端/常驻节点分析.md', + '/zh/guide/客户端/其他配置.md', ] }, { @@ -123,36 +123,20 @@ export const zh: SidebarConfig = { '/zh/quickStarted/': [ { text: '快速入门', - link: '/zh/quickStarted/deploySever.md', - // children: [ - // { - // text: '快速入门', - // link: '/zh/quickStarted/deploySever.md', - // }, - // ], - }, - { - text: '依赖安装参考', - // collapsible: true, children: [ - '/zh/quickStarted/references/install_python37_on_centos.md', - '/zh/quickStarted/references/install_python37_on_ubuntu.md', - '/zh/quickStarted/references/install_mysql_on_centos.md', - '/zh/quickStarted/references/install_redis_on_centos.md', - '/zh/quickStarted/references/install_redis_from_source.md', - '/zh/quickStarted/references/install_nginx_from_source.md', - ], + '/zh/quickStarted/README.md', + '/zh/quickStarted/dockerDeploy.md', + '/zh/quickStarted/dockercomposeDeploy.md', + '/zh/quickStarted/codeDeploy.md', + ] }, { text: '其他', // collapsible: true, children: [ - '/zh/quickStarted/intro.md', + '/zh/quickStarted/enhanceDeploy.md', '/zh/quickStarted/tools.md', '/zh/quickStarted/FAQ.md', - '/zh/quickStarted/codeDeploy.md', - '/zh/quickStarted/dockercomposeDeploy.md', - '/zh/quickStarted/enhanceDeploy.md', ], }, ], diff --git a/doc/README.md b/doc/README.md index cee92ccde..afdbaa194 100644 --- a/doc/README.md +++ b/doc/README.md @@ -3,8 +3,8 @@ home: true title: 腾讯云代码分析文档 heroImage: /images/Logo.svg actions: - - text: 快速入门 - link: /zh/quickStarted/deploySever.html + - text: 快速部署 + link: /zh/quickStarted/ type: primary - text: 帮助文档 link: /zh/guide/ @@ -35,48 +35,3 @@ footer: MIT Licensed | Copyright © 1998-present Tencent. All Rights Reserved. [https://git.code.tencent.com/Tencent_Open_Source/CodeAnalysis.git](https://git.code.tencent.com/Tencent_Open_Source/CodeAnalysis.git) -### 腾讯云代码分析简介 - -腾讯云代码分析（Tencent Cloud Code Analysis，简称TCA，内部曾用研发代号 **CodeDog** ）是集众多分析工具的云原生、分布式、高性能的代码综合分析跟踪平台，包含服务端、Web端和客户端三个组件，已集成一批自研工具，同时也支持动态集成业界各编程语言的分析工具。 - -代码分析是通过词法分析、语法分析、控制流、数据流分析等技术对程序代码进行扫描，对代码进行综合分析，验证代码是否满足规范性、安全性、可靠性、可维护性等指标的一种代码分析技术。 - -使用TCA可以帮助团队用代码分析技术查找代码中的规范性、结构性、安全漏洞等问题，持续监控项目代码质量并进行告警。同时TCA开放API，支持与上下游系统对接，从而集成代码分析能力，为代码质量提供保障，更有益于传承优良的团队代码文化。 - -![组件图](https://tencent.github.io/CodeAnalysis/media/Components.png) - -![流程图](https://tencent.github.io/CodeAnalysis/media/Flow.png) - -### 体验 - -[官方版本](http://tca.tencent.com) - -### 快速入门 - -- [快速入门](./zh/quickStarted/intro.md) -- [如何在本地部署Server与Web](./zh/quickStarted/deploySever.md#通过源代码) -- [如何通过Docker-Compose部署Server与Web](./zh/quickStarted/deploySever.md#通过docker-compose) -- [如何使用客户端](./zh/quickStarted/deployClient.md) -- [部署常见问题与解决方式](./zh/quickStarted/FAQ.md) - -## 社区 - -- 微信公众号：「腾讯云静态分析」，关注并发送“进群”即可加入官方开源交流微信群 -- QQ交流群：361791391 -- [GitHub讨论区](https://github.com/Tencent/CodeAnalysis/discussions) -- [Wiki](https://github.com/Tencent/CodeAnalysis/wiki) -- [腾讯云代码分析白皮书](https://github.com/Tencent/CodeAnalysis/tree/main/腾讯云代码分析白皮书.pdf) - -## 更新日志 - -[Changelog](https://github.com/Tencent/CodeAnalysis/tree/main/CHANGELOG.md) - -## 贡献 - -- 查看我们的[贡献说明](https://github.com/Tencent/CodeAnalysis/tree/main/CONTRIBUTING.md) -- [腾讯开源摘星计划2022](https://github.com/weopenprojects/WeOpen-Star/issues/19#issue-1228583868)（活动时间：2022年5月~12月） -- [腾讯开源激励计划](https://opensource.tencent.com/contribution) 鼓励开发者的参与和贡献，期待你的加入 - -### License - -[MIT licensed](https://github.com/Tencent/CodeAnalysis/tree/main/LICENSE) diff --git a/doc/images/codelint_04.png b/doc/images/codelint_04.png new file mode 100644 index 0000000000000000000000000000000000000000..b315bc7bf547e0dfc5751bf47da460d524169173 GIT binary patch literal 319620 zcmeFZ2T)Vp+ApqDQ4vJ}rCNYc1f=((2pD?rOv^8v?`bPkT~&enBJIU<=gyIX 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"b/doc/zh/advanced/\351\233\206\346\210\220\344\273\243\347\240\201\345\210\206\346\236\220\345\267\245\345\205\267.md" @@ -1,4 +1,4 @@ -# 集成代码分析工具 +# 在TCA源码中集成代码分析工具 ## 初识TCA任务执行机制 diff --git a/doc/zh/community/changelog.md b/doc/zh/community/changelog.md index e3fd99512..c26a00bdf 100644 --- a/doc/zh/community/changelog.md +++ b/doc/zh/community/changelog.md @@ -1,61 +1,154 @@ # 更新日志 +## V1.4.1 (2022-7-28) +### Features +- 【服务端】统一部署脚本，封装local、docker、docker-compose部署方式启动server&web&client +- 【服务端】支持源码安装Redis与Nginx +- 【服务端】macOS启动docker desktop +- 【服务端】完善github action脚本 +- 【工具】更新工具列表 -## V1.2.0 (2022-4-27) +### Docs +- 上传新版本白皮书 +- 调整快速入门指引文档 + + + +## V1.4.0 (2022-7-18) +### Features +- 【客户端】jenkins插件增加分析方案模版ID和分析方案名称参数 +- 【服务端】增加扫描方案模板API +- 【服务器】优化文件服务器鉴权交互 +- 【客户端】QuickScan支持指定分析方案模板进行扫描；支持从环境变量读取文件服务器url和token +- 【Web端】升级moment依赖 +### Docs +- 更新插件使用说明书和启动参数说明 + + + +## V1.3.3 (2022-6-29) +### Features +- 【服务端】支持团队、项目组禁用，支持代码库、分支项目删除 +- 【服务端】扫描方案支持分支过滤 +- 【Web端】支持禁用团队、项目，代码库登记支持ssh_url +- 【Web端】支持分支过滤配置，修复代码统计文件选中效果，支持工具、依赖凭证移除 +- 【工具】增加tca_ql工具 +- 【客户端】节点模式不再由客户端加载编译工具的环境变量，避免覆盖机器原有环境变量 +- 【客户端】QuickScan模式，异常时输出task.log方便排查问题 +- 【客户端】.code.yml支持.yaml后缀 +### Bugfixes +- 【客户端】tool_scheme和ini配置共用时，可能出现工具重复，需要对工具库去重后再拉取 +### Docs +- 更新TCA Action相关文档 +- 更新Jenkins插件文档；增加环境依赖说明 +- 更新自定义工具文档，使用工具依赖 +- 更新CLS readme + + + +## V1.3.2 (2022-6-16) +### Features +- 【客户端】QuickScan根据语言执行不同的任务 +### Docs +- docker-compose部署文档中数据库注意事项 + + + +## V1.3.1 (2022-6-14) +### Features +- 【客户端】新增merge quest分支增量扫描 +- 【客户端】新增Quickscan模式 +- 【客户端】localscan支持工具并发 +- 【工具】新增二进制文件依赖分析工具 +- 【服务端】server调整服务监控探测脚本：celery状态判断 +- 【服务端】增加子任务接口，完善部署脚本 +- 【服务端】更新CLS版本v20220613.1 +- 【服务端】基于 CentOS7.9.2009（已测）的运行环境一键安装脚本，并已安装及配置命令 gunicorn 和 celery +- 【Web端】调整OAuth显示 + + + +## V1.3.0 (2022-6-7) +### Features +- 【工具】新增独立工具Loong +- 【工具】新增Java、JS基础安全规则包 +- 【工具】增加Go和Python技术安全规则包 +- 【服务端】新增oauth授权及工具依赖管理 +- 【服务端】docker-compose部署支持挂载本地日志目录 +- 【客户端】支持工具依赖管理 +- 【Web端】支持工具依赖管理设置和Git OAuth设置 +- 【Web端】团队列表支持滚动加载 +### Bugfixes +- 【服务端】补充scmproxy缺失依赖 +- 【服务端】修复issue入库忽略处理操作 + +### Docs +- 更新工具目录readme +- 更新client README.md + + + +## V1.2.1 (2022-5-24) ### Features +- 【工具】新增Collie/Compass（测试版）工具 +- 【工具】添加tscancode系列工具 +- 【工具】工具区分编译型和非编译型 +- 【客户端】更新cmdscm二进制文件，调整获取ssh端口号方式 +- 【客户端】增加腾讯工蜂作为工具拉取源，支持选用 +- 【服务端】调整工程配置和文档，支持https克隆 +- 【Web端】前端页面优化 + +### Docs +- 添加集成工具说明文档 +- readme增加微信公众号和腾讯开源摘星计划的说明及链接 +- 修改帮助文档的脚本名称；修改工蜂镜像仓库链接位置 +- 调整自定义规则文档 +- 调整doc，优化部署、使用文档 + + +## V1.2.0 (2022-4-27) +### Features - 【Web端】增加工具管理 - 【工具】增加logback检查的安全规则 - 【服务端】增加TCA server&web 一键部署脚本 - 【服务端】删除main部分异步任务；调整server nginx启动位置 - 【服务端】增加server健康监测 - ### Docs - - 完善部署和Q&A文档 - 上传工具列表 -## V1.1.3 (2022-4-18) +## V1.1.3 (2022-4-18) ### Features - - 【工具】上传开源合规检查规则 - 【工具】新增PHP安全相关规则 - 【服务端】上线license鉴权 - 【客户端】支持对工具license校验 - ### Docs - - 更新文档内的工具默认路径 - 增加任务分布式执行能力操作文档 - 增加PR操作流程 -## V1.1.2 (2022-4-2) +## V1.1.2 (2022-4-2) ### Features - -- 【服务端】优化部署构建脚本 - +- 【服务端】优化部署构建脚本 ### Docs - -- 简化前端部署脚本&文档 +- 简化前端部署脚本&文档 - 优化指引文档 -## V1.1.1 (2022-3-31) +## V1.1.1 (2022-3-31) ### Features - - 【工具】增加0daychecker工具 - 【工具】增加Log4j、LogBack漏洞检查规则包 ### Docs - - 完善部署文档说明，推荐使用Docker-Compose 2.3.3版本 ## V1.1.0 (2022-3-29) - ### Features - - 【客户端】client支持arm64架构执行环境 - 【客户端】client新增分布式节点模式 - 【客户端】修改参数isTotal(是否开启全量扫描)判断方式及参数startCommand（启动客户端命令）拼接方式 @@ -65,21 +158,17 @@ - 【Web端】web模块部署脚本问题修复及优化 - 【Web端】增加管理后台、增加在线分析 - 【Web端】调整前端部署脚本，支持传递nginx配置地址、前端资源部署地址 - ### Bugfixes - - Jenkins插件命令拼装逻辑修正 - ### Docs - - 调整pypi下载失败提示 - 调整前端部署文档及脚本 - 更新License -## V1.0.1 (2022-03-01) -### Features +## V1.0.1 (2022-03-01) +### Features - feat: 【服务端】调整代码库登记ssh url链接格式适配 - feat: 【工具】上线支持PHP安全工具-Rips - feat: 【工具】调整androidlint部分规则描述 @@ -90,17 +179,16 @@ - feat: 【客户端】增加在docker中快速使用client的方式 ### Bugfixes - - fix: 【服务端】补充缺失的依赖 - fix: 【Web端】修复下载codedog.ini失败提示 - + ### Docs - - doc: 上线部署文档Q&A - doc: 优化部署文档、帮助文档说明 - doc: 增加产品白皮书 - doc: 补充redis和nginx源码安装参考文档 -## V1.0.0 -初始发布 + +## V1.0.0 +初始发布 \ No newline at end of file diff --git a/doc/zh/guide/README.md b/doc/zh/guide/README.md index 7c9c9ea9e..da9dfcdd6 100644 --- a/doc/zh/guide/README.md +++ b/doc/zh/guide/README.md @@ -1,12 +1,11 @@ # 腾讯云代码分析 -**腾讯云代码分析**（**Code Analysis, TCA**）起步于 2012 年（内部代号CodeDog），是集众多代码分析工具的云原生、分布式、高性能的代码综合分析跟踪管理平台，其主要功能是持续跟踪分析代码，观测项目代码质量，支撑团队传承代码文化。 +**腾讯云代码分析**（**Tencent Cloud Code Analysis, TCA**）起步于 2012 年（内部代号CodeDog），是集众多代码分析工具的云原生、分布式、高性能的代码综合分析跟踪管理平台，其主要功能是精准跟踪管理代码分析发现的代码质量缺陷、代码规范、代码安全漏洞、无效代码，以及度量代码复杂度、重复代码、代码统计。持续跟踪分析代码，观测项目代码质量，支撑团队传承代码文化。 -用心关注每行代码迭代、助力传承卓越代码文化！ +用心关注每行代码迭代，助力传承卓越代码文化！ -精准跟踪管理代码分析发现的代码质量缺陷、代码规范、代码安全漏洞、无效代码，以及度量代码复杂度、重复代码、代码统计。 -代码分析是通过词法分析、语法分析、控制流、数据流分析等技术对程序代码进行分析，验证代码是否满足**规范性**、**安全性**、**可靠性**、**可维护性**、**部分性能**等，对代码进行综合分析和度量等指标的一种代码分析技术。 +**代码分析**是通过词法分析、语法分析、控制流、数据流分析等技术对程序代码进行扫描，对代码进行综合分析，验证代码是否满足规范性、安全性、可靠性、可维护性等指标的一种代码分析技术。 ## 主要功能 @@ -20,16 +19,16 @@ 包含代码圈复杂度、代码重复率和代码统计等度量信息。 -#### 代码圈复杂度 +### 代码圈复杂度 圈复杂度也称为条件复杂度或循环复杂度，它可以用来衡量一个模块判定结构的复杂程度。圈复杂度大说明程序代码的判断逻辑复杂，可能造成代码质量低下且难于测试和维护。 定期分析工程项目中代码的圈复杂度，可以有效地帮助开发与测试逐步优化代码质量。 -#### 代码重复率 +### 代码重复率 定期分析工程项目中的重复代码，可以有效地帮助开发发现冗余代码，进行代码抽象和重构，降低代码风险，以便于更好的管理和维护代码。 -#### 代码统计 +### 代码统计 支持全量增量展示代码行数统计，包含代码行、注释行和空白行，可以有效地跟踪了解工程项目中代码量持续变化，并可以查看各个语言的占比情况。 diff --git "a/doc/zh/guide/\344\273\243\347\240\201\346\243\200\346\237\245/\345\210\206\346\236\220\347\273\223\346\236\234\346\237\245\347\234\213.md" "b/doc/zh/guide/\344\273\243\347\240\201\346\243\200\346\237\245/\345\210\206\346\236\220\347\273\223\346\236\234\346\237\245\347\234\213.md" index 591f45c64..81289d1e0 100644 --- "a/doc/zh/guide/\344\273\243\347\240\201\346\243\200\346\237\245/\345\210\206\346\236\220\347\273\223\346\236\234\346\237\245\347\234\213.md" +++ "b/doc/zh/guide/\344\273\243\347\240\201\346\243\200\346\237\245/\345\210\206\346\236\220\347\273\223\346\236\234\346\237\245\347\234\213.md" @@ -1,14 +1,15 @@ # 代码检查结果查看 -客户端分析完毕后，如果分析方案含有代码检查功能，则代码分析结束后会上报结果信息到腾讯云代码分析平台，用户可在平台上查看问题列表及详情。 - -![问题列表](../../../images/codelint_01.png) +代码分析完毕后，可在`分支概览`页面查看分析结果概览。如果分析方案含有代码检查功能，则会上报代码检查结果信息到腾讯云代码分析平台，用户可在平台上查看问题列表及问题详情。 +![问题列表](../../../images/codelint_04.png) ## 问题列表 -进入代码检查问题列表页面后，默认展示**当前分支 + 当前分析方案（即分支项目）**发现的全部未处理问题。 +![问题列表](../../../images/codelint_01.png) + +进入代码检查问题列表页面后，默认展示当前分支项目发现的全部未处理问题。 -如果仅希望查看增量问题，可以进入分析历史页面，指定查看某一次的扫描结果即可。也可以在过滤筛选项中填入发现问题的扫描 `id`进行筛选查看结果（该`id`为扫描任务 ID，需要到扫描任务列表中查询）。 +如果仅希望查看增量问题，可以进入`分析历史`页面，指定查看某一次的扫描结果即可。也可以在过滤筛选项中填入发现问题的扫描 `id`进行筛选查看结果（该`id`为扫描任务 ID，需要到扫描任务列表中查询）。 - **责任人说明** diff --git "a/doc/zh/guide/\345\210\206\346\236\220\346\226\271\346\241\210/\345\237\272\347\241\200\345\261\236\346\200\247\351\205\215\347\275\256.md" "b/doc/zh/guide/\345\210\206\346\236\220\346\226\271\346\241\210/\345\237\272\347\241\200\345\261\236\346\200\247\351\205\215\347\275\256.md" index 3c28a4c40..b0edbc3a0 100644 --- "a/doc/zh/guide/\345\210\206\346\236\220\346\226\271\346\241\210/\345\237\272\347\241\200\345\261\236\346\200\247\351\205\215\347\275\256.md" +++ "b/doc/zh/guide/\345\210\206\346\236\220\346\226\271\346\241\210/\345\237\272\347\241\200\345\261\236\346\200\247\351\205\215\347\275\256.md" @@ -10,15 +10,7 @@ - **运行环境** - - 对于客户端分析，根据客户端所在本地执行机器选择对应运行环境即可。 - - - 对于在线分析，根据项目实际情况，选取对应运行环境即可。 - - ::: tip - 在线分析时，会根据方案的运行环境，将任务分配到对应环境的节点机器上执行代码分析。 - - 需考虑项目在对应环境的节点机器上能否正常执行 - ::: + 用于将任务分配到指定的环境节点机器上执行代码分析，需考虑项目在对应环境的节点机器上能否正常执行。 - **环境变量** diff --git "a/doc/zh/guide/\345\233\242\351\230\237\347\256\241\347\220\206/\350\212\202\347\202\271\347\256\241\347\220\206.md" "b/doc/zh/guide/\345\233\242\351\230\237\347\256\241\347\220\206/\350\212\202\347\202\271\347\256\241\347\220\206.md" index e9684cd13..a035fc97f 100644 --- "a/doc/zh/guide/\345\233\242\351\230\237\347\256\241\347\220\206/\350\212\202\347\202\271\347\256\241\347\220\206.md" +++ "b/doc/zh/guide/\345\233\242\351\230\237\347\256\241\347\220\206/\350\212\202\347\202\271\347\256\241\347\220\206.md" @@ -1,68 +1,44 @@ -# 节点与标签 +# 团队节点与标签 -除了使用**公共节点**执行代码分析外，团队还可以利用**团队标签**注册并使用**团队节点**。 - -## 名词释义与特点 +::: warning +**团队节点及标签说明** -- 团队节点是**团队注册并管理**的**私有**节点。 +- **团队节点**是团队注册并管理的私有节点。 -- 团队节点**仅会运行**当前团队所属的分析任务。 +- **团队标签**用于关联团队内的节点机器与分析项目。 -- 团队标签是用于关联节点机器与分析项目。 - ::: tip - 当一个分析项目在方案中配置运行环境为团队标签后，该项目创建的任务就会下发到团队标签关联的节点机器上运行 - ::: +- 团队可以利用**团队标签**注册并使用**团队节点**。 -## 适用场景 +- 在项目的分析方案中配置运行环境为团队标签后，才可将该项目的分析任务下发到对应的团队节点。 -1. 业务项目**不想**在公共机器上**排队**等待 +- 团队节点**仅支持运行**当前团队中的分析任务，节点可执行的任务范围取决于该节点的负责人权限： + - 如果节点负责人为团队管理员，该节点可以执行当前团队所有项目的分析任务 + - 如果节点负责人为项目管理员，该节点只能运行指定项目下的分析任务 + - 如果节点负责人为部分代码库的管理员，该节点只能运行对应代码库的分析任务 +::: -2. 业务项目**代码比较敏感**，不能在公共机器上运行 +## 适用场景 -3. 业务项目需要**依赖特定**的**机器环境**（比如CPU架构、操作系统等） +1. 团队因资源可靠性或项目敏感性，需使用私有机器资源 -4. ... +2. 团队项目分析依赖**特定机器环境**（比如CPU架构、操作系统等） -以上场景，均可考虑使用团队节点，业务团队提供机器资源接入作为团队节点，仅分析自己业务的代码库，**保证执行效率**，**保护源码不泄漏**，**支持项目特殊依赖**等 +以上场景，团队可接入专机资源作为团队节点，仅分析自己业务的代码库，以**保证执行效率**，**保护源码安全**，**支持项目环境依赖**等。 ## 团队节点注册 -- 根据环境下载客户端二进制文件或拉取源码，参考[客户端](../客户端/配置说明.md)。 - -- 通过终端启动客户端： - - - 客户端二进制启动 - - ```bash - ./codepuppy start -t TOKEN --org-sid ORG_SID - ``` - - - 客户端源码启动 - - ```bash - python3 codepuppy.py start -t TOKEN --org-sid ORG_SID - ``` - - ::: tip - 1. TOKEN 可以从平台**个人中心-个人令牌**页面获取 - 2. ORG_SID 可以从**页面链接**中获取 - ::: +参考[客户端常驻节点分析](../客户端/常驻节点分析.md)进行环境配置和启动节点。 ## 团队节点管理 -完成团队节点注册后，可以在当前团队下看到对应的节点信息，同时**需要进行配置** +完成团队节点注册后，可以在当前团队`节点管理`下看到对应的节点信息，同时**需要进行节点配置** ::: warning - 团队节点**首次注册**时，需要手动在平台上配置**所属标签**、**节点可用性**、**工具进程**等。 -- 将节点的**节点可用性**调整为**活跃**后，运行客户端节点的终端会输出**心跳上报成功**的日志 +- 将节点的**节点可用性**调整为**活跃**后，节点终端客户端运行日志会输出**心跳上报成功**的日志 ::: -- 首次注册团队节点，节点状态为不可用 - - ![注册团队节点](../../../images/org_node_manager_1.png) - -- 调整后的节点 - +- 首次注册团队节点，节点状态默认为不可用，需调整节点状态为“活跃”： ![注册团队节点](../../../images/org_node_manager_2.png) - 配置节点关联的工具进程： @@ -74,20 +50,8 @@ 2. 团队标签可以参考`CodeDog`标签为不同的系统类型（Linux、MacOS、Windows）建立标签，比如`专属标签-Linux`、`专属标签-Mac`等 ::: -### 团队节点执行任务范围 - -::: warning 使用团队节点运行分析任务的前提 -对应分析项目使用的分析方案中，需要配置分析方案中的**运行环境**为该团队节点配置的所属标签。 -::: - -::: warning 团队节点执行的任务范围取决于该节点的负责人 -- 如果节点负责人为团队管理员，该节点可以执行当前团队所有项目的分析任务 -- 如果节点负责人为项目管理员，该节点只能运行指定项目下的分析任务 -- 如果节点负责人为部分代码库的管理员，该节点只能运行对应代码库的分析任务 -::: - -## 团队标签管理 +## 使用团队标签 您可以创建一个团队标签，并配置到您的团队节点和您的分析方案中 diff --git "a/doc/zh/guide/\345\256\242\346\210\267\347\253\257/\345\205\266\344\273\226\351\205\215\347\275\256.md" "b/doc/zh/guide/\345\256\242\346\210\267\347\253\257/\345\205\266\344\273\226\351\205\215\347\275\256.md" new file mode 100644 index 000000000..8863a5086 --- /dev/null +++ "b/doc/zh/guide/\345\256\242\346\210\267\347\253\257/\345\205\266\344\273\226\351\205\215\347\275\256.md" @@ -0,0 +1,28 @@ + +# 其他配置与用法 + +### 1. 配置使用本地工具 + +:::warning +如果由于网络原因，执行时无法从github自动拉取工具，或拉取比较慢，可以参考基础配置腾讯工蜂工具地址，或使用以下方式预先下载好工具，配置使用本地工具目录。 +::: + +- （1）下载工具配置库 `https://github.com/TCATools/puppy-tools-config.git` ，存放到 `client/data/tools`目录下（如果未生成，可先创建该目录）。 +- （2）根据当前机器操作系统，查看`puppy-tools-config`目录下的`linux_tools.ini`或`mac_tools.ini`或`windows_tools.ini`文件，将`[tool_url]`中声明的所有工具下载到 `client/data/tools`目录下。 +- （3）填写`client/config.ini`中的配置：`USE_LOCAL_TOOL`=`True`，即可使用下载好的本地工具，不自动拉取和更新工具。 + +### 2. 使用自建git server存放工具 + +:::warning +如果自己搭建了一套git server，可以将工具配置库 `https://github.com/TCATools/puppy-tools-config.git` 以及里面声明的工具仓库，存放到自建git serevr上。 +::: + +- （1）将工具配置库 `https://github.com/TCATools/puppy-tools-config.git` 上传到自建git仓库。 +- （2）按所需的操作系统，将`puppy-tools-config`仓库下的`linux_tools.ini`或`mac_tools.ini`或`windows_tools.ini`文件中`[tool_url]`声明的所有工具库，上传到自建git仓库。 +- （3）修改`linux_tools.ini`或`mac_tools.ini`或`windows_tools.ini`文件中`[base_value]`中的`git_url`为自建git server地址。 +- （4）修改`client/config.ini`中的`TOOL_CONFIG_URL`为自建git server的`puppy-tools-config`仓库地址。 +- （5）填写`client/config.ini`中的`[TOOL_LOAD_ACCOUNT]`配置，输入有拉取权限的用户名密码，即可使用自建git server拉取工具。 + +### 3. git lfs带宽和存储配额不够问题 + +- 如果git拉取工具时，出现git lfs拉取失败，可能是lfs带宽和存储配额不够，可以打开对应的工具github页面，通过`Download ZIP`的方式下载工具压缩包，再解压到`client/data/tools`目录下。 diff --git "a/doc/zh/guide/\345\256\242\346\210\267\347\253\257/\345\270\270\351\251\273\350\212\202\347\202\271\345\210\206\346\236\220.md" "b/doc/zh/guide/\345\256\242\346\210\267\347\253\257/\345\270\270\351\251\273\350\212\202\347\202\271\345\210\206\346\236\220.md" index eff0e9571..2b81c31c1 100644 --- "a/doc/zh/guide/\345\256\242\346\210\267\347\253\257/\345\270\270\351\251\273\350\212\202\347\202\271\345\210\206\346\236\220.md" +++ "b/doc/zh/guide/\345\256\242\346\210\267\347\253\257/\345\270\270\351\251\273\350\212\202\347\202\271\345\210\206\346\236\220.md" @@ -1,7 +1,7 @@ # 常驻节点分析 ::: tip -TCA客户端除了通过`localscan`命令启动单次的代码分析，也可以作为一个分布式分析节点启动，作为常驻进程，多个节点可以分布式并行执行服务端下发的任务，提高扫描效率。 +TCA 客户端除了通过`localscan`命令启动单次的代码分析，也可以作为一个分布式分析节点启动，作为常驻进程，多个节点可以分布式并行执行服务端下发的任务，提高扫描效率。 和本地分析一样，需要先安装环境和必要的工具，并配置好服务端地址。 ::: @@ -14,44 +14,69 @@ TCA客户端除了通过`localscan`命令启动单次的代码分析，也可以 ## 前置步骤 -公共/专有机器上具备客户端。 +节点机器上具备客户端及客户端相关依赖环境，可查阅[本地分析-前置步骤](本地分析.md#前置步骤)部分进行配置。 -如果是开源版客户端，需要配置相关环境和依赖，可查阅[开源版客户端使用说明](配置说明.md#开源版客户端使用说明)。 - -## 常驻节点配置 +## 节点配置 ### 配置 `config.ini` 文件 -- 将``替换成实际的serve ip（可包含端口号）。 +1. 将``替换成实际的 TCA 平台 IP（可包含端口号）。 + +2. 国内使用 github 拉取网络较慢，推荐使用腾讯工蜂拉取，需要修改以下配置： +- 修改 `TOOL_CONFIG_URL=https://git.code.tencent.com/TCA/tca-tools/puppy-tools-config.git` +- 将[腾讯工蜂](https://git.code.tencent.com)的账号密码填写到`TOOL_LOAD_ACCOUNT `中。（注：没有腾讯工蜂账号的需要注册；由于腾讯工蜂的开源仓库也要求使用账号才能拉取，所以此处必须填写账号密码） -### 启动代码分析常驻节点 +### 启动常驻节点 - 从TCA前端页面中获取 `token`，前往 **个人中心-个人令牌-复制Token** ::: tip - 作为公共节点：token需要具有超级管理员权限，如使用`CodeDog`账户的`token`。 - - 可以通过[用户管理页面](../后台管理/后台管理说明.md)查看到哪些用户是超级管理员。 - - 作为专机节点：该节点仅能分析该`token`具有权限的项目。 + 节点仅能分析该`token`具有权限的项目，因此如设置公共的分析节点，推荐使用超级管理员的token。 + + 可以通过[用户管理页面](../后台管理/用户管理.md)查看到哪些用户是超级管理员。 ::: -- 进入到`client`目录下，执行命令：`python3 codepuppy.py -l codepuppy.log start -t ` +- 如启动团队节点，还需获取团队编号：org_sid，获取方式： +从 TCA 平台项目概览页面URL中获取，项目概览URL格式：`http://{域名}/t/{org_sid}/p/{team_name}/profile` -- 启动后，可以在命令行输出或`codepuppy.log`中查看运行日志，如果未报异常，且输出`task loop is started.`，表示节点已经正常启动。 -### 配置节点 +**两种方式可选启动客户端：** +#### 使用客户端源码启动常驻节点 -常驻节点首次启动后，需要到节点管理页面设置节点状态（默认为`不可用`），将其设置为**`活跃`**，用于接收和执行任务。 +- 如启动公共节点，需进入到源码的`client`目录下，执行命令： +```bash +python3 codepuppy.py -l codepuppy.log start -t +``` -- 进入TCA节点管理页面。`管理入口`-`节点管理` +- 如启动团队节点，需增加参数 org_sid： +```bash +python3 codepuppy.py -l codepuppy.log start -t --org-sid +``` - 可以看到当前在线的节点，可以修改节点名称、标签、负责人等信息。 +启动后，可以在命令行输出或`codepuppy.log`中查看运行日志，如果未报异常，且输出`task loop is started.`，表示节点已经正常启动。 +#### 使用客户端二进制启动常驻节点 - ::: tip - 常驻节点首次启动后，需将节点状态从**不可用（失效）**状态切换到**活跃（在线）**状态 - ::: +- 如启动公共节点，需进入到源码的`client`目录下，执行命令： +```bash +./codepuppy -l codepuppy.log start -t +``` + +- 如启动团队节点，需增加参数 org_sid： +```bash +./codepuppy -l codepuppy.log start -t --org-sid +``` +启动后，可以在命令行输出或`codepuppy.log`中查看运行日志，如果未报异常，且输出`task loop is started.`，表示节点已经正常启动。 + +### 管理节点 + +常驻节点首次启动后，需要到节点管理页面管理节点状态： + +1. **设置节点状态：** + 进入 TCA 节点管理页面。`管理入口`-`节点管理`，可以看到当前在线的节点，节点状态默认为`不可用`，需将其设置为**`活跃`**才可用于接收和执行任务。 + 也可以按需修改节点名称、标签、负责人等信息。 -- 可以进入**工具进程配置**页面，对节点支持的工具进程进行管理（默认会全部勾选），未勾选的工具进程，将不会在该节点上执行。 +2. （按需可选）**配置节点工具进程：** + 进入**工具进程配置**页面，对节点支持的工具进程进行管理（默认会全部勾选），未勾选的工具进程，将不会在该节点上执行。 -- **节点所属标签**会与分析方案中的运行环境标签进行匹配，只有相同标签的任务才会下发到该机器节点上。 +3. （按需可选）**设置节点标签：** + 节点标签会与分析方案中的运行环境标签进行匹配，只有相同标签的任务才会下发到该机器节点上。 diff --git "a/doc/zh/guide/\345\256\242\346\210\267\347\253\257/\346\234\254\345\234\260\345\210\206\346\236\220.md" "b/doc/zh/guide/\345\256\242\346\210\267\347\253\257/\346\234\254\345\234\260\345\210\206\346\236\220.md" index 83e6e11a4..6fdbfaa04 100644 --- "a/doc/zh/guide/\345\256\242\346\210\267\347\253\257/\346\234\254\345\234\260\345\210\206\346\236\220.md" +++ "b/doc/zh/guide/\345\256\242\346\210\267\347\253\257/\346\234\254\345\234\260\345\210\206\346\236\220.md" @@ -1,58 +1,97 @@ -# 本地分析 +# 客户端本地分析 ## 使用场景 - 希望在本地随时分析。 -- 如果公共机器无法满足编译环境的情况，复用本地编译环境。 - -- 如果对代码安全有要求也推荐使用本地分析。 +- 接入持续集成系统实现自动化分析。 ## 前置步骤 +**1. 客户端运行环境机器配置推荐** + +| 操作系统 | 推荐配置 | +| --------: | :------------------------------------------- | +| Linux | 8核16G内存，硬盘空间256G（可用空间不低于100G） | +| Mac | 8核16G内存，硬盘空间256G（可用空间不低于100G） | +| Windows | 8核16G内存，硬盘空间256G（可用空间不低于100G） | + +以上为推荐配置，实际情况需要考虑扫描对象代码库的大小，按实际情况增加磁盘空间。 + +**2. 本地需具备客户端** + +下载[开源版源码](https://github.com/Tencent/CodeAnalysis)。 +或从[开源版release](https://github.com/Tencent/CodeAnalysis/releases)下载客户端以运行客户端二进制； + + +**3. 安装Python环境和第三方库（仅客户端源码启动分析需要）** +- 预装Python3.7、pip，支持 `python3` 和 `pip3` 命令 +- 安装依赖：`pip3 install -r CodeAnalysis/client/requirements/app_reqs.pip` -本地具备客户端。 +**4. 安装第三方工具（docker下启动分析可跳过）** +- 进入到`client/requirements`目录 +- 在命令行中执行安装脚本`install.sh`(linux/mac环境)或`install.bat`(windows环境) -如果是开源版客户端，需要配置相关环境和依赖，可查阅[开源版客户端使用说明](配置说明.md#开源版客户端使用说明)。 ## 分析配置 ### 配置客户端 `config.ini` 文件 -将 `` 替换成实际的serve ip（可包含端口号） +1. 将 `` 替换成实际的TCA平台IP（可包含端口号） -### 配置客户端 `codedog.ini` 文件 +2. 国内使用github拉取网络较慢，推荐使用腾讯工蜂拉取，需要修改以下配置： +- 修改 `TOOL_CONFIG_URL=https://git.code.tencent.com/TCA/tca-tools/puppy-tools-config.git` +- 将[腾讯工蜂](https://git.code.tencent.com)的账号密码填写到`TOOL_LOAD_ACCOUNT `中。（注：没有腾讯工蜂账号的需要注册；由于腾讯工蜂的开源仓库也要求使用账号才能拉取，所以此处必须填写账号密码） -- `token`，必填项。从TCA前端页面中获取，前往 **个人中心-个人令牌-复制Token** +### 配置客户端 `codedog.ini` 文件 -- `org_sid`，团队编号，必填项。可以从TCA前端项目页面URL获取。 +`codedog.ini`获取方法： +- 方法一： 下载TCA源码或[开源版release](https://github.com/Tencent/CodeAnalysis/releases)的客户端包，在源码目录中复制`CodeAnalysis/client/codedog.ini`并按文件内配置说明进行修改。 +- 方法二： 在TCA平台平台上配置好对应信息后，下载配置文件到本地使用。 -- `team_name`，项目名称，必填项。可以从TCA前端项目页面URL获取。 + ![下载配置文件](../../../images/start_scan_03.png) - ```bash - # 如 - http://{域名}/t/{org_sid}/p/{team_name}/profile - ``` +`codedog.ini`中以下字段为必填项： -- `source_dir`，本地代码目录路径，必填项。绝对路径。 +| 字段名 | 填写说明 | +| :-------- | :------------------------------------------- | +|`token` | 从TCA平台页面获取，前往[个人中心]-[个人令牌]-复制Token | +|`org_sid`(团队编号) | 从TCA平台项目概览页面URL中获取，项目概览URL格式：`http://{域名}/t/{org_sid}/p/{team_name}/profile` | +|`team_name`(项目名称) | 同上 | +|`source_dir` | 本地代码目录路径 | -- 其他参数 - - 按需填写其他可选项，也可以不填，按默认配置执行 +其他字段按需填写。 ## 启动代码分析 -### 源码下启动分析 +启动客户端分析有三种方式可选：[客户端源码下启动分析](#客户端源码下启动分析)、[客户端二进制启动分析](#客户端二进制启动分析)、[docker下启动分析](#docker下启动分析) +### 客户端源码下启动分析 + +- 进入到客户端`client`目录下 -- 进入到`client`目录下 +- 执行命令： + 客户端源码：`python3 codepuppy.py localscan` -- 执行命令：`python3 codepuppy.py localscan` +### 客户端二进制启动分析 +- 进入到客户端`client`目录下 + +- 执行命令： + 客户端源码：`./codepuppy localscan` ### docker下启动分析 +#### 1. 构建docker镜像 +在client目录下，执行以下命令：`docker build -t tca-client .` +**(需已安装Docker)** + +#### 2. 执行Docker容器 +::: warning +注意：因为以下步骤会将代码目录挂载到容器中，需要先将codedog.ini里面的source_dir修改为/workspace/src，其他参数保持不变。 +::: + +执行Docker容器有以下两种方式： #### 直接使用docker运行 -- 在client目录下，执行以下命令： -- (注意：按照实际情况填写`SOURCE_DIR`环境变量值) + 在`client`目录下，执行以下命令：(注意：按照实际情况填写`SOURCE_DIR`环境变量值) ```bash export SOURCE_DIR=需要扫描的代码目录绝对路径 @@ -61,9 +100,8 @@ docker run -it --rm -v $PWD:/workspace/client -v $SOURCE_DIR:/workspace/src -- #### 使用docker内bash终端运行 -- 通过以下方式，进入容器内的bash终端后，通过命令行启动client代码： -- 在client目录下，执行以下命令： -- (注意：按照实际情况填写`SOURCE_DIR`环境变量值) + 通过以下方式，进入容器内的bash终端后，通过命令行启动client代码： + 在`client`目录下，执行以下命令：(注意：按照实际情况填写`SOURCE_DIR`环境变量值) ```bash export SOURCE_DIR=需要扫描的代码目录绝对路径 diff --git "a/doc/zh/guide/\345\256\242\346\210\267\347\253\257/\351\205\215\347\275\256\350\257\246\346\203\205.md" "b/doc/zh/guide/\345\256\242\346\210\267\347\253\257/\351\205\215\347\275\256\350\257\246\346\203\205.md" deleted file mode 100644 index 8cbe12b5a..000000000 --- "a/doc/zh/guide/\345\256\242\346\210\267\347\253\257/\351\205\215\347\275\256\350\257\246\346\203\205.md" +++ /dev/null @@ -1,26 +0,0 @@ -## 在线分析 - -在线分析即是通过Server端将分析任务注册到执行队列中，并将任务分配到平台配置的常驻节点上，在常驻节点执行分析，分析完毕后将分析结果上报入库。 - -::: tip -平台需要存在常驻节点，请查阅 [常驻节点分析](./常驻节点分析.md) - -否则任务因没有机器而无法完成分配，超时后任务会注销。 -::: - -## 客户端分析 - -客户端分析即是本地分析，可直接配置本地的客户端配置文件，或在平台上配置好对应信息后，下载配置文件，替换客户端配置问题，并启动客户端分析。分析完毕后会将数据上报入库。 - -- 下载配置文件 - - ![下载配置文件](../../../images/start_scan_03.png) - -- 替换客户端配置文件，并启动客户端分析。 - -::: tip -本地需要下载客户端，请查阅 - -- [部署与配置客户端](../../quickStarted/deployClient.md) -- [客户端使用说明文档](./本地分析.md) -::: \ No newline at end of file diff --git "a/doc/zh/guide/\345\277\253\351\200\237\345\205\245\351\227\250/\345\277\253\351\200\237\345\220\257\345\212\250\344\270\200\346\254\241\344\273\243\347\240\201\345\210\206\346\236\220.md" "b/doc/zh/guide/\345\277\253\351\200\237\345\205\245\351\227\250/\345\277\253\351\200\237\345\220\257\345\212\250\344\270\200\346\254\241\344\273\243\347\240\201\345\210\206\346\236\220.md" index 70bdc82cd..7af389ee8 100644 --- "a/doc/zh/guide/\345\277\253\351\200\237\345\205\245\351\227\250/\345\277\253\351\200\237\345\220\257\345\212\250\344\270\200\346\254\241\344\273\243\347\240\201\345\210\206\346\236\220.md" +++ "b/doc/zh/guide/\345\277\253\351\200\237\345\205\245\351\227\250/\345\277\253\351\200\237\345\220\257\345\212\250\344\270\200\346\254\241\344\273\243\347\240\201\345\210\206\346\236\220.md" @@ -1,20 +1,17 @@ # 快速启动一次代码分析 -## 创建项目 +## 创建团队及项目 -- **创建团队并进入** +- **创建团队** + 点击了解[团队管理](../团队管理/团队管理.md) ![创建团队](../../../images/create_team.png) - :::tip - 还没有团队？点击了解[团队管理](../团队管理/团队管理.md) - ::: - - **为团队创建一个项目，或选择一个已有项目，并进入项目内** ![创建项目](../../../images/create_team_group.png) -## 完成代码库登记 +## 登记代码库 - **完成代码库登记，并点击进入代码分析** @@ -22,7 +19,7 @@ ![进入代码分析](../../../images/start_scan_01.png) -## 开启第一次代码分析 +## 启动代码分析 ### 执行初始化创建 @@ -30,8 +27,8 @@ ::: tip - 1. 用户可选择使用分析方案模板，或创建分析方案的方式，利用方案的分析配置进行代码分析。 - 2. 点击确认时，平台会首先创建该代码库的分析方案，然后根据代码库分支、当前分析方案创建分支项目，最终下载客户端分析配置文件，客户端执行代码分析。 + 1. 首次开启代码分析，用户可选择使用已有的分析方案模板，或创建分析方案的。 + 2. 点击确认时，平台会首先创建该代码库的分析方案，然后根据代码库分支、当前分析方案创建分支项目，供用户启动代码分析。 ::: ### 执行代码分析 @@ -42,27 +39,20 @@ #### 在线分析 -在线分析即是通过Server端将分析任务注册到执行队列中，并将任务分配到平台配置的常驻节点上，在常驻节点执行分析，分析完毕后将分析结果上报入库。 +在线分析即是通过Server端将分析任务注册到执行队列中，并将任务分配到平台配置的常驻分析节点上进行，分析完毕后将分析结果上报入库。 ::: tip -平台需要存在常驻节点，请查阅 [常驻节点分析](../客户端/常驻节点分析.md) +使用在线分析要求平台具有常驻分析节点： +- 如您的TCA平台是使用官方一键部署脚本完成的环境部署（Docker部署、Docker-Compose部署、源码部署三种），默认已启动一个分析节点（即客户端），可直接用于在线分析。可查看[管理入口-节点管理](../后台管理/节点管理.md)确认该节点状态。 + +- 您也可自行接入更多分析节点实现并行执行代码分析，接入节点操作请查阅[常驻节点分析](../客户端/常驻节点分析.md) -否则任务因没有机器而无法完成分配，超时后任务会注销。 +**如无分析节点，在线分析任务将无法完成分配，未分配任务将于超时后自动注销**。 ::: #### 客户端分析 -客户端分析即是本地分析，可直接配置本地的客户端配置文件，或在平台上配置好对应信息后，下载配置文件，替换客户端配置问题，并启动客户端分析。分析完毕后会将数据上报入库。 - -- 下载配置文件 - - ![下载配置文件](../../../images/start_scan_03.png) - -- 替换客户端配置文件，并启动客户端分析。 - -::: tip -本地需要下载客户端，请查阅 [客户端使用说明文档](../客户端/本地分析.md) -::: +客户端分析即是本地分析，需要在本地有客户端，并配置好客户端配置文件 `codedog.ini`，详细操作参考：[启动客户端分析](../客户端/本地分析.md)。分析完毕后会将数据上报入库。 ## 查看分析历史 diff --git a/doc/zh/quickStarted/FAQ.md b/doc/zh/quickStarted/FAQ.md index 481d771b8..ed4d5b7d4 100644 --- a/doc/zh/quickStarted/FAQ.md +++ b/doc/zh/quickStarted/FAQ.md @@ -1,4 +1,4 @@ -# 常见问题 +# FAQ :::tip 该Q&A文档会持续更新，非常欢迎您的建议与共建！ @@ -195,19 +195,7 @@ ln -s /usr/local/python3/bin/celery /usr/local/bin/celery ### 2. 服务启动与初始化 -#### 2.1 ``compose_init.sh``脚本需要填写的密码是什么？ - -执行``compose_init.sh``提示需要输入的密码是数据库的初始化密码，默认为``TCA!@#2021`` - -```bash -$ ./compose_init.sh -Recreating tca_open_source_mysql_1 ... done -Recreating tca_open_source_redis_1 ... done -wait db [DB default password: TCA!@#2021] -Enter password: <此处输入'TCA!@#2021'> -``` - -#### 2.2 服务占用端口异常 +#### 2.1 服务占用端口异常 TCA 本地部署启动后，会监听多个端口： @@ -227,7 +215,7 @@ TCA 本地部署启动后，会监听多个端口： 不推荐调整TCA指定服务的端口号，需要调整多处配置，以及可能会影响到后续服务的升级 -#### 2.3 服务输出日志找不到 +#### 2.2 服务输出日志找不到 本地部署输出的日志位置： diff --git a/doc/zh/quickStarted/README.md b/doc/zh/quickStarted/README.md new file mode 100644 index 000000000..433733d4f --- /dev/null +++ b/doc/zh/quickStarted/README.md @@ -0,0 +1,21 @@ +# 腾讯云代码分析介绍 + +**腾讯云代码分析**（Tencent Cloud Code Analysis，简称TCA，内部曾用研发代号 CodeDog ）是集众多分析工具的云原生、分布式、高性能的代码综合分析跟踪平台，包含**服务端、Web端、客户端**三个组件，已集成一批自研工具，同时也支持动态集成业界各编程语言的分析工具。 + +**代码分析**是通过词法分析、语法分析、控制流、数据流分析等技术对程序代码进行扫描，对代码进行综合分析，验证代码是否满足规范性、安全性、可靠性、可维护性等指标的一种代码分析技术。 + +使用TCA可以帮助团队用代码分析技术查找代码中的规范性、结构性、安全漏洞等问题，持续监控项目代码质量并进行告警。同时TCA开放API，支持与上下游系统对接，从而集成代码分析能力，为代码质量提供保障，更有益于传承优良的团队代码文化。 + +![组件图](https://tencent.github.io/CodeAnalysis/media/Components.png) + +![流程图](https://tencent.github.io/CodeAnalysis/media/Flow.png) + +--- + +拉取 TCA [代码库](https://github.com/Tencent/CodeAnalysis) 后，首次体验推荐您使用[ Docker 快速部署](./dockerDeploy.md)方式快速搭建和体验腾讯云代码分析平台。 + +如您更多环境需求，也可通过以下两种方式部署腾讯云代码分析平台： +- [通过 Docker-Compose 部署](./dockercomposeDeploy.md) +- [通过源代码部署](./codeDeploy.md) + + diff --git a/doc/zh/quickStarted/codeDeploy.md b/doc/zh/quickStarted/codeDeploy.md index cdce367d9..f5c205be4 100644 --- a/doc/zh/quickStarted/codeDeploy.md +++ b/doc/zh/quickStarted/codeDeploy.md @@ -1,5 +1,8 @@ -# 源码部署 -兼容旧版的部署方式 +# 源代码快速部署 +TCA提供部署脚本，支持一键式快速部署Server、Web、Client。 +脚本共提供三种部署方式：[Docker部署(平台体验首推)](./dockerDeploy.md)、[Docker-Compose部署](./dockercomposeDeploy.md)、源码部署， +可根据您的具体使用场景任意选择其一进行部署。 + #### 依赖环境 - 系统环境 @@ -7,24 +10,24 @@ - 最低配置：2核4G内存、100G硬盘存储空间 - 环境准备 -> 目前TCA脚本已封装好Python、Mariadb、Redis与Nginx安装步骤，可以按“操作说明”内容进行操作 - - **Python 3.7** + :::tip + TCA 一键部署脚本已封装好 Python、Mariadb、Redis 与 Nginx 安装步骤，**无需自行安装**，**本地部署体验**可按 [操作说明](#操作说明) 内容直接进行部署操作。 - - **MySQL服务（MySQL5.7.8以上版本或Mariadb 10.5以上版本）** + **注意：生产环境建议使用专业的 MySQL、Redis 等服务** + ::: + - Python 3.7 - - **Redis服务（4.0版本以上）** + - MySQL 服务（MySQL5.7.8 以上版本或 Mariadb 10.5 以上版本） - - **Nginx服务** + - Redis 服务（4.0版本以上） - :::warning - 仅适用于本地部署体验，生产环境建议使用专业的 MySQL、Redis 等服务 - ::: + - Nginx 服务 - 权限准备 - 环境权限：安装 Server 依赖软件（python、nginx、yum 等软件包）需要使用 ROOT 权限 - - 启动 Server服务时可以使用非 ROOT 用户运行 + - 启动 Server 服务时可以使用非 ROOT 用户运行 - 数据库权限：Server 服务执行数据库初始化需要依赖 ``CREATE、ALTER、INDEX、DELETE、LOCK TABLES、SELECT、INSERT、REFERENCES、UPDATE`` 权限 - 端口使用：需要开放80端口的访问权限(80为TCA平台默认访问端口)，或调整 Web 服务默认的访问端口地址 @@ -32,59 +35,78 @@ ##### 首次启动操作 -1. 进入CodeAnalysis工作目录（例如``~/CodeAnalysis``)，以下路径均为目录内的相对路径 -2. 安装基础软件与部署TCA（可根据脚本选项确定是否要安装Python、MySQL、Redis、Nginx相关基础软件），执行 +1. 进入 CodeAnalysis 工作目录（例如``~/CodeAnalysis``)，以下路径均为目录内的相对路径 + +2. 安装基础软件与部署 TCA（可根据脚本选项确定是否要安装 Python、MySQL、Redis、Nginx 相关基础软件），执行 ```bash $ bash ./quick_install.sh local deploy ``` + 执行该命令会做以下四个步骤： - - Install：检测本地Python3.7、Mariadb/MySQL、Redis与Nginx，如果不存在会提示安装 - - Init：部署TCA Server、Web与Client，并进行初始化 - - Start：启动TCA Server、Web与Client - - Check：检测TCA的运行状态 + - `Install`：检测本地 Python3.7、Mariadb/MySQL、Redis 与 Nginx，如果不存在会提示安装 + - `Init`：部署 TCA Server、Web与Client，并进行初始化 + - `Start`：启动 TCA Server、Web与Client + - `Check`：检测 TCA 的运行状态 - >注：在运行过程中，脚本会检测本地是否安装了相关基础软件（Python3.7、MySQL/Mariadb、Redis、Nignx），如果未安装会输出以下类似提示语： - >``` - >Do you want to install [Redis] by this script? - >Please enter:[Y/N] - >``` - >如果确定通过脚本安装可以输入`Y`。 + **注意**：在运行过程中，脚本会检测本地是否安装了相关基础软件（Python3.7、MySQL/Mariadb、Redis、Nignx），如果未安装会输出以下类似提示语： + ```bash + Do you want to install [Redis] by this script? + Please enter:[Y/N] + ``` + 如果确定通过脚本安装可以输入`Y`。 + + 3. 执行完成，无其他报错，即可登录： - - TCA 平台初始登录账号是``CodeDog``，密码是``admin``， + +:::tip +至此，您已完成 TCA 平台部署，请在浏览器输入`http://部署机器IP/`，点击立即体验，完成登录后即可开启您的腾讯云代码分析。 +平台内操作指引请查看：[快速启动一次代码分析](../guide/快速入门/快速启动一次代码分析.md) + +默认平台登录账号/密码：CodeDog/admin + +如部署过程中，已调整默认账号密码，请按照调整后的账号密码进行登录 +::: + ##### 更新操作 -1. 更新代码 -2. 执行以下命令： - - `bash ./quick_install.sh local install tca`：更新相关配置 - - `bash ./quick_install.sh local start`：启动服务（会自动关闭之前的服务） - - `bash ./quick_install.sh local check`：检查服务是否启动失败 - -注： -1. `local install`命令行参数说明： - - `base`：安装Python、Mariadb/MySQL、Redis与Nginx - - `tca`：初始化或更新TCA Server、Web、Client相关配置和数据 - - `server`：初始化或更新TCA Server相关配置和数据 - - `web`：初始化或更新TCA Web相关配置和数据 - - `client`：初始化或更新TCA Client相关配置和数据 - - 不填参数，默认会执行`base`、`tca`相关操作 +**1. 更新代码** + +**2. 执行以下命令** +```bash +bash ./quick_install.sh local install tca #更新相关配置 +bash ./quick_install.sh local start #启动服务（会自动关闭之前的服务） +bash ./quick_install.sh local check #检查服务是否启动失败 +``` +**注意：** + `local install`命令行参数说明： + - `base`：安装 Python、Mariadb/MySQL、Redis 与 Nginx + - `tca`：初始化或更新 TCA Server、Web、Client 相关配置和数据 + - `server`：初始化或更新 TCA Server 相关配置和数据 + - `web`：初始化或更新 TCA Web 相关配置和数据 + - `client`：初始化或更新 TCA Client 相关配置和数据 + - 不填参数，默认会执行`base`、`tca`相关操作 ##### 启动和停止服务 - 启动所有服务：`bash ./quick_install.sh local start` + - 启动Main相关服务：`bash ./quick_install.sh local start main` - `local start`支持启动指定服务，如上述的启动Main服务，还支持`mysql/redis/analysis/file/login/scmproxy/nginx/client/all` -- 停止所有服务：`.bash /quick_install.sh local stop` + +- 停止所有服务：`bash /quick_install.sh local stop` + - 停止Main相关服务：`bash ./quick_install.sh local stop main` - `local stop`支持停止指定服务，如上述的停止Main服务，还支持`analysis/file/login/scmproxy/nginx/client/all` -注： +**注意：** 1. 启动时会自动关闭之前已经运行的服务 -2. `local start`支持启动指定服务，如上述的启动Main服务，还支持`mysql/redis/main/analysis/file/login/scmproxy/nginx/all` - - `mysql`和`redis`默认会使用`systemctl`进行启动，如果`systemctl`无法使用，则会直接使用`nohup`方式运行相关服务 + +2. `mysql`和`redis`默认会使用`systemctl`进行启动，如果`systemctl`无法使用，则会直接使用`nohup`方式运行相关服务 ##### 检查服务运行状态 检查服务运行状态：`bash ./quick_install.sh local check` - - 目前支持检查server与web，暂不支持client + - 目前支持检查 server 与 web，暂不支持 client ##### 获取服务输出日志 -打印TCA Server各个服务的日志路径： `bash ./quick_install.sh local log` \ No newline at end of file +打印 TCA Server 各个服务的日志路径： `bash ./quick_install.sh local log` + diff --git a/doc/zh/quickStarted/dockerDeploy.md b/doc/zh/quickStarted/dockerDeploy.md new file mode 100644 index 000000000..3c5fc8ae7 --- /dev/null +++ b/doc/zh/quickStarted/dockerDeploy.md @@ -0,0 +1,70 @@ +# Docker快速部署（平台体验首推） + +:::warning +Docker部署会包含Mariadb和Redis，如果需要更大规模使用，可以调整配置文件使用运维规范的 MySQL/Mariadb 和 Redis。 + +::: + +#### 依赖环境 + +- 系统环境 + - Linux、macOS、Windows + - 最低配置：2核4G内存、100G硬盘存储空间 +- 环境准备 + - Docker +- 权限准备 + - 需要开放80、8000端口的访问权限(80为TCA平台访问端口，8000为TCA Server访问端口) + +#### 部署对象 +Server、Web 与 Client + +#### 操作说明 +##### 首次启动操作 + +1. 进入CodeAnalysis工作目录（例如``~/CodeAnalysis``)，以下路径均为目录内的相对路径 +2. 执行命令： + ```bash + bash ./quick_install.sh docker deploy + ``` +::: tip +1. 通过Docker部署默认会从DockerHub上拉取``tencenttca/tca:latest``镜像 +2. 通过Docker部署默认会在当前根目录下的挂载三个路径： + - `.docker_temp/logs`：容器内的`/var/log/tca/`，存放TCA平台的日输出文件； + - `.docker_temp/data`：容器内的`/var/opt/tca/`， 存放TCA平台的服务数据，主要是Mariadb、Redis； + - `.docker_temp/configs`：容器内的``/etc/tca``，存放TCA平台的配置文件，主要是`config.sh` +::: + +##### 更新操作 +1. 更新代码 +2. 执行以下命令： +```bash +TCA_IMAGE_BUILD=true ./quick_install.sh docker deploy #重新构建并启动tca容器 +``` +::: tip +`TCA_IMAGE_BUILD=true`表示从本地构建TCA镜像运行 +::: + + + +##### 运行容器 +如果已经在机器上执行过`docker deploy`，并保留容器数据的，可以执行以下命令启动容器，继续运行TCA + +```bash +bash ./quick_install.sh docker start +``` + +##### 停止容器 +如果容器正在运行，希望停止容器，可以运行 + +```bash +bash ./quick_install.sh docker stop +``` + +#### 使用TCA +至此，您已完成第一个TCA平台部署，请在浏览器输入`http://部署机器IP/`，点击立即体验，完成登录后即可开启您的腾讯云代码分析。 +平台内操作指引请查看：[快速启动一次代码分析](../guide/快速入门/快速启动一次代码分析.md) +:::tip +默认平台登录账号/密码：CodeDog/admin + +如部署过程中，已调整默认账号密码，请按照调整后的账号密码进行登录 +::: diff --git a/doc/zh/quickStarted/dockercomposeDeploy.md b/doc/zh/quickStarted/dockercomposeDeploy.md index 9e67309d0..a19842f7e 100644 --- a/doc/zh/quickStarted/dockercomposeDeploy.md +++ b/doc/zh/quickStarted/dockercomposeDeploy.md @@ -1,35 +1,53 @@ # Docker-Compose快速部署 +TCA提供部署脚本，支持一键式快速部署 Server、Web、Client。 +脚本共提供三种部署方式：[Docker部署(平台体验首推)](./dockerDeploy.md)、Docker-Compose部署、[源码部署](./codeDeploy.md)， +可根据您的具体使用场景任意选择其一进行部署。 + #### 部署对象 Server、Web 与 Client :::warning -仅适用于Docker-Compose部署体验，生产环境建议使用专业的 MySQL、Redis 等服务 -兼容之前的部署方式 +仅适用于 Docker-Compose 部署体验，生产环境建议使用专业的 MySQL、Redis 等服务 ::: #### 操作说明 ##### 首次启动操作 -1. 进入CodeAnalysis工作目录（例如``~/CodeAnalysis``)，以下路径均为目录内的相对路径 +1. 进入 CodeAnalysis 工作目录（例如``~/CodeAnalysis``)，以下路径均为目录内的相对路径 + 2. 执行命令： - - `bash ./quick_install.sh docker-compose deploy`：启动tca_server容器 +``` bash +bash ./quick_install.sh docker-compose deploy #启动tca_server容器 +``` +注意：通过 Docker-Compose 部署默认会在当前根目录下的挂载三个路径： -注意：通过Docker-Compose部署默认会在当前根目录下的挂载三个路径： +- `.docker_data/logs`：存放 TCA 平台的各个服务日志输出目录； +- `.docker_data/mysql`：存放 TCA 平台的 MySQL 数据 +- `.docker_data/redis`：存放 TCA 平台的 Redis 数据 +- `.docker_data/filedata`：存放 TCA 平台文件服务器的文件 -- `.docker_data/logs`：存放TCA平台的各个服务日志输出目录； -- `.docker_data/mysql`：存放TCA平台的MySQL数据 -- `.docker_data/redis`：存放TCA平台的Redis数据 -- `.docker_data/filedata`：存放TCA平台文件服务器的文件 + +:::tip +完成 TCA 平台部署后，请在浏览器输入`http://部署机器IP/`，点击立即体验，完成登录后即可开启您的腾讯云代码分析。 +平台内操作指引请查看：[快速启动一次代码分析](../guide/快速入门/快速启动一次代码分析.md) + +默认平台登录账号/密码：CodeDog/admin + +如部署过程中，已调整默认账号密码，请按照调整后的账号密码进行登录 +::: ##### 更新操作 1. 更新代码 + 2. 执行以下命令： - - `bash ./quick_install.sh docker-compose build`：重新构建TCA相关镜像 - - `bash ./quick_install.sh docker-compose stop`：停止运行中的TCA容器 - - `bash ./quick_install.sh docker-compose deploy`: 重新部署TCA相关容器与初始化（或刷新数据） +``` bash +bash ./quick_install.sh docker-compose build #重新构建TCA相关镜像 +bash ./quick_install.sh docker-compose stop #停止运行中的TCA容器 +bash ./quick_install.sh docker-compose deploy #重新部署TCA相关容器与初始化（或刷新数据） +``` ##### 运行操作 -如果已经在机器上执行过``docker-compose deploy``，并保留容器数据的，可以执行以下命令启动容器，继续运行TCA +如果已经在机器上执行过``docker-compose deploy``，并保留容器数据的，可以执行以下命令启动容器，继续运行 TCA ```bash bash ./quick_install.sh docker-compose start @@ -45,6 +63,6 @@ bash ./quick_install.sh docker-compose stop ##### 构建镜像操作 如果希望构建镜像，可以执行以下命令 -``` +```bash bash ./quick_install.sh docker-compose build ``` \ No newline at end of file diff --git a/doc/zh/quickStarted/enhanceDeploy.md b/doc/zh/quickStarted/enhanceDeploy.md index fa67f3c50..734db135c 100644 --- a/doc/zh/quickStarted/enhanceDeploy.md +++ b/doc/zh/quickStarted/enhanceDeploy.md @@ -3,7 +3,9 @@ TCA 除开集成业界知名的分析工具之外，也有自主研发的独立 TCA 增强分析模块，需要用户额外部署 License 鉴权微服务，并邮件申请 License 。 -**注意：License申请完全免费！** +::: tip +**注意：License申请完全免费！** +::: ## 概念 - 独立工具：TCA 自主研发的代码分析工具； @@ -16,13 +18,15 @@ TCA 增强分析模块，需要用户额外部署 License 鉴权微服务，并 - 支持Java/Kotlin API和函数调用链分析； - 支持代码安全、空指针检查、内存泄漏等规则。 +**持续更新中……** ## CLS部署 ### 准备 - 一台 CLS 微服务专属机器，CLS 微服务需要跟该机器绑定 ### 步骤 -1. 在 [CLS](https://github.com/Tencent/CodeAnalysis/tree/main/server/cls) 目录下执行以下命令，获取 Server ID 和 Client License +1. 在 TCA 源码中[`server/cls`](https://github.com/Tencent/CodeAnalysis/tree/main/server/cls) 目录下执行以下命令，获取 `Server ID` 和 `Client License` + ```shell $ ./cls server 2022-04-13 18:35:29.356510559 +0800 CST [INFO] Version: 20220328.1 @@ -30,22 +34,23 @@ $ ./cls server xxx 2022-04-13 18:35:29.454552966 +0800 CST [INFO] License Server ID: xxx ``` -- Server ID: 机器码，用于跟TCA团队申请License授权 -- Client License: 提供给TCA Client, 方便TCA Client进行工具鉴权（重要，建议备份留底） +- `Server ID`: 机器码，用于向 TCA 团队申请 License 授权 +- `Client License`: 提供给 TCA Client，方便 TCA Client 进行工具鉴权（重要，建议备份留底） + +2. 在 TCA Client目录的 [`config.ini`](https://github.com/Tencent/CodeAnalysis/blob/main/client/config.ini) 中配置 CLS 微服务信息，比如 -2. 在 TCA Client 的 [config.ini](https://github.com/Tencent/CodeAnalysis/blob/main/client/config.ini) 中配置 CLS 微服务，比如 ```ini [LICENSE_CONFIG] ; [可选]使用独立工具时，需要填写，默认不需要 -; License服务器url, base_path, license URL=http://: +;License服务的域名和端口 BASE_PATH= -LICENSE= +LICENSE= ``` -3. 跟 TCA 团队邮件申请 License +3. 向 TCA 团队邮件申请 License -- 发送邮箱： +- 收件邮箱： ``` v_cocohwang@tencent.com anjingliu@tencent.com @@ -53,11 +58,12 @@ yalechen@tencent.com tommyzhang@tencent.com ``` -- 格式如下： +- 申请邮件格式如下： -TCA独立工具License申请邮件 +主题：**TCA 独立工具 License 申请** -| | | +正文： +| | | | :----: | :----: | | 申请人名称 | xxx | | 申请人所在组织名称 | xxx | @@ -67,18 +73,24 @@ TCA独立工具License申请邮件 | 首次登记的机器码 | xxx | | 体验申请用途 | xxx | -4. 收到 TCA 团队回复邮件之后，在 CLS 目录下的[config.yaml](https://github.com/Tencent/CodeAnalysis/blob/main/server/cls/config.yaml)文件中填写License -注意！请遵从yaml格式，比如： -- 键值对中，冒号 `:` 后面一定要跟一个空白字符，示例 `key: value`. +4. 收到 TCA 团队回复邮件之后，在 CLS 目录下的[`config.yaml`](https://github.com/Tencent/CodeAnalysis/blob/main/server/cls/config.yaml)文件中填写License + +::: warning +注意：遵从yaml格式， +比如： +- 键值对中，冒号 `:` 后面跟一个空白字符，示例 `key: value`. +::: + +5. 执行以下命令启动CLS -5. 执行以下命令启动 ```shell ./cls server -d ``` 6. 启动 TCA 分析任务 +在 TCA 平台的分析方案里面勾选独立工具相关的规则包。 -### 运维 +### CLS 运维 #### 自动重启 ```shell # 查找CLS进程ID @@ -87,6 +99,3 @@ ps aux|grep cls kill -USR2 ``` -## 使用 - -在 TCA 对应项目的分析方案里面勾选名称以 `TCA-Armory` 开头的工具的规则。 From 371e900bdbda63e0d554a40a89e4f7bcd0e90866 Mon Sep 17 00:00:00 2001 From: aaaa-j Date: Fri, 26 Aug 2022 14:30:33 +0800 Subject: [PATCH 2/2] =?UTF-8?q?=E6=8F=90=E4=BA=A4=E8=8B=B1=E6=96=87?= =?UTF-8?q?=E7=89=88=E7=9B=B8=E5=85=B3=E4=BF=AE=E6=94=B9,=E5=AF=B9?= =?UTF-8?q?=E9=BD=90=E4=B8=AD=E6=96=87=E7=89=88=E6=96=87=E6=A1=A3?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- doc/.vuepress/config.ts | 2 +- doc/.vuepress/configs/navbar/en.ts | 12 +- doc/.vuepress/configs/navbar/zh.ts | 10 +- doc/.vuepress/configs/sidebar/en.ts | 33 ++-- doc/.vuepress/configs/sidebar/zh.ts | 3 +- doc/en/README.md | 50 +----- .../install_mysql_on_centos.md | 0 .../install_nginx_from_source.md | 0 .../install_python37_on_centos.md | 0 .../install_python37_on_ubuntu.md | 0 .../install_redis_from_source.md | 0 .../install_redis_on_centos.md | 0 ...06\346\236\220\345\267\245\345\205\267.md" | 2 +- doc/en/community/changelog.md | 146 ++++++++++++++---- doc/en/guide/README.md | 13 +- ...36\346\200\247\351\205\215\347\275\256.md" | 10 +- ...02\347\202\271\347\256\241\347\220\206.md" | 78 +++------- ...66\344\273\226\351\205\215\347\275\256.md" | 28 ++++ ...02\347\202\271\345\210\206\346\236\220.md" | 71 ++++++--- ...54\345\234\260\345\210\206\346\236\220.md" | 92 +++++++---- ...15\347\275\256\350\257\246\346\203\205.md" | 26 ---- ...43\347\240\201\345\210\206\346\236\220.md" | 38 ++--- doc/en/quickStarted/FAQ.md | 18 +-- doc/en/quickStarted/README.md | 22 +++ doc/en/quickStarted/codeDeploy.md | 112 ++++++++------ doc/en/quickStarted/dockerDeploy.md | 70 +++++++++ doc/en/quickStarted/dockercomposeDeploy.md | 45 ++++-- doc/en/quickStarted/enhanceDeploy.md | 49 +++--- .../install_mysql_on_centos.md | 0 .../install_nginx_from_source.md | 0 .../install_python37_on_centos.md | 0 .../install_python37_on_ubuntu.md | 0 .../install_redis_from_source.md | 0 .../install_redis_on_centos.md | 0 34 files changed, 550 insertions(+), 380 deletions(-) rename doc/en/{quickStarted/references => advanced}/install_mysql_on_centos.md (100%) rename doc/en/{quickStarted/references => advanced}/install_nginx_from_source.md (100%) rename doc/en/{quickStarted/references => advanced}/install_python37_on_centos.md (100%) rename doc/en/{quickStarted/references => advanced}/install_python37_on_ubuntu.md (100%) rename doc/en/{quickStarted/references => advanced}/install_redis_from_source.md (100%) rename doc/en/{quickStarted/references => advanced}/install_redis_on_centos.md (100%) create mode 100644 "doc/en/guide/\345\256\242\346\210\267\347\253\257/\345\205\266\344\273\226\351\205\215\347\275\256.md" delete mode 100644 "doc/en/guide/\345\256\242\346\210\267\347\253\257/\351\205\215\347\275\256\350\257\246\346\203\205.md" create mode 100644 doc/en/quickStarted/README.md create mode 100644 doc/en/quickStarted/dockerDeploy.md rename doc/zh/{quickStarted/references => advanced}/install_mysql_on_centos.md (100%) rename doc/zh/{quickStarted/references => advanced}/install_nginx_from_source.md (100%) rename doc/zh/{quickStarted/references => advanced}/install_python37_on_centos.md (100%) rename doc/zh/{quickStarted/references => advanced}/install_python37_on_ubuntu.md (100%) rename doc/zh/{quickStarted/references => advanced}/install_redis_from_source.md (100%) rename doc/zh/{quickStarted/references => advanced}/install_redis_on_centos.md (100%) diff --git a/doc/.vuepress/config.ts b/doc/.vuepress/config.ts index 8f7c6f178..080e6a9c3 100644 --- a/doc/.vuepress/config.ts +++ b/doc/.vuepress/config.ts @@ -43,7 +43,7 @@ export default defineUserConfig({ }, '/en': { lang: 'en-US', - title: 'Tencent Code Analysis', + title: 'Tencent Cloud Code Analysis', description: '用心关注每行代码迭代、助力传承卓越代码文化！', }, }, diff --git a/doc/.vuepress/configs/navbar/en.ts b/doc/.vuepress/configs/navbar/en.ts index 1ddb3af9e..a93ce6b43 100644 --- a/doc/.vuepress/configs/navbar/en.ts +++ b/doc/.vuepress/configs/navbar/en.ts @@ -2,8 +2,8 @@ import type { NavbarConfig } from '@vuepress/theme-default' export const en: NavbarConfig = [ { - text: '快速入门', - link: '/en/quickStarted/deploySever.md', + text: '快速部署', + link: '/en/quickStarted/', }, { text: '帮助文档', @@ -24,9 +24,13 @@ export const en: NavbarConfig = [ ], }, { - text: '文章', + text: '依赖安装参考', children: [ - + '/en/advanced/install_python37_on_centos.md', + '/en/advanced/install_python37_on_ubuntu.md', + '/en/advanced/install_mysql_on_centos.md', + '/en/advanced/install_redis_from_source.md', + '/en/advanced/install_redis_on_centos.md', ], }, ] diff --git a/doc/.vuepress/configs/navbar/zh.ts b/doc/.vuepress/configs/navbar/zh.ts index 8d16435d3..1e49b9ec6 100644 --- a/doc/.vuepress/configs/navbar/zh.ts +++ b/doc/.vuepress/configs/navbar/zh.ts @@ -25,11 +25,11 @@ export const zh: NavbarConfig = [ { text: '依赖安装参考', children: [ - '/zh/quickStarted/references/install_python37_on_centos.md', - '/zh/quickStarted/references/install_python37_on_ubuntu.md', - '/zh/quickStarted/references/install_mysql_on_centos.md', - '/zh/quickStarted/references/install_redis_from_source.md', - '/zh/quickStarted/references/install_redis_on_centos.md', + '/zh/advanced/install_python37_on_centos.md', + '/zh/advanced/install_python37_on_ubuntu.md', + '/zh/advanced/install_mysql_on_centos.md', + '/zh/advanced/install_redis_from_source.md', + '/zh/advanced/install_redis_on_centos.md', ], }, ] diff --git a/doc/.vuepress/configs/sidebar/en.ts b/doc/.vuepress/configs/sidebar/en.ts index c0a628011..71276c220 100644 --- a/doc/.vuepress/configs/sidebar/en.ts +++ b/doc/.vuepress/configs/sidebar/en.ts @@ -66,9 +66,9 @@ export const en: SidebarConfig = { { text: '客户端', children: [ - '/en/guide/客户端/配置说明.md', '/en/guide/客户端/本地分析.md', '/en/guide/客户端/常驻节点分析.md', + '/en/guide/客户端/其他配置.md', ] }, { @@ -124,35 +124,20 @@ export const en: SidebarConfig = { { text: '快速入门', link: '/en/quickStarted/deploySever.md', - // children: [ - // { - // text: '快速入门', - // link: '/en/quickStarted/deploySever.md', - // }, - // ], - }, - { - text: '依赖安装参考', - // collapsible: true, - children: [ - '/en/quickStarted/references/install_python37_on_centos.md', - '/en/quickStarted/references/install_python37_on_ubuntu.md', - '/en/quickStarted/references/install_mysql_on_centos.md', - '/en/quickStarted/references/install_redis_on_centos.md', - '/en/quickStarted/references/install_redis_from_source.md', - '/en/quickStarted/references/install_nginx_from_source.md', - ], + children: + [ + '/en/quickStarted/README.md', + '/en/quickStarted/dockerDeploy.md', + '/en/quickStarted/dockercomposeDeploy.md', + '/en/quickStarted/codeDeploy.md', + ], }, { text: '其他', // collapsible: true, children: [ - '/en/quickStarted/intro.md', - '/en/quickStarted/tools.md', - '/en/quickStarted/FAQ.md', - '/en/quickStarted/codeDeploy.md', - '/en/quickStarted/dockercomposeDeploy.md', '/en/quickStarted/enhanceDeploy.md', + '/en/quickStarted/FAQ.md', ], }, ], diff --git a/doc/.vuepress/configs/sidebar/zh.ts b/doc/.vuepress/configs/sidebar/zh.ts index d6e693276..b70e12a6c 100644 --- a/doc/.vuepress/configs/sidebar/zh.ts +++ b/doc/.vuepress/configs/sidebar/zh.ts @@ -18,7 +18,7 @@ export const zh: SidebarConfig = { ] }, { - text: '分析结果', + text: '代码检查', children: [ '/zh/guide/代码检查/分析结果查看.md', '/zh/guide/代码检查/添加规则配置.md', @@ -135,7 +135,6 @@ export const zh: SidebarConfig = { // collapsible: true, children: [ '/zh/quickStarted/enhanceDeploy.md', - '/zh/quickStarted/tools.md', '/zh/quickStarted/FAQ.md', ], }, diff --git a/doc/en/README.md b/doc/en/README.md index e698dd0cd..ece2309fa 100644 --- a/doc/en/README.md +++ b/doc/en/README.md @@ -3,8 +3,8 @@ home: true title: 腾讯云代码分析文档 heroImage: /images/Logo.svg actions: - - text: 快速入门 - link: /zh/quickStarted/deploySever.html + - text: 快速部署 + link: /en/quickStarted/ type: primary - text: 帮助文档 link: /zh/guide/ @@ -34,49 +34,3 @@ footer: MIT Licensed | Copyright © 1998-present Tencent. All Rights Reserved. ### Repo Mirror [https://git.code.tencent.com/Tencent_Open_Source/CodeAnalysis.git](https://git.code.tencent.com/Tencent_Open_Source/CodeAnalysis.git) - -### What is TCA - -Tencent Cloud Code Analysis (TCA for short, code-named **CodeDog** inside the company early) is a comprehensive platform for code analysis and issue tracking. TCA consist of three components, server, web and client. It integrates of a number of self-developed tools, and also supports dynamic integration of code analysis tools in various programming languages. - -Code analysis is a technology, using lexical analysis, syntax analysis, control-flow analysis, data-flow analysis to make a comprehensive analysis of the code, so as to verify whether the code meets the requirements of normative, security, reliability, maintainability and other indicators. - -Using TCA can help team find normative, structural, security vulnerabilities and other issues in the code, continuously monitor the quality of the project code and issue alerts. At the same time, TCA opens up APIs to support connection with upstream and downstream systems, so as to integrate code analysis capabilities, ensure code quality, and be more conducive to inheriting an excellent team code culture. - -![组件图](https://tencent.github.io/CodeAnalysis/media/Components.png) - -![流程图](https://tencent.github.io/CodeAnalysis/media/Flow.png) - -### Experience - -[Experience Link](http://tca.tencent.com) - -### Getting Started - -- [How to get start](./quickStarted/intro.md) -- [How to deploy server and web](./quickStarted/deploySever.md#通过源代码) -- [How to deploy server and web with docker-compose](./quickStarted/deploySever.md#通过docker-compose) -- [How to use client](./quickStarted/deployClient.md) -- [Deploy Q&A](./quickStarted/FAQ.md) - -### Community - -- WeChat official account:腾讯云静态分析 -- QQ Group: 361791391 -- [Discussion](https://github.com/Tencent/CodeAnalysis/discussions) -- [Wiki](https://github.com/Tencent/CodeAnalysis/wiki) -- [White Paper](https://github.com/Tencent/CodeAnalysis/tree/main/腾讯云代码分析白皮书.pdf) - -### Changelogs - -- Check our [Changelog](https://github.com/Tencent/CodeAnalysis/tree/main/CHANGELOG.md) - -### Contributing - -- Check out [CONTRIBUTING](https://github.com/Tencent/CodeAnalysis/tree/main/CONTRIBUTING.md) to see how to develop with TCA. -- [Tencent WeOpen Star Project](https://github.com/weopenprojects/WeOpen-Star/issues/19#issue-1228583868)（From May 2022 to September 2022） -- [Tencent Open Source Incentive Program](https://opensource.tencent.com/contribution) encourages the participation and contribution of developers. We look forward to your active participation. - -### License - -TCA is [MIT licensed](https://github.com/Tencent/CodeAnalysis/tree/main/LICENSE) diff --git a/doc/en/quickStarted/references/install_mysql_on_centos.md b/doc/en/advanced/install_mysql_on_centos.md similarity index 100% rename from doc/en/quickStarted/references/install_mysql_on_centos.md rename to doc/en/advanced/install_mysql_on_centos.md diff --git a/doc/en/quickStarted/references/install_nginx_from_source.md b/doc/en/advanced/install_nginx_from_source.md similarity index 100% rename from doc/en/quickStarted/references/install_nginx_from_source.md rename to doc/en/advanced/install_nginx_from_source.md diff --git a/doc/en/quickStarted/references/install_python37_on_centos.md b/doc/en/advanced/install_python37_on_centos.md similarity index 100% rename from doc/en/quickStarted/references/install_python37_on_centos.md rename to doc/en/advanced/install_python37_on_centos.md diff --git a/doc/en/quickStarted/references/install_python37_on_ubuntu.md b/doc/en/advanced/install_python37_on_ubuntu.md similarity index 100% rename from doc/en/quickStarted/references/install_python37_on_ubuntu.md rename to doc/en/advanced/install_python37_on_ubuntu.md diff --git a/doc/en/quickStarted/references/install_redis_from_source.md b/doc/en/advanced/install_redis_from_source.md similarity index 100% rename from doc/en/quickStarted/references/install_redis_from_source.md rename to doc/en/advanced/install_redis_from_source.md diff --git a/doc/en/quickStarted/references/install_redis_on_centos.md b/doc/en/advanced/install_redis_on_centos.md similarity index 100% rename from doc/en/quickStarted/references/install_redis_on_centos.md rename to doc/en/advanced/install_redis_on_centos.md diff --git "a/doc/en/advanced/\351\233\206\346\210\220\344\273\243\347\240\201\345\210\206\346\236\220\345\267\245\345\205\267.md" "b/doc/en/advanced/\351\233\206\346\210\220\344\273\243\347\240\201\345\210\206\346\236\220\345\267\245\345\205\267.md" index ca4463fe8..5d4375463 100644 --- "a/doc/en/advanced/\351\233\206\346\210\220\344\273\243\347\240\201\345\210\206\346\236\220\345\267\245\345\205\267.md" +++ "b/doc/en/advanced/\351\233\206\346\210\220\344\273\243\347\240\201\345\210\206\346\236\220\345\267\245\345\205\267.md" @@ -1,4 +1,4 @@ -# 集成代码分析工具 +# 在TCA源码中集成代码分析工具 ## 初识TCA任务执行机制 diff --git a/doc/en/community/changelog.md b/doc/en/community/changelog.md index e3fd99512..c26a00bdf 100644 --- a/doc/en/community/changelog.md +++ b/doc/en/community/changelog.md @@ -1,61 +1,154 @@ # 更新日志 +## V1.4.1 (2022-7-28) +### Features +- 【服务端】统一部署脚本，封装local、docker、docker-compose部署方式启动server&web&client +- 【服务端】支持源码安装Redis与Nginx +- 【服务端】macOS启动docker desktop +- 【服务端】完善github action脚本 +- 【工具】更新工具列表 -## V1.2.0 (2022-4-27) +### Docs +- 上传新版本白皮书 +- 调整快速入门指引文档 + + + +## V1.4.0 (2022-7-18) +### Features +- 【客户端】jenkins插件增加分析方案模版ID和分析方案名称参数 +- 【服务端】增加扫描方案模板API +- 【服务器】优化文件服务器鉴权交互 +- 【客户端】QuickScan支持指定分析方案模板进行扫描；支持从环境变量读取文件服务器url和token +- 【Web端】升级moment依赖 +### Docs +- 更新插件使用说明书和启动参数说明 + + + +## V1.3.3 (2022-6-29) +### Features +- 【服务端】支持团队、项目组禁用，支持代码库、分支项目删除 +- 【服务端】扫描方案支持分支过滤 +- 【Web端】支持禁用团队、项目，代码库登记支持ssh_url +- 【Web端】支持分支过滤配置，修复代码统计文件选中效果，支持工具、依赖凭证移除 +- 【工具】增加tca_ql工具 +- 【客户端】节点模式不再由客户端加载编译工具的环境变量，避免覆盖机器原有环境变量 +- 【客户端】QuickScan模式，异常时输出task.log方便排查问题 +- 【客户端】.code.yml支持.yaml后缀 +### Bugfixes +- 【客户端】tool_scheme和ini配置共用时，可能出现工具重复，需要对工具库去重后再拉取 +### Docs +- 更新TCA Action相关文档 +- 更新Jenkins插件文档；增加环境依赖说明 +- 更新自定义工具文档，使用工具依赖 +- 更新CLS readme + + + +## V1.3.2 (2022-6-16) +### Features +- 【客户端】QuickScan根据语言执行不同的任务 +### Docs +- docker-compose部署文档中数据库注意事项 + + + +## V1.3.1 (2022-6-14) +### Features +- 【客户端】新增merge quest分支增量扫描 +- 【客户端】新增Quickscan模式 +- 【客户端】localscan支持工具并发 +- 【工具】新增二进制文件依赖分析工具 +- 【服务端】server调整服务监控探测脚本：celery状态判断 +- 【服务端】增加子任务接口，完善部署脚本 +- 【服务端】更新CLS版本v20220613.1 +- 【服务端】基于 CentOS7.9.2009（已测）的运行环境一键安装脚本，并已安装及配置命令 gunicorn 和 celery +- 【Web端】调整OAuth显示 + + + +## V1.3.0 (2022-6-7) +### Features +- 【工具】新增独立工具Loong +- 【工具】新增Java、JS基础安全规则包 +- 【工具】增加Go和Python技术安全规则包 +- 【服务端】新增oauth授权及工具依赖管理 +- 【服务端】docker-compose部署支持挂载本地日志目录 +- 【客户端】支持工具依赖管理 +- 【Web端】支持工具依赖管理设置和Git OAuth设置 +- 【Web端】团队列表支持滚动加载 +### Bugfixes +- 【服务端】补充scmproxy缺失依赖 +- 【服务端】修复issue入库忽略处理操作 + +### Docs +- 更新工具目录readme +- 更新client README.md + + + +## V1.2.1 (2022-5-24) ### Features +- 【工具】新增Collie/Compass（测试版）工具 +- 【工具】添加tscancode系列工具 +- 【工具】工具区分编译型和非编译型 +- 【客户端】更新cmdscm二进制文件，调整获取ssh端口号方式 +- 【客户端】增加腾讯工蜂作为工具拉取源，支持选用 +- 【服务端】调整工程配置和文档，支持https克隆 +- 【Web端】前端页面优化 + +### Docs +- 添加集成工具说明文档 +- readme增加微信公众号和腾讯开源摘星计划的说明及链接 +- 修改帮助文档的脚本名称；修改工蜂镜像仓库链接位置 +- 调整自定义规则文档 +- 调整doc，优化部署、使用文档 + + +## V1.2.0 (2022-4-27) +### Features - 【Web端】增加工具管理 - 【工具】增加logback检查的安全规则 - 【服务端】增加TCA server&web 一键部署脚本 - 【服务端】删除main部分异步任务；调整server nginx启动位置 - 【服务端】增加server健康监测 - ### Docs - - 完善部署和Q&A文档 - 上传工具列表 -## V1.1.3 (2022-4-18) +## V1.1.3 (2022-4-18) ### Features - - 【工具】上传开源合规检查规则 - 【工具】新增PHP安全相关规则 - 【服务端】上线license鉴权 - 【客户端】支持对工具license校验 - ### Docs - - 更新文档内的工具默认路径 - 增加任务分布式执行能力操作文档 - 增加PR操作流程 -## V1.1.2 (2022-4-2) +## V1.1.2 (2022-4-2) ### Features - -- 【服务端】优化部署构建脚本 - +- 【服务端】优化部署构建脚本 ### Docs - -- 简化前端部署脚本&文档 +- 简化前端部署脚本&文档 - 优化指引文档 -## V1.1.1 (2022-3-31) +## V1.1.1 (2022-3-31) ### Features - - 【工具】增加0daychecker工具 - 【工具】增加Log4j、LogBack漏洞检查规则包 ### Docs - - 完善部署文档说明，推荐使用Docker-Compose 2.3.3版本 ## V1.1.0 (2022-3-29) - ### Features - - 【客户端】client支持arm64架构执行环境 - 【客户端】client新增分布式节点模式 - 【客户端】修改参数isTotal(是否开启全量扫描)判断方式及参数startCommand（启动客户端命令）拼接方式 @@ -65,21 +158,17 @@ - 【Web端】web模块部署脚本问题修复及优化 - 【Web端】增加管理后台、增加在线分析 - 【Web端】调整前端部署脚本，支持传递nginx配置地址、前端资源部署地址 - ### Bugfixes - - Jenkins插件命令拼装逻辑修正 - ### Docs - - 调整pypi下载失败提示 - 调整前端部署文档及脚本 - 更新License -## V1.0.1 (2022-03-01) -### Features +## V1.0.1 (2022-03-01) +### Features - feat: 【服务端】调整代码库登记ssh url链接格式适配 - feat: 【工具】上线支持PHP安全工具-Rips - feat: 【工具】调整androidlint部分规则描述 @@ -90,17 +179,16 @@ - feat: 【客户端】增加在docker中快速使用client的方式 ### Bugfixes - - fix: 【服务端】补充缺失的依赖 - fix: 【Web端】修复下载codedog.ini失败提示 - + ### Docs - - doc: 上线部署文档Q&A - doc: 优化部署文档、帮助文档说明 - doc: 增加产品白皮书 - doc: 补充redis和nginx源码安装参考文档 -## V1.0.0 -初始发布 + +## V1.0.0 +初始发布 \ No newline at end of file diff --git a/doc/en/guide/README.md b/doc/en/guide/README.md index 7c9c9ea9e..da9dfcdd6 100644 --- a/doc/en/guide/README.md +++ b/doc/en/guide/README.md @@ -1,12 +1,11 @@ # 腾讯云代码分析 -**腾讯云代码分析**（**Code Analysis, TCA**）起步于 2012 年（内部代号CodeDog），是集众多代码分析工具的云原生、分布式、高性能的代码综合分析跟踪管理平台，其主要功能是持续跟踪分析代码，观测项目代码质量，支撑团队传承代码文化。 +**腾讯云代码分析**（**Tencent Cloud Code Analysis, TCA**）起步于 2012 年（内部代号CodeDog），是集众多代码分析工具的云原生、分布式、高性能的代码综合分析跟踪管理平台，其主要功能是精准跟踪管理代码分析发现的代码质量缺陷、代码规范、代码安全漏洞、无效代码，以及度量代码复杂度、重复代码、代码统计。持续跟踪分析代码，观测项目代码质量，支撑团队传承代码文化。 -用心关注每行代码迭代、助力传承卓越代码文化！ +用心关注每行代码迭代，助力传承卓越代码文化！ -精准跟踪管理代码分析发现的代码质量缺陷、代码规范、代码安全漏洞、无效代码，以及度量代码复杂度、重复代码、代码统计。 -代码分析是通过词法分析、语法分析、控制流、数据流分析等技术对程序代码进行分析，验证代码是否满足**规范性**、**安全性**、**可靠性**、**可维护性**、**部分性能**等，对代码进行综合分析和度量等指标的一种代码分析技术。 +**代码分析**是通过词法分析、语法分析、控制流、数据流分析等技术对程序代码进行扫描，对代码进行综合分析，验证代码是否满足规范性、安全性、可靠性、可维护性等指标的一种代码分析技术。 ## 主要功能 @@ -20,16 +19,16 @@ 包含代码圈复杂度、代码重复率和代码统计等度量信息。 -#### 代码圈复杂度 +### 代码圈复杂度 圈复杂度也称为条件复杂度或循环复杂度，它可以用来衡量一个模块判定结构的复杂程度。圈复杂度大说明程序代码的判断逻辑复杂，可能造成代码质量低下且难于测试和维护。 定期分析工程项目中代码的圈复杂度，可以有效地帮助开发与测试逐步优化代码质量。 -#### 代码重复率 +### 代码重复率 定期分析工程项目中的重复代码，可以有效地帮助开发发现冗余代码，进行代码抽象和重构，降低代码风险，以便于更好的管理和维护代码。 -#### 代码统计 +### 代码统计 支持全量增量展示代码行数统计，包含代码行、注释行和空白行，可以有效地跟踪了解工程项目中代码量持续变化，并可以查看各个语言的占比情况。 diff --git "a/doc/en/guide/\345\210\206\346\236\220\346\226\271\346\241\210/\345\237\272\347\241\200\345\261\236\346\200\247\351\205\215\347\275\256.md" "b/doc/en/guide/\345\210\206\346\236\220\346\226\271\346\241\210/\345\237\272\347\241\200\345\261\236\346\200\247\351\205\215\347\275\256.md" index 3c28a4c40..b0edbc3a0 100644 --- "a/doc/en/guide/\345\210\206\346\236\220\346\226\271\346\241\210/\345\237\272\347\241\200\345\261\236\346\200\247\351\205\215\347\275\256.md" +++ "b/doc/en/guide/\345\210\206\346\236\220\346\226\271\346\241\210/\345\237\272\347\241\200\345\261\236\346\200\247\351\205\215\347\275\256.md" @@ -10,15 +10,7 @@ - **运行环境** - - 对于客户端分析，根据客户端所在本地执行机器选择对应运行环境即可。 - - - 对于在线分析，根据项目实际情况，选取对应运行环境即可。 - - ::: tip - 在线分析时，会根据方案的运行环境，将任务分配到对应环境的节点机器上执行代码分析。 - - 需考虑项目在对应环境的节点机器上能否正常执行 - ::: + 用于将任务分配到指定的环境节点机器上执行代码分析，需考虑项目在对应环境的节点机器上能否正常执行。 - **环境变量** diff --git "a/doc/en/guide/\345\233\242\351\230\237\347\256\241\347\220\206/\350\212\202\347\202\271\347\256\241\347\220\206.md" "b/doc/en/guide/\345\233\242\351\230\237\347\256\241\347\220\206/\350\212\202\347\202\271\347\256\241\347\220\206.md" index e9684cd13..a035fc97f 100644 --- "a/doc/en/guide/\345\233\242\351\230\237\347\256\241\347\220\206/\350\212\202\347\202\271\347\256\241\347\220\206.md" +++ "b/doc/en/guide/\345\233\242\351\230\237\347\256\241\347\220\206/\350\212\202\347\202\271\347\256\241\347\220\206.md" @@ -1,68 +1,44 @@ -# 节点与标签 +# 团队节点与标签 -除了使用**公共节点**执行代码分析外，团队还可以利用**团队标签**注册并使用**团队节点**。 - -## 名词释义与特点 +::: warning +**团队节点及标签说明** -- 团队节点是**团队注册并管理**的**私有**节点。 +- **团队节点**是团队注册并管理的私有节点。 -- 团队节点**仅会运行**当前团队所属的分析任务。 +- **团队标签**用于关联团队内的节点机器与分析项目。 -- 团队标签是用于关联节点机器与分析项目。 - ::: tip - 当一个分析项目在方案中配置运行环境为团队标签后，该项目创建的任务就会下发到团队标签关联的节点机器上运行 - ::: +- 团队可以利用**团队标签**注册并使用**团队节点**。 -## 适用场景 +- 在项目的分析方案中配置运行环境为团队标签后，才可将该项目的分析任务下发到对应的团队节点。 -1. 业务项目**不想**在公共机器上**排队**等待 +- 团队节点**仅支持运行**当前团队中的分析任务，节点可执行的任务范围取决于该节点的负责人权限： + - 如果节点负责人为团队管理员，该节点可以执行当前团队所有项目的分析任务 + - 如果节点负责人为项目管理员，该节点只能运行指定项目下的分析任务 + - 如果节点负责人为部分代码库的管理员，该节点只能运行对应代码库的分析任务 +::: -2. 业务项目**代码比较敏感**，不能在公共机器上运行 +## 适用场景 -3. 业务项目需要**依赖特定**的**机器环境**（比如CPU架构、操作系统等） +1. 团队因资源可靠性或项目敏感性，需使用私有机器资源 -4. ... +2. 团队项目分析依赖**特定机器环境**（比如CPU架构、操作系统等） -以上场景，均可考虑使用团队节点，业务团队提供机器资源接入作为团队节点，仅分析自己业务的代码库，**保证执行效率**，**保护源码不泄漏**，**支持项目特殊依赖**等 +以上场景，团队可接入专机资源作为团队节点，仅分析自己业务的代码库，以**保证执行效率**，**保护源码安全**，**支持项目环境依赖**等。 ## 团队节点注册 -- 根据环境下载客户端二进制文件或拉取源码，参考[客户端](../客户端/配置说明.md)。 - -- 通过终端启动客户端： - - - 客户端二进制启动 - - ```bash - ./codepuppy start -t TOKEN --org-sid ORG_SID - ``` - - - 客户端源码启动 - - ```bash - python3 codepuppy.py start -t TOKEN --org-sid ORG_SID - ``` - - ::: tip - 1. TOKEN 可以从平台**个人中心-个人令牌**页面获取 - 2. ORG_SID 可以从**页面链接**中获取 - ::: +参考[客户端常驻节点分析](../客户端/常驻节点分析.md)进行环境配置和启动节点。 ## 团队节点管理 -完成团队节点注册后，可以在当前团队下看到对应的节点信息，同时**需要进行配置** +完成团队节点注册后，可以在当前团队`节点管理`下看到对应的节点信息，同时**需要进行节点配置** ::: warning - 团队节点**首次注册**时，需要手动在平台上配置**所属标签**、**节点可用性**、**工具进程**等。 -- 将节点的**节点可用性**调整为**活跃**后，运行客户端节点的终端会输出**心跳上报成功**的日志 +- 将节点的**节点可用性**调整为**活跃**后，节点终端客户端运行日志会输出**心跳上报成功**的日志 ::: -- 首次注册团队节点，节点状态为不可用 - - ![注册团队节点](../../../images/org_node_manager_1.png) - -- 调整后的节点 - +- 首次注册团队节点，节点状态默认为不可用，需调整节点状态为“活跃”： ![注册团队节点](../../../images/org_node_manager_2.png) - 配置节点关联的工具进程： @@ -74,20 +50,8 @@ 2. 团队标签可以参考`CodeDog`标签为不同的系统类型（Linux、MacOS、Windows）建立标签，比如`专属标签-Linux`、`专属标签-Mac`等 ::: -### 团队节点执行任务范围 - -::: warning 使用团队节点运行分析任务的前提 -对应分析项目使用的分析方案中，需要配置分析方案中的**运行环境**为该团队节点配置的所属标签。 -::: - -::: warning 团队节点执行的任务范围取决于该节点的负责人 -- 如果节点负责人为团队管理员，该节点可以执行当前团队所有项目的分析任务 -- 如果节点负责人为项目管理员，该节点只能运行指定项目下的分析任务 -- 如果节点负责人为部分代码库的管理员，该节点只能运行对应代码库的分析任务 -::: - -## 团队标签管理 +## 使用团队标签 您可以创建一个团队标签，并配置到您的团队节点和您的分析方案中 diff --git "a/doc/en/guide/\345\256\242\346\210\267\347\253\257/\345\205\266\344\273\226\351\205\215\347\275\256.md" "b/doc/en/guide/\345\256\242\346\210\267\347\253\257/\345\205\266\344\273\226\351\205\215\347\275\256.md" new file mode 100644 index 000000000..8863a5086 --- /dev/null +++ "b/doc/en/guide/\345\256\242\346\210\267\347\253\257/\345\205\266\344\273\226\351\205\215\347\275\256.md" @@ -0,0 +1,28 @@ + +# 其他配置与用法 + +### 1. 配置使用本地工具 + +:::warning +如果由于网络原因，执行时无法从github自动拉取工具，或拉取比较慢，可以参考基础配置腾讯工蜂工具地址，或使用以下方式预先下载好工具，配置使用本地工具目录。 +::: + +- （1）下载工具配置库 `https://github.com/TCATools/puppy-tools-config.git` ，存放到 `client/data/tools`目录下（如果未生成，可先创建该目录）。 +- （2）根据当前机器操作系统，查看`puppy-tools-config`目录下的`linux_tools.ini`或`mac_tools.ini`或`windows_tools.ini`文件，将`[tool_url]`中声明的所有工具下载到 `client/data/tools`目录下。 +- （3）填写`client/config.ini`中的配置：`USE_LOCAL_TOOL`=`True`，即可使用下载好的本地工具，不自动拉取和更新工具。 + +### 2. 使用自建git server存放工具 + +:::warning +如果自己搭建了一套git server，可以将工具配置库 `https://github.com/TCATools/puppy-tools-config.git` 以及里面声明的工具仓库，存放到自建git serevr上。 +::: + +- （1）将工具配置库 `https://github.com/TCATools/puppy-tools-config.git` 上传到自建git仓库。 +- （2）按所需的操作系统，将`puppy-tools-config`仓库下的`linux_tools.ini`或`mac_tools.ini`或`windows_tools.ini`文件中`[tool_url]`声明的所有工具库，上传到自建git仓库。 +- （3）修改`linux_tools.ini`或`mac_tools.ini`或`windows_tools.ini`文件中`[base_value]`中的`git_url`为自建git server地址。 +- （4）修改`client/config.ini`中的`TOOL_CONFIG_URL`为自建git server的`puppy-tools-config`仓库地址。 +- （5）填写`client/config.ini`中的`[TOOL_LOAD_ACCOUNT]`配置，输入有拉取权限的用户名密码，即可使用自建git server拉取工具。 + +### 3. git lfs带宽和存储配额不够问题 + +- 如果git拉取工具时，出现git lfs拉取失败，可能是lfs带宽和存储配额不够，可以打开对应的工具github页面，通过`Download ZIP`的方式下载工具压缩包，再解压到`client/data/tools`目录下。 diff --git "a/doc/en/guide/\345\256\242\346\210\267\347\253\257/\345\270\270\351\251\273\350\212\202\347\202\271\345\210\206\346\236\220.md" "b/doc/en/guide/\345\256\242\346\210\267\347\253\257/\345\270\270\351\251\273\350\212\202\347\202\271\345\210\206\346\236\220.md" index eff0e9571..2b81c31c1 100644 --- "a/doc/en/guide/\345\256\242\346\210\267\347\253\257/\345\270\270\351\251\273\350\212\202\347\202\271\345\210\206\346\236\220.md" +++ "b/doc/en/guide/\345\256\242\346\210\267\347\253\257/\345\270\270\351\251\273\350\212\202\347\202\271\345\210\206\346\236\220.md" @@ -1,7 +1,7 @@ # 常驻节点分析 ::: tip -TCA客户端除了通过`localscan`命令启动单次的代码分析，也可以作为一个分布式分析节点启动，作为常驻进程，多个节点可以分布式并行执行服务端下发的任务，提高扫描效率。 +TCA 客户端除了通过`localscan`命令启动单次的代码分析，也可以作为一个分布式分析节点启动，作为常驻进程，多个节点可以分布式并行执行服务端下发的任务，提高扫描效率。 和本地分析一样，需要先安装环境和必要的工具，并配置好服务端地址。 ::: @@ -14,44 +14,69 @@ TCA客户端除了通过`localscan`命令启动单次的代码分析，也可以 ## 前置步骤 -公共/专有机器上具备客户端。 +节点机器上具备客户端及客户端相关依赖环境，可查阅[本地分析-前置步骤](本地分析.md#前置步骤)部分进行配置。 -如果是开源版客户端，需要配置相关环境和依赖，可查阅[开源版客户端使用说明](配置说明.md#开源版客户端使用说明)。 - -## 常驻节点配置 +## 节点配置 ### 配置 `config.ini` 文件 -- 将``替换成实际的serve ip（可包含端口号）。 +1. 将``替换成实际的 TCA 平台 IP（可包含端口号）。 + +2. 国内使用 github 拉取网络较慢，推荐使用腾讯工蜂拉取，需要修改以下配置： +- 修改 `TOOL_CONFIG_URL=https://git.code.tencent.com/TCA/tca-tools/puppy-tools-config.git` +- 将[腾讯工蜂](https://git.code.tencent.com)的账号密码填写到`TOOL_LOAD_ACCOUNT `中。（注：没有腾讯工蜂账号的需要注册；由于腾讯工蜂的开源仓库也要求使用账号才能拉取，所以此处必须填写账号密码） -### 启动代码分析常驻节点 +### 启动常驻节点 - 从TCA前端页面中获取 `token`，前往 **个人中心-个人令牌-复制Token** ::: tip - 作为公共节点：token需要具有超级管理员权限，如使用`CodeDog`账户的`token`。 - - 可以通过[用户管理页面](../后台管理/后台管理说明.md)查看到哪些用户是超级管理员。 - - 作为专机节点：该节点仅能分析该`token`具有权限的项目。 + 节点仅能分析该`token`具有权限的项目，因此如设置公共的分析节点，推荐使用超级管理员的token。 + + 可以通过[用户管理页面](../后台管理/用户管理.md)查看到哪些用户是超级管理员。 ::: -- 进入到`client`目录下，执行命令：`python3 codepuppy.py -l codepuppy.log start -t ` +- 如启动团队节点，还需获取团队编号：org_sid，获取方式： +从 TCA 平台项目概览页面URL中获取，项目概览URL格式：`http://{域名}/t/{org_sid}/p/{team_name}/profile` -- 启动后，可以在命令行输出或`codepuppy.log`中查看运行日志，如果未报异常，且输出`task loop is started.`，表示节点已经正常启动。 -### 配置节点 +**两种方式可选启动客户端：** +#### 使用客户端源码启动常驻节点 -常驻节点首次启动后，需要到节点管理页面设置节点状态（默认为`不可用`），将其设置为**`活跃`**，用于接收和执行任务。 +- 如启动公共节点，需进入到源码的`client`目录下，执行命令： +```bash +python3 codepuppy.py -l codepuppy.log start -t +``` -- 进入TCA节点管理页面。`管理入口`-`节点管理` +- 如启动团队节点，需增加参数 org_sid： +```bash +python3 codepuppy.py -l codepuppy.log start -t --org-sid +``` - 可以看到当前在线的节点，可以修改节点名称、标签、负责人等信息。 +启动后，可以在命令行输出或`codepuppy.log`中查看运行日志，如果未报异常，且输出`task loop is started.`，表示节点已经正常启动。 +#### 使用客户端二进制启动常驻节点 - ::: tip - 常驻节点首次启动后，需将节点状态从**不可用（失效）**状态切换到**活跃（在线）**状态 - ::: +- 如启动公共节点，需进入到源码的`client`目录下，执行命令： +```bash +./codepuppy -l codepuppy.log start -t +``` + +- 如启动团队节点，需增加参数 org_sid： +```bash +./codepuppy -l codepuppy.log start -t --org-sid +``` +启动后，可以在命令行输出或`codepuppy.log`中查看运行日志，如果未报异常，且输出`task loop is started.`，表示节点已经正常启动。 + +### 管理节点 + +常驻节点首次启动后，需要到节点管理页面管理节点状态： + +1. **设置节点状态：** + 进入 TCA 节点管理页面。`管理入口`-`节点管理`，可以看到当前在线的节点，节点状态默认为`不可用`，需将其设置为**`活跃`**才可用于接收和执行任务。 + 也可以按需修改节点名称、标签、负责人等信息。 -- 可以进入**工具进程配置**页面，对节点支持的工具进程进行管理（默认会全部勾选），未勾选的工具进程，将不会在该节点上执行。 +2. （按需可选）**配置节点工具进程：** + 进入**工具进程配置**页面，对节点支持的工具进程进行管理（默认会全部勾选），未勾选的工具进程，将不会在该节点上执行。 -- **节点所属标签**会与分析方案中的运行环境标签进行匹配，只有相同标签的任务才会下发到该机器节点上。 +3. （按需可选）**设置节点标签：** + 节点标签会与分析方案中的运行环境标签进行匹配，只有相同标签的任务才会下发到该机器节点上。 diff --git "a/doc/en/guide/\345\256\242\346\210\267\347\253\257/\346\234\254\345\234\260\345\210\206\346\236\220.md" "b/doc/en/guide/\345\256\242\346\210\267\347\253\257/\346\234\254\345\234\260\345\210\206\346\236\220.md" index 83e6e11a4..6fdbfaa04 100644 --- "a/doc/en/guide/\345\256\242\346\210\267\347\253\257/\346\234\254\345\234\260\345\210\206\346\236\220.md" +++ "b/doc/en/guide/\345\256\242\346\210\267\347\253\257/\346\234\254\345\234\260\345\210\206\346\236\220.md" @@ -1,58 +1,97 @@ -# 本地分析 +# 客户端本地分析 ## 使用场景 - 希望在本地随时分析。 -- 如果公共机器无法满足编译环境的情况，复用本地编译环境。 - -- 如果对代码安全有要求也推荐使用本地分析。 +- 接入持续集成系统实现自动化分析。 ## 前置步骤 +**1. 客户端运行环境机器配置推荐** + +| 操作系统 | 推荐配置 | +| --------: | :------------------------------------------- | +| Linux | 8核16G内存，硬盘空间256G（可用空间不低于100G） | +| Mac | 8核16G内存，硬盘空间256G（可用空间不低于100G） | +| Windows | 8核16G内存，硬盘空间256G（可用空间不低于100G） | + +以上为推荐配置，实际情况需要考虑扫描对象代码库的大小，按实际情况增加磁盘空间。 + +**2. 本地需具备客户端** + +下载[开源版源码](https://github.com/Tencent/CodeAnalysis)。 +或从[开源版release](https://github.com/Tencent/CodeAnalysis/releases)下载客户端以运行客户端二进制； + + +**3. 安装Python环境和第三方库（仅客户端源码启动分析需要）** +- 预装Python3.7、pip，支持 `python3` 和 `pip3` 命令 +- 安装依赖：`pip3 install -r CodeAnalysis/client/requirements/app_reqs.pip` -本地具备客户端。 +**4. 安装第三方工具（docker下启动分析可跳过）** +- 进入到`client/requirements`目录 +- 在命令行中执行安装脚本`install.sh`(linux/mac环境)或`install.bat`(windows环境) -如果是开源版客户端，需要配置相关环境和依赖，可查阅[开源版客户端使用说明](配置说明.md#开源版客户端使用说明)。 ## 分析配置 ### 配置客户端 `config.ini` 文件 -将 `` 替换成实际的serve ip（可包含端口号） +1. 将 `` 替换成实际的TCA平台IP（可包含端口号） -### 配置客户端 `codedog.ini` 文件 +2. 国内使用github拉取网络较慢，推荐使用腾讯工蜂拉取，需要修改以下配置： +- 修改 `TOOL_CONFIG_URL=https://git.code.tencent.com/TCA/tca-tools/puppy-tools-config.git` +- 将[腾讯工蜂](https://git.code.tencent.com)的账号密码填写到`TOOL_LOAD_ACCOUNT `中。（注：没有腾讯工蜂账号的需要注册；由于腾讯工蜂的开源仓库也要求使用账号才能拉取，所以此处必须填写账号密码） -- `token`，必填项。从TCA前端页面中获取，前往 **个人中心-个人令牌-复制Token** +### 配置客户端 `codedog.ini` 文件 -- `org_sid`，团队编号，必填项。可以从TCA前端项目页面URL获取。 +`codedog.ini`获取方法： +- 方法一： 下载TCA源码或[开源版release](https://github.com/Tencent/CodeAnalysis/releases)的客户端包，在源码目录中复制`CodeAnalysis/client/codedog.ini`并按文件内配置说明进行修改。 +- 方法二： 在TCA平台平台上配置好对应信息后，下载配置文件到本地使用。 -- `team_name`，项目名称，必填项。可以从TCA前端项目页面URL获取。 + ![下载配置文件](../../../images/start_scan_03.png) - ```bash - # 如 - http://{域名}/t/{org_sid}/p/{team_name}/profile - ``` +`codedog.ini`中以下字段为必填项： -- `source_dir`，本地代码目录路径，必填项。绝对路径。 +| 字段名 | 填写说明 | +| :-------- | :------------------------------------------- | +|`token` | 从TCA平台页面获取，前往[个人中心]-[个人令牌]-复制Token | +|`org_sid`(团队编号) | 从TCA平台项目概览页面URL中获取，项目概览URL格式：`http://{域名}/t/{org_sid}/p/{team_name}/profile` | +|`team_name`(项目名称) | 同上 | +|`source_dir` | 本地代码目录路径 | -- 其他参数 - - 按需填写其他可选项，也可以不填，按默认配置执行 +其他字段按需填写。 ## 启动代码分析 -### 源码下启动分析 +启动客户端分析有三种方式可选：[客户端源码下启动分析](#客户端源码下启动分析)、[客户端二进制启动分析](#客户端二进制启动分析)、[docker下启动分析](#docker下启动分析) +### 客户端源码下启动分析 + +- 进入到客户端`client`目录下 -- 进入到`client`目录下 +- 执行命令： + 客户端源码：`python3 codepuppy.py localscan` -- 执行命令：`python3 codepuppy.py localscan` +### 客户端二进制启动分析 +- 进入到客户端`client`目录下 + +- 执行命令： + 客户端源码：`./codepuppy localscan` ### docker下启动分析 +#### 1. 构建docker镜像 +在client目录下，执行以下命令：`docker build -t tca-client .` +**(需已安装Docker)** + +#### 2. 执行Docker容器 +::: warning +注意：因为以下步骤会将代码目录挂载到容器中，需要先将codedog.ini里面的source_dir修改为/workspace/src，其他参数保持不变。 +::: + +执行Docker容器有以下两种方式： #### 直接使用docker运行 -- 在client目录下，执行以下命令： -- (注意：按照实际情况填写`SOURCE_DIR`环境变量值) + 在`client`目录下，执行以下命令：(注意：按照实际情况填写`SOURCE_DIR`环境变量值) ```bash export SOURCE_DIR=需要扫描的代码目录绝对路径 @@ -61,9 +100,8 @@ docker run -it --rm -v $PWD:/workspace/client -v $SOURCE_DIR:/workspace/src -- #### 使用docker内bash终端运行 -- 通过以下方式，进入容器内的bash终端后，通过命令行启动client代码： -- 在client目录下，执行以下命令： -- (注意：按照实际情况填写`SOURCE_DIR`环境变量值) + 通过以下方式，进入容器内的bash终端后，通过命令行启动client代码： + 在`client`目录下，执行以下命令：(注意：按照实际情况填写`SOURCE_DIR`环境变量值) ```bash export SOURCE_DIR=需要扫描的代码目录绝对路径 diff --git "a/doc/en/guide/\345\256\242\346\210\267\347\253\257/\351\205\215\347\275\256\350\257\246\346\203\205.md" "b/doc/en/guide/\345\256\242\346\210\267\347\253\257/\351\205\215\347\275\256\350\257\246\346\203\205.md" deleted file mode 100644 index 8cbe12b5a..000000000 --- "a/doc/en/guide/\345\256\242\346\210\267\347\253\257/\351\205\215\347\275\256\350\257\246\346\203\205.md" +++ /dev/null @@ -1,26 +0,0 @@ -## 在线分析 - -在线分析即是通过Server端将分析任务注册到执行队列中，并将任务分配到平台配置的常驻节点上，在常驻节点执行分析，分析完毕后将分析结果上报入库。 - -::: tip -平台需要存在常驻节点，请查阅 [常驻节点分析](./常驻节点分析.md) - -否则任务因没有机器而无法完成分配，超时后任务会注销。 -::: - -## 客户端分析 - -客户端分析即是本地分析，可直接配置本地的客户端配置文件，或在平台上配置好对应信息后，下载配置文件，替换客户端配置问题，并启动客户端分析。分析完毕后会将数据上报入库。 - -- 下载配置文件 - - ![下载配置文件](../../../images/start_scan_03.png) - -- 替换客户端配置文件，并启动客户端分析。 - -::: tip -本地需要下载客户端，请查阅 - -- [部署与配置客户端](../../quickStarted/deployClient.md) -- [客户端使用说明文档](./本地分析.md) -::: \ No newline at end of file diff --git "a/doc/en/guide/\345\277\253\351\200\237\345\205\245\351\227\250/\345\277\253\351\200\237\345\220\257\345\212\250\344\270\200\346\254\241\344\273\243\347\240\201\345\210\206\346\236\220.md" "b/doc/en/guide/\345\277\253\351\200\237\345\205\245\351\227\250/\345\277\253\351\200\237\345\220\257\345\212\250\344\270\200\346\254\241\344\273\243\347\240\201\345\210\206\346\236\220.md" index 70bdc82cd..7af389ee8 100644 --- "a/doc/en/guide/\345\277\253\351\200\237\345\205\245\351\227\250/\345\277\253\351\200\237\345\220\257\345\212\250\344\270\200\346\254\241\344\273\243\347\240\201\345\210\206\346\236\220.md" +++ "b/doc/en/guide/\345\277\253\351\200\237\345\205\245\351\227\250/\345\277\253\351\200\237\345\220\257\345\212\250\344\270\200\346\254\241\344\273\243\347\240\201\345\210\206\346\236\220.md" @@ -1,20 +1,17 @@ # 快速启动一次代码分析 -## 创建项目 +## 创建团队及项目 -- **创建团队并进入** +- **创建团队** + 点击了解[团队管理](../团队管理/团队管理.md) ![创建团队](../../../images/create_team.png) - :::tip - 还没有团队？点击了解[团队管理](../团队管理/团队管理.md) - ::: - - **为团队创建一个项目，或选择一个已有项目，并进入项目内** ![创建项目](../../../images/create_team_group.png) -## 完成代码库登记 +## 登记代码库 - **完成代码库登记，并点击进入代码分析** @@ -22,7 +19,7 @@ ![进入代码分析](../../../images/start_scan_01.png) -## 开启第一次代码分析 +## 启动代码分析 ### 执行初始化创建 @@ -30,8 +27,8 @@ ::: tip - 1. 用户可选择使用分析方案模板，或创建分析方案的方式，利用方案的分析配置进行代码分析。 - 2. 点击确认时，平台会首先创建该代码库的分析方案，然后根据代码库分支、当前分析方案创建分支项目，最终下载客户端分析配置文件，客户端执行代码分析。 + 1. 首次开启代码分析，用户可选择使用已有的分析方案模板，或创建分析方案的。 + 2. 点击确认时，平台会首先创建该代码库的分析方案，然后根据代码库分支、当前分析方案创建分支项目，供用户启动代码分析。 ::: ### 执行代码分析 @@ -42,27 +39,20 @@ #### 在线分析 -在线分析即是通过Server端将分析任务注册到执行队列中，并将任务分配到平台配置的常驻节点上，在常驻节点执行分析，分析完毕后将分析结果上报入库。 +在线分析即是通过Server端将分析任务注册到执行队列中，并将任务分配到平台配置的常驻分析节点上进行，分析完毕后将分析结果上报入库。 ::: tip -平台需要存在常驻节点，请查阅 [常驻节点分析](../客户端/常驻节点分析.md) +使用在线分析要求平台具有常驻分析节点： +- 如您的TCA平台是使用官方一键部署脚本完成的环境部署（Docker部署、Docker-Compose部署、源码部署三种），默认已启动一个分析节点（即客户端），可直接用于在线分析。可查看[管理入口-节点管理](../后台管理/节点管理.md)确认该节点状态。 + +- 您也可自行接入更多分析节点实现并行执行代码分析，接入节点操作请查阅[常驻节点分析](../客户端/常驻节点分析.md) -否则任务因没有机器而无法完成分配，超时后任务会注销。 +**如无分析节点，在线分析任务将无法完成分配，未分配任务将于超时后自动注销**。 ::: #### 客户端分析 -客户端分析即是本地分析，可直接配置本地的客户端配置文件，或在平台上配置好对应信息后，下载配置文件，替换客户端配置问题，并启动客户端分析。分析完毕后会将数据上报入库。 - -- 下载配置文件 - - ![下载配置文件](../../../images/start_scan_03.png) - -- 替换客户端配置文件，并启动客户端分析。 - -::: tip -本地需要下载客户端，请查阅 [客户端使用说明文档](../客户端/本地分析.md) -::: +客户端分析即是本地分析，需要在本地有客户端，并配置好客户端配置文件 `codedog.ini`，详细操作参考：[启动客户端分析](../客户端/本地分析.md)。分析完毕后会将数据上报入库。 ## 查看分析历史 diff --git a/doc/en/quickStarted/FAQ.md b/doc/en/quickStarted/FAQ.md index 481d771b8..ed4d5b7d4 100644 --- a/doc/en/quickStarted/FAQ.md +++ b/doc/en/quickStarted/FAQ.md @@ -1,4 +1,4 @@ -# 常见问题 +# FAQ :::tip 该Q&A文档会持续更新，非常欢迎您的建议与共建！ @@ -195,19 +195,7 @@ ln -s /usr/local/python3/bin/celery /usr/local/bin/celery ### 2. 服务启动与初始化 -#### 2.1 ``compose_init.sh``脚本需要填写的密码是什么？ - -执行``compose_init.sh``提示需要输入的密码是数据库的初始化密码，默认为``TCA!@#2021`` - -```bash -$ ./compose_init.sh -Recreating tca_open_source_mysql_1 ... done -Recreating tca_open_source_redis_1 ... done -wait db [DB default password: TCA!@#2021] -Enter password: <此处输入'TCA!@#2021'> -``` - -#### 2.2 服务占用端口异常 +#### 2.1 服务占用端口异常 TCA 本地部署启动后，会监听多个端口： @@ -227,7 +215,7 @@ TCA 本地部署启动后，会监听多个端口： 不推荐调整TCA指定服务的端口号，需要调整多处配置，以及可能会影响到后续服务的升级 -#### 2.3 服务输出日志找不到 +#### 2.2 服务输出日志找不到 本地部署输出的日志位置： diff --git a/doc/en/quickStarted/README.md b/doc/en/quickStarted/README.md new file mode 100644 index 000000000..eb9c19ef2 --- /dev/null +++ b/doc/en/quickStarted/README.md @@ -0,0 +1,22 @@ +# Tencent Cloud Code Analysis + + +**Tencent Cloud Code Analysis** (TCA for short, code-named CodeDog inside the company early) is a comprehensive platform for code analysis and issue tracking. TCA consist of three components, **server, web and client**. It integrates of a number of self-developed tools, and also supports dynamic integration of code analysis tools in various programming languages. + +**Code analysis** is a technology, using lexical analysis, syntax analysis, control-flow analysis, data-flow analysis to make a comprehensive analysis of the code, so as to verify whether the code meets the requirements of normative, security, reliability, maintainability and other indicators. + +Using TCA can help team find normative, structural, security vulnerabilities and other issues in the code, continuously monitor the quality of the project code and issue alerts. At the same time, TCA opens up APIs to support connection with upstream and downstream systems, so as to integrate code analysis capabilities, ensure code quality, and be more conducive to inheriting an excellent team code culture. + +![组件图](https://tencent.github.io/CodeAnalysis/media/Components.png) + +![流程图](https://tencent.github.io/CodeAnalysis/media/Flow.png) + +--- + +For the first experience, it is recommended that you use the [Docker deployment](./dockerDeploy.md) to quickly build and experience the Tencent Cloud code analysis platform for the first experience. + +If you have more environmental requirements, you can also deploy Tencent Cloud Code Analysis Platform in the following two ways: + +- Deploy through [Docker-Compose](./dockercomposeDeploy.md) + +- Deploy through [source code](./codeDeploy.md) diff --git a/doc/en/quickStarted/codeDeploy.md b/doc/en/quickStarted/codeDeploy.md index 95cd0ae1c..f5c205be4 100644 --- a/doc/en/quickStarted/codeDeploy.md +++ b/doc/en/quickStarted/codeDeploy.md @@ -1,5 +1,8 @@ -# 源码部署 -兼容旧版的部署方式 +# 源代码快速部署 +TCA提供部署脚本，支持一键式快速部署Server、Web、Client。 +脚本共提供三种部署方式：[Docker部署(平台体验首推)](./dockerDeploy.md)、[Docker-Compose部署](./dockercomposeDeploy.md)、源码部署， +可根据您的具体使用场景任意选择其一进行部署。 + #### 依赖环境 - 系统环境 @@ -7,24 +10,24 @@ - 最低配置：2核4G内存、100G硬盘存储空间 - 环境准备 -> 目前TCA脚本已封装好Python、Mariadb、Redis与Nginx安装步骤，可以按“操作说明”内容进行操作 - - **Python 3.7**，[安装指引](./references/install_python37_on_centos.md) + :::tip + TCA 一键部署脚本已封装好 Python、Mariadb、Redis 与 Nginx 安装步骤，**无需自行安装**，**本地部署体验**可按 [操作说明](#操作说明) 内容直接进行部署操作。 - - **MySQL服务（MySQL5.7.8以上版本或Mariadb 10.5以上版本）**，[安装指引](./references/install_mysql_on_centos.md) + **注意：生产环境建议使用专业的 MySQL、Redis 等服务** + ::: + - Python 3.7 - - **Redis服务（4.0版本以上）**，[安装指引](./references/install_redis_on_centos.md) + - MySQL 服务（MySQL5.7.8 以上版本或 Mariadb 10.5 以上版本） - - **Nginx服务** + - Redis 服务（4.0版本以上） - :::warning - 仅适用于本地部署体验，生产环境建议使用专业的 MySQL、Redis 等服务 - ::: + - Nginx 服务 - 权限准备 - 环境权限：安装 Server 依赖软件（python、nginx、yum 等软件包）需要使用 ROOT 权限 - - 启动 Server服务时可以使用非 ROOT 用户运行 + - 启动 Server 服务时可以使用非 ROOT 用户运行 - 数据库权限：Server 服务执行数据库初始化需要依赖 ``CREATE、ALTER、INDEX、DELETE、LOCK TABLES、SELECT、INSERT、REFERENCES、UPDATE`` 权限 - 端口使用：需要开放80端口的访问权限(80为TCA平台默认访问端口)，或调整 Web 服务默认的访问端口地址 @@ -32,59 +35,78 @@ ##### 首次启动操作 -1. 进入CodeAnalysis工作目录（例如``~/CodeAnalysis``)，以下路径均为目录内的相对路径 -2. 安装基础软件与部署TCA（可根据脚本选项确定是否要安装相关基础软件），执行 +1. 进入 CodeAnalysis 工作目录（例如``~/CodeAnalysis``)，以下路径均为目录内的相对路径 + +2. 安装基础软件与部署 TCA（可根据脚本选项确定是否要安装 Python、MySQL、Redis、Nginx 相关基础软件），执行 ```bash $ bash ./quick_install.sh local deploy ``` - 执行该命令会做以下事情： - - 检测本地Python3.7、Mariadb/MySQL、Redis与Nginx，如果不存在会提示安装（install） - - 部署TCA Server、Web与Client，并进行初始化（install） - - 启动TCA Server、Web与Client（start） - - 检测TCA的运行状态（check） + + 执行该命令会做以下四个步骤： + - `Install`：检测本地 Python3.7、Mariadb/MySQL、Redis 与 Nginx，如果不存在会提示安装 + - `Init`：部署 TCA Server、Web与Client，并进行初始化 + - `Start`：启动 TCA Server、Web与Client + - `Check`：检测 TCA 的运行状态 - >注：在运行过程中，脚本会检测本地是否安装了相关基础软件（Python3.7、MySQL/Mariadb、Redis、Nignx），如果未安装会输出以下类似提示语： - >``` - >Do you want to install [Redis] by this script? - >Please enter:[Y/N] - >``` - >如果确定通过脚本安装可以输入`Y`。 + **注意**：在运行过程中，脚本会检测本地是否安装了相关基础软件（Python3.7、MySQL/Mariadb、Redis、Nignx），如果未安装会输出以下类似提示语： + ```bash + Do you want to install [Redis] by this script? + Please enter:[Y/N] + ``` + 如果确定通过脚本安装可以输入`Y`。 + + 3. 执行完成，无其他报错，即可登录： - - TCA 平台初始登录账号是``CodeDog``，密码是``admin``， + +:::tip +至此，您已完成 TCA 平台部署，请在浏览器输入`http://部署机器IP/`，点击立即体验，完成登录后即可开启您的腾讯云代码分析。 +平台内操作指引请查看：[快速启动一次代码分析](../guide/快速入门/快速启动一次代码分析.md) + +默认平台登录账号/密码：CodeDog/admin + +如部署过程中，已调整默认账号密码，请按照调整后的账号密码进行登录 +::: + ##### 更新操作 -1. 更新代码 -2. 执行以下命令： - - `bash ./quick_install.sh local install tca`：更新相关配置 - - `bash ./quick_install.sh local start`：启动服务（会自动关闭之前的服务） - - `bash ./quick_install.sh local check`：检查服务是否启动失败 - -注： -1. `local install`命令行参数说明： - - `base`：安装Python、Mariadb/MySQL、Redis与Nginx - - `tca`：初始化或更新TCA Server、Web、Client相关配置和数据 - - `server`：初始化或更新TCA Server相关配置和数据 - - `web`：初始化或更新TCA Web相关配置和数据 - - `client`：初始化或更新TCA Client相关配置和数据 - - 不填参数，默认会执行`base`、`tca`相关操作 +**1. 更新代码** + +**2. 执行以下命令** +```bash +bash ./quick_install.sh local install tca #更新相关配置 +bash ./quick_install.sh local start #启动服务（会自动关闭之前的服务） +bash ./quick_install.sh local check #检查服务是否启动失败 +``` +**注意：** + `local install`命令行参数说明： + - `base`：安装 Python、Mariadb/MySQL、Redis 与 Nginx + - `tca`：初始化或更新 TCA Server、Web、Client 相关配置和数据 + - `server`：初始化或更新 TCA Server 相关配置和数据 + - `web`：初始化或更新 TCA Web 相关配置和数据 + - `client`：初始化或更新 TCA Client 相关配置和数据 + - 不填参数，默认会执行`base`、`tca`相关操作 ##### 启动和停止服务 - 启动所有服务：`bash ./quick_install.sh local start` + - 启动Main相关服务：`bash ./quick_install.sh local start main` - `local start`支持启动指定服务，如上述的启动Main服务，还支持`mysql/redis/analysis/file/login/scmproxy/nginx/client/all` -- 停止所有服务：`.bash /quick_install.sh local stop` + +- 停止所有服务：`bash /quick_install.sh local stop` + - 停止Main相关服务：`bash ./quick_install.sh local stop main` - `local stop`支持停止指定服务，如上述的停止Main服务，还支持`analysis/file/login/scmproxy/nginx/client/all` -注： +**注意：** 1. 启动时会自动关闭之前已经运行的服务 -2. `local start`支持启动指定服务，如上述的启动Main服务，还支持`mysql/redis/main/analysis/file/login/scmproxy/nginx/all` - - `mysql`和`redis`默认会使用`systemctl`进行启动，如果`systemctl`无法使用，则会直接使用`nohup`方式运行相关服务 + +2. `mysql`和`redis`默认会使用`systemctl`进行启动，如果`systemctl`无法使用，则会直接使用`nohup`方式运行相关服务 ##### 检查服务运行状态 检查服务运行状态：`bash ./quick_install.sh local check` - - 目前支持检查server与web，暂不支持client + - 目前支持检查 server 与 web，暂不支持 client ##### 获取服务输出日志 -打印TCA Server各个服务的日志路径： `bash ./quick_install.sh local log` \ No newline at end of file +打印 TCA Server 各个服务的日志路径： `bash ./quick_install.sh local log` + diff --git a/doc/en/quickStarted/dockerDeploy.md b/doc/en/quickStarted/dockerDeploy.md new file mode 100644 index 000000000..3c5fc8ae7 --- /dev/null +++ b/doc/en/quickStarted/dockerDeploy.md @@ -0,0 +1,70 @@ +# Docker快速部署（平台体验首推） + +:::warning +Docker部署会包含Mariadb和Redis，如果需要更大规模使用，可以调整配置文件使用运维规范的 MySQL/Mariadb 和 Redis。 + +::: + +#### 依赖环境 + +- 系统环境 + - Linux、macOS、Windows + - 最低配置：2核4G内存、100G硬盘存储空间 +- 环境准备 + - Docker +- 权限准备 + - 需要开放80、8000端口的访问权限(80为TCA平台访问端口，8000为TCA Server访问端口) + +#### 部署对象 +Server、Web 与 Client + +#### 操作说明 +##### 首次启动操作 + +1. 进入CodeAnalysis工作目录（例如``~/CodeAnalysis``)，以下路径均为目录内的相对路径 +2. 执行命令： + ```bash + bash ./quick_install.sh docker deploy + ``` +::: tip +1. 通过Docker部署默认会从DockerHub上拉取``tencenttca/tca:latest``镜像 +2. 通过Docker部署默认会在当前根目录下的挂载三个路径： + - `.docker_temp/logs`：容器内的`/var/log/tca/`，存放TCA平台的日输出文件； + - `.docker_temp/data`：容器内的`/var/opt/tca/`， 存放TCA平台的服务数据，主要是Mariadb、Redis； + - `.docker_temp/configs`：容器内的``/etc/tca``，存放TCA平台的配置文件，主要是`config.sh` +::: + +##### 更新操作 +1. 更新代码 +2. 执行以下命令： +```bash +TCA_IMAGE_BUILD=true ./quick_install.sh docker deploy #重新构建并启动tca容器 +``` +::: tip +`TCA_IMAGE_BUILD=true`表示从本地构建TCA镜像运行 +::: + + + +##### 运行容器 +如果已经在机器上执行过`docker deploy`，并保留容器数据的，可以执行以下命令启动容器，继续运行TCA + +```bash +bash ./quick_install.sh docker start +``` + +##### 停止容器 +如果容器正在运行，希望停止容器，可以运行 + +```bash +bash ./quick_install.sh docker stop +``` + +#### 使用TCA +至此，您已完成第一个TCA平台部署，请在浏览器输入`http://部署机器IP/`，点击立即体验，完成登录后即可开启您的腾讯云代码分析。 +平台内操作指引请查看：[快速启动一次代码分析](../guide/快速入门/快速启动一次代码分析.md) +:::tip +默认平台登录账号/密码：CodeDog/admin + +如部署过程中，已调整默认账号密码，请按照调整后的账号密码进行登录 +::: diff --git a/doc/en/quickStarted/dockercomposeDeploy.md b/doc/en/quickStarted/dockercomposeDeploy.md index e9062bb65..a19842f7e 100644 --- a/doc/en/quickStarted/dockercomposeDeploy.md +++ b/doc/en/quickStarted/dockercomposeDeploy.md @@ -1,34 +1,53 @@ # Docker-Compose快速部署 +TCA提供部署脚本，支持一键式快速部署 Server、Web、Client。 +脚本共提供三种部署方式：[Docker部署(平台体验首推)](./dockerDeploy.md)、Docker-Compose部署、[源码部署](./codeDeploy.md)， +可根据您的具体使用场景任意选择其一进行部署。 + #### 部署对象 Server、Web 与 Client :::warning -仅适用于Docker-Compose部署体验，生产环境建议使用专业的 MySQL、Redis 等服务 -兼容之前的部署方式 +仅适用于 Docker-Compose 部署体验，生产环境建议使用专业的 MySQL、Redis 等服务 ::: #### 操作说明 ##### 首次启动操作 -1. 进入CodeAnalysis工作目录（例如``~/CodeAnalysis``)，以下路径均为目录内的相对路径 +1. 进入 CodeAnalysis 工作目录（例如``~/CodeAnalysis``)，以下路径均为目录内的相对路径 + 2. 执行命令： - - `bash ./quick_install.sh docker-compose deploy`：启动tca_server容器 +``` bash +bash ./quick_install.sh docker-compose deploy #启动tca_server容器 +``` +注意：通过 Docker-Compose 部署默认会在当前根目录下的挂载三个路径： -注意：通过Docker-Compose部署默认会在当前根目录下的挂载三个路径： +- `.docker_data/logs`：存放 TCA 平台的各个服务日志输出目录； +- `.docker_data/mysql`：存放 TCA 平台的 MySQL 数据 +- `.docker_data/redis`：存放 TCA 平台的 Redis 数据 +- `.docker_data/filedata`：存放 TCA 平台文件服务器的文件 -- `.docker_data/logs`：存放TCA平台的各个服务日志输出目录； -- `.docker_data/mysql`：存放TCA平台的MySQL数据 -- `.docker_data/redis`：存放TCA平台的Redis数据 -- `.docker_data/filedata`：存放TCA平台文件服务器的文件 + +:::tip +完成 TCA 平台部署后，请在浏览器输入`http://部署机器IP/`，点击立即体验，完成登录后即可开启您的腾讯云代码分析。 +平台内操作指引请查看：[快速启动一次代码分析](../guide/快速入门/快速启动一次代码分析.md) + +默认平台登录账号/密码：CodeDog/admin + +如部署过程中，已调整默认账号密码，请按照调整后的账号密码进行登录 +::: ##### 更新操作 1. 更新代码 + 2. 执行以下命令： - - `bash ./quick_install.sh docker-compose build`：重新构建TCA相关镜像 - - `bash ./quick_install.sh docker-compose deploy`: 重新部署TCA相关容器与初始化（或刷新数据） +``` bash +bash ./quick_install.sh docker-compose build #重新构建TCA相关镜像 +bash ./quick_install.sh docker-compose stop #停止运行中的TCA容器 +bash ./quick_install.sh docker-compose deploy #重新部署TCA相关容器与初始化（或刷新数据） +``` ##### 运行操作 -如果已经在机器上执行过``docker-compose deploy``，并保留容器数据的，可以执行以下命令启动容器，继续运行TCA +如果已经在机器上执行过``docker-compose deploy``，并保留容器数据的，可以执行以下命令启动容器，继续运行 TCA ```bash bash ./quick_install.sh docker-compose start @@ -44,6 +63,6 @@ bash ./quick_install.sh docker-compose stop ##### 构建镜像操作 如果希望构建镜像，可以执行以下命令 -``` +```bash bash ./quick_install.sh docker-compose build ``` \ No newline at end of file diff --git a/doc/en/quickStarted/enhanceDeploy.md b/doc/en/quickStarted/enhanceDeploy.md index fa67f3c50..734db135c 100644 --- a/doc/en/quickStarted/enhanceDeploy.md +++ b/doc/en/quickStarted/enhanceDeploy.md @@ -3,7 +3,9 @@ TCA 除开集成业界知名的分析工具之外，也有自主研发的独立 TCA 增强分析模块，需要用户额外部署 License 鉴权微服务，并邮件申请 License 。 -**注意：License申请完全免费！** +::: tip +**注意：License申请完全免费！** +::: ## 概念 - 独立工具：TCA 自主研发的代码分析工具； @@ -16,13 +18,15 @@ TCA 增强分析模块，需要用户额外部署 License 鉴权微服务，并 - 支持Java/Kotlin API和函数调用链分析； - 支持代码安全、空指针检查、内存泄漏等规则。 +**持续更新中……** ## CLS部署 ### 准备 - 一台 CLS 微服务专属机器，CLS 微服务需要跟该机器绑定 ### 步骤 -1. 在 [CLS](https://github.com/Tencent/CodeAnalysis/tree/main/server/cls) 目录下执行以下命令，获取 Server ID 和 Client License +1. 在 TCA 源码中[`server/cls`](https://github.com/Tencent/CodeAnalysis/tree/main/server/cls) 目录下执行以下命令，获取 `Server ID` 和 `Client License` + ```shell $ ./cls server 2022-04-13 18:35:29.356510559 +0800 CST [INFO] Version: 20220328.1 @@ -30,22 +34,23 @@ $ ./cls server xxx 2022-04-13 18:35:29.454552966 +0800 CST [INFO] License Server ID: xxx ``` -- Server ID: 机器码，用于跟TCA团队申请License授权 -- Client License: 提供给TCA Client, 方便TCA Client进行工具鉴权（重要，建议备份留底） +- `Server ID`: 机器码，用于向 TCA 团队申请 License 授权 +- `Client License`: 提供给 TCA Client，方便 TCA Client 进行工具鉴权（重要，建议备份留底） + +2. 在 TCA Client目录的 [`config.ini`](https://github.com/Tencent/CodeAnalysis/blob/main/client/config.ini) 中配置 CLS 微服务信息，比如 -2. 在 TCA Client 的 [config.ini](https://github.com/Tencent/CodeAnalysis/blob/main/client/config.ini) 中配置 CLS 微服务，比如 ```ini [LICENSE_CONFIG] ; [可选]使用独立工具时，需要填写，默认不需要 -; License服务器url, base_path, license URL=http://: +;License服务的域名和端口 BASE_PATH= -LICENSE= +LICENSE= ``` -3. 跟 TCA 团队邮件申请 License +3. 向 TCA 团队邮件申请 License -- 发送邮箱： +- 收件邮箱： ``` v_cocohwang@tencent.com anjingliu@tencent.com @@ -53,11 +58,12 @@ yalechen@tencent.com tommyzhang@tencent.com ``` -- 格式如下： +- 申请邮件格式如下： -TCA独立工具License申请邮件 +主题：**TCA 独立工具 License 申请** -| | | +正文： +| | | | :----: | :----: | | 申请人名称 | xxx | | 申请人所在组织名称 | xxx | @@ -67,18 +73,24 @@ TCA独立工具License申请邮件 | 首次登记的机器码 | xxx | | 体验申请用途 | xxx | -4. 收到 TCA 团队回复邮件之后，在 CLS 目录下的[config.yaml](https://github.com/Tencent/CodeAnalysis/blob/main/server/cls/config.yaml)文件中填写License -注意！请遵从yaml格式，比如： -- 键值对中，冒号 `:` 后面一定要跟一个空白字符，示例 `key: value`. +4. 收到 TCA 团队回复邮件之后，在 CLS 目录下的[`config.yaml`](https://github.com/Tencent/CodeAnalysis/blob/main/server/cls/config.yaml)文件中填写License + +::: warning +注意：遵从yaml格式， +比如： +- 键值对中，冒号 `:` 后面跟一个空白字符，示例 `key: value`. +::: + +5. 执行以下命令启动CLS -5. 执行以下命令启动 ```shell ./cls server -d ``` 6. 启动 TCA 分析任务 +在 TCA 平台的分析方案里面勾选独立工具相关的规则包。 -### 运维 +### CLS 运维 #### 自动重启 ```shell # 查找CLS进程ID @@ -87,6 +99,3 @@ ps aux|grep cls kill -USR2 ``` -## 使用 - -在 TCA 对应项目的分析方案里面勾选名称以 `TCA-Armory` 开头的工具的规则。 diff --git a/doc/zh/quickStarted/references/install_mysql_on_centos.md b/doc/zh/advanced/install_mysql_on_centos.md similarity index 100% rename from doc/zh/quickStarted/references/install_mysql_on_centos.md rename to doc/zh/advanced/install_mysql_on_centos.md diff --git a/doc/zh/quickStarted/references/install_nginx_from_source.md b/doc/zh/advanced/install_nginx_from_source.md similarity index 100% rename from doc/zh/quickStarted/references/install_nginx_from_source.md rename to doc/zh/advanced/install_nginx_from_source.md diff --git a/doc/zh/quickStarted/references/install_python37_on_centos.md b/doc/zh/advanced/install_python37_on_centos.md similarity index 100% rename from doc/zh/quickStarted/references/install_python37_on_centos.md rename to doc/zh/advanced/install_python37_on_centos.md diff --git a/doc/zh/quickStarted/references/install_python37_on_ubuntu.md b/doc/zh/advanced/install_python37_on_ubuntu.md similarity index 100% rename from doc/zh/quickStarted/references/install_python37_on_ubuntu.md rename to doc/zh/advanced/install_python37_on_ubuntu.md diff --git a/doc/zh/quickStarted/references/install_redis_from_source.md b/doc/zh/advanced/install_redis_from_source.md similarity index 100% rename from doc/zh/quickStarted/references/install_redis_from_source.md rename to doc/zh/advanced/install_redis_from_source.md diff --git a/doc/zh/quickStarted/references/install_redis_on_centos.md b/doc/zh/advanced/install_redis_on_centos.md similarity index 100% rename from doc/zh/quickStarted/references/install_redis_on_centos.md rename to doc/zh/advanced/install_redis_on_centos.md

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