feat(script): SEO auditor + PROGRESS.md v24 update
Add seo_auditor.py - crawls external websites, scores 6 SEO dimensions (meta/heading/content/performance/links/mobile), generates optimization tasks. Update PROGRESS.md with v24 external promotion feature. Ultraworked with [Sisyphus](https://github.com/code-yeongyu/oh-my-openagent) Co-authored-by: Sisyphus <clio-agent@sisyphuslabs.ai>
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> 本文件为项目进度唯一真理源，所有进度信息以此为准。
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> 本文件为项目进度唯一真理源，所有进度信息以此为准。
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> 其他文档中的进度描述一律以本文为准。
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> 其他文档中的进度描述一律以本文为准。
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**最后更新**：2026-06-17 (v23)
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**最后更新**：2026-06-21 (v24)
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---
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---
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@@ -173,6 +173,65 @@
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| Landing 页 GitHub 链接修正 | 2026-06-18 | `your-org` → `github.com` |
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| Landing 页 GitHub 链接修正 | 2026-06-18 | `your-org` → `github.com` |
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| v23 全部功能验收 | 2026-06-18 | 12 页 200 OK、org_id 隔离生效、RBAC(require_role)11路由、菜单7项正确、factory/insights 新页、dashboard 重设计 |
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| v23 全部功能验收 | 2026-06-18 | 12 页 200 OK、org_id 隔离生效、RBAC(require_role)11路由、菜单7项正确、factory/insights 新页、dashboard 重设计 |
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## 十一、外推营销系统（v24 · 2026-06-21）
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### 从「内容生产」到「外部推广」
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**背景**：平台此前只覆盖平台内生产的内容的 SEO/GEO 优化，无法对用户已有的外部网站、公众号、小程序等做 SEO 推广。v24 新增完整的外部推广模块。
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### 新增数据模型（6 张表）
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| 模型 | 表名 | 说明 |
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|------|------|------|
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| `ExternalProduct` | `external_products` | 外部推广产品（website/article/wechat_account/miniprogram）|
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| `PromotionCampaign` | `promotion_campaigns` | 推广活动，关联产品和关键词 |
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| `CampaignKeyword` | `campaign_keywords` | 关键词跟踪（搜索量/难度/排名）|
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| `SEOAudit` | `seo_audits` | SEO 审计报告（6 维度评分）|
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| `KeywordRanking` | `keyword_rankings` | 多引擎关键词排名记录 |
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| `OptimizationTask` | `optimization_tasks` | AI 生成的优化建议 |
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### API 端点（20 个）
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| 端点 | 功能 |
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|------|------|
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| `GET/POST/PUT/DELETE /api/external/products` | 产品 CRUD |
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| `GET/POST/PUT/DELETE /api/external/campaigns` | 活动 CRUD |
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| `GET/POST/PUT/DELETE /api/external/keywords` | 关键词 CRUD |
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| `GET /api/external/audits` | SEO 审计记录列表 |
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| `GET /api/external/audits/{id}` | 审计详情（含优化建议）|
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| `GET /api/external/rankings` | 关键词排名列表 |
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| `GET /api/external/rankings/overview` | 排名概览统计 |
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| `GET /api/external/optimization-tasks` | 优化建议列表 |
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| `PATCH /api/external/optimization-tasks/{id}` | 更新任务状态 |
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| `GET /api/external/overview` | 外推营销总览 |
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### SEO 审计脚本
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`scripts/seo_auditor.py` — 自动抓取目标网站并分析：
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| 维度 | 权重 | 检测项 |
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|------|------|--------|
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| Meta 标签 | 20% | title/description/keywords/OG tags |
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| 标题结构 | 15% | H1/H2 存在性、层级连续性 |
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| 内容质量 | 25% | 字数、图片 alt、关键词密度 |
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| 性能 | 10% | 渲染阻塞资源、图片尺寸 |
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| 链接 | 10% | 内链/外链/断链/nofollow |
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| 移动端 | 20% | viewport、响应式、字号 |
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审计结果自动保存到 DB，生成可追踪的 OptimizationTask。
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### 关键文件变更
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| 文件 | 改动 |
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|------|------|
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| `platform/backend/app/models.py` | 新增 6 个模型（ExternalProduct/PromotionCampaign/CampaignKeyword/SEOAudit/KeywordRanking/OptimizationTask）|
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| `platform/backend/app/schemas.py` | 新增 18 个 Pydantic schema 类 |
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| `platform/backend/app/api/external_promotion.py` | **新建** — 20 个 API 端点 |
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| `platform/backend/app/main.py` | 注册 external_promotion router |
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| `platform/frontend/campaigns.html` | **新建** — 外推营销 SPA 页面（6 Tab）|
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| `platform/frontend/uni-nav.js` | 导航增加「外推营销」入口 |
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| `scripts/seo_auditor.py` | **新建** — SEO 审计自动化脚本 |
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---
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---
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## 六、归档日志
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## 六、归档日志
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"""
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SEO Auditor — 外部网站 SEO 审计脚本
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功能：
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- 抓取目标网站首页和关键页面
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- 分析 Meta 标签、标题结构、内容质量、性能、链接、移动端适配
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- 生成评分报告（0-100 分/维度）
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- 自动生成优化建议
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- 结果写入 DB（SEOAudit + OptimizationTask）
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用法：
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python3 scripts/seo_auditor.py --product-id 1
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python3 scripts/seo_auditor.py --url https://example.com --name "我的网站"
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"""
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import sys
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import os
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import re
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import json
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import logging
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from datetime import datetime, timezone
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from urllib.parse import urlparse
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sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'platform', 'backend'))
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logging.basicConfig(level=logging.INFO, format='%(asctime)s [%(levelname)s] %(message)s')
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logger = logging.getLogger(__name__)
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def extract_meta(html):
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"""分析 Meta 标签"""
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score = 100
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issues = []
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title = re.search(r'<title[^>]*>(.*?)</title>', html, re.I | re.S)
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if not title:
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score -= 30
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issues.append({"category": "meta", "severity": "high", "issue": "缺少 <title> 标签", "recommendation": "添加包含目标关键词的 title 标签，建议 50-60 字符"})
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else:
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t = title.group(1).strip()
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if len(t) < 10:
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score -= 15
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issues.append({"category": "meta", "severity": "medium", "issue": f"title 过短 ({len(t)}字符)", "recommendation": "title 建议 50-60 字符"})
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if len(t) > 80:
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score -= 10
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issues.append({"category": "meta", "severity": "low", "issue": f"title 过长 ({len(t)}字符)", "recommendation": "title 超过 80 字符可能在搜索结果中被截断"})
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desc = re.search(r'<meta\s+name=["\']description["\'][^>]*content=["\']([^"\']*)["\']', html, re.I)
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if not desc:
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score -= 25
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issues.append({"category": "meta", "severity": "high", "issue": "缺少 meta description", "recommendation": "添加包含关键词的 meta description，建议 120-160 字符"})
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else:
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d = desc.group(1).strip()
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if len(d) < 50:
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score -= 10
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issues.append({"category": "meta", "severity": "medium", "issue": f"description 过短 ({len(d)}字符)", "recommendation": "description 建议 120-160 字符"})
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keywords = re.search(r'<meta\s+name=["\']keywords["\'][^>]*content=["\']([^"\']*)["\']', html, re.I)
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if not keywords:
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score -= 5
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issues.append({"category": "meta", "severity": "low", "issue": "缺少 meta keywords", "recommendation": "添加 meta keywords（虽然不是排名因素，但用于内容相关性提示）"})
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og_title = re.search(r'<meta\s+property=["\']og:title["\'][^>]*content=["\']([^"\']*)["\']', html, re.I)
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og_desc = re.search(r'<meta\s+property=["\']og:description["\'][^>]*content=["\']([^"\']*)["\']', html, re.I)
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og_image = re.search(r'<meta\s+property=["\']og:image["\'][^>]*content=["\']([^"\']*)["\']', html, re.I)
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if not og_title:
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score -= 10
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issues.append({"category": "meta", "severity": "medium", "issue": "缺少 og:title", "recommendation": "添加 Open Graph title 改善社交分享展示"})
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if not og_desc:
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score -= 5
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issues.append({"category": "meta", "severity": "low", "issue": "缺少 og:description", "recommendation": "添加 og:description 改善社交分享展示"})
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if not og_image:
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score -= 5
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issues.append({"category": "meta", "severity": "low", "issue": "缺少 og:image", "recommendation": "添加 og:image 让分享链接显示缩略图"})
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return max(0, score), issues
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def extract_headings(html):
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"""分析标题结构"""
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score = 100
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issues = []
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h1s = re.findall(r'<h1[^>]*>(.*?)</h1>', html, re.I | re.S)
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if len(h1s) == 0:
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score -= 30
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issues.append({"category": "heading", "severity": "high", "issue": "页面缺少 H1 标签", "recommendation": "每个页面应当只有一个 H1，包含主要关键词"})
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elif len(h1s) > 1:
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score -= 15
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issues.append({"category": "heading", "severity": "medium", "issue": f"存在 {len(h1s)} 个 H1 标签", "recommendation": "每个页面应当只有一个 H1 标签"})
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else:
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h1_text = re.sub(r'<[^>]+>', '', h1s[0]).strip()
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if len(h1_text) < 5:
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score -= 5
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issues.append({"category": "heading", "severity": "low", "issue": "H1 内容过短", "recommendation": "H1 应清晰描述页面主题"})
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h2s = re.findall(r'<h2[^>]*>(.*?)</h2>', html, re.I | re.S)
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if len(h2s) == 0 and len(re.findall(r'<(h[2-6])', html, re.I)) > 0:
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pass
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elif len(h2s) == 0:
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score -= 10
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issues.append({"category": "heading", "severity": "medium", "issue": "缺少 H2 子标题", "recommendation": "使用 H2 组织内容结构，提升可读性和 SEO"})
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# Check heading hierarchy
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all_headings = re.findall(r'<h([1-6])[^>]*>', html, re.I)
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if all_headings:
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prev_level = int(all_headings[0])
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for level in all_headings[1:]:
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l = int(level)
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if l > prev_level + 1:
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score -= 5
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issues.append({"category": "heading", "severity": "medium", "issue": f"标题层级跳级：H{prev_level} → H{l}", "recommendation": "标题层级应连续，不要跳级"})
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break
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prev_level = l
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return max(0, score), issues
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def extract_content(html):
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"""分析内容质量"""
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score = 100
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issues = []
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text = re.sub(r'<[^>]+>', ' ', html)
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text = re.sub(r'\s+', ' ', text).strip()
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word_count = len(text)
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if word_count < 300:
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score -= 30
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issues.append({"category": "content", "severity": "high", "issue": f"内容过短（{word_count}字符）", "recommendation": "正文建议至少 300 字符，优质内容建议 1000+ 字符"})
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elif word_count < 1000:
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score -= 15
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issues.append({"category": "content", "severity": "medium", "issue": f"内容偏短（{word_count}字符）", "recommendation": "增加内容深度，建议达到 1000+ 字符"})
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# Check image alt
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imgs = re.findall(r'<img[^>]+>', html, re.I)
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no_alt = sum(1 for img in imgs if 'alt=' not in img.lower())
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if imgs and no_alt == len(imgs):
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score -= 10
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issues.append({"category": "content", "severity": "medium", "issue": "所有图片缺少 alt 属性", "recommendation": "为图片添加描述性的 alt 文本"})
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elif no_alt > 0:
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score -= 5
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issues.append({"category": "content", "severity": "low", "issue": f"{no_alt}/{len(imgs)} 张图片缺少 alt", "recommendation": "为剩余图片补全 alt 属性"})
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return max(0, score), issues, {"word_count": word_count, "image_count": len(imgs)}
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def extract_links(html, base_url):
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"""分析链接"""
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score = 100
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issues = []
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domain = urlparse(base_url).netloc
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internal_links = re.findall(r'href=["\'](https?://[^"\']+)["\']', html, re.I)
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external_links = [url for url in internal_links if urlparse(url).netloc != domain]
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internal_links = [url for url in internal_links if urlparse(url).netloc == domain]
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broken_keywords = re.findall(r'href=["\']([^"\']*(?:404|broken|dead)[^"\']*)["\']', html, re.I)
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if len(internal_links) == 0:
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score -= 15
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issues.append({"category": "links", "severity": "medium", "issue": "页面没有内部链接", "recommendation": "添加指向站内其他页面的链接，改善爬虫抓取和用户导航"})
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if len(external_links) == 0:
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pass
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ext_no_nofollow = re.findall(r'<a\s+[^>]*href=["\']https?://(?!' + re.escape(domain) + r')["\'][^>]*>', html, re.I)
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if ext_no_nofollow:
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score -= 5
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issues.append({"category": "links", "severity": "low", "issue": "外部链接缺少 nofollow", "recommendation": "对外部链接添加 rel=\"nofollow noopener\" 属性"})
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# Check for broken link patterns
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broken = re.findall(r'href=["\'](?:https?://[^"\']*?(?:404|error|not-found)[^"\']*)["\']', html, re.I)
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if broken:
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score -= 10
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issues.append({"category": "links", "severity": "high", "issue": f"发现 {len(broken)} 个疑似断链", "recommendation": "检查并修复或删除失效链接"})
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return max(0, score), issues, {"internal": len(internal_links), "external": len(external_links)}
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def extract_performance(html):
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"""分析性能(基础版 — 仅分析可前端检测的指标)"""
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score = 100
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issues = []
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# Check for render-blocking resources
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css_links = re.findall(r'<link[^>]*href=["\'].*?\.css["\']', html, re.I)
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js_scripts = re.findall(r'<script[^>]*src=["\']([^"\']+)["\']', html, re.I)
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render_blocking = len(css_links) + len(js_scripts)
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if render_blocking > 10:
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score -= 10
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issues.append({"category": "performance", "severity": "medium", "issue": f"存在 {render_blocking} 个渲染阻塞资源", "recommendation": "考虑异步加载非关键 CSS/JS，使用 defer 或 async"})
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||||||
|
# Check image without dimensions
|
||||||
|
imgs_no_dim = re.findall(r'<img(?!\s*(?:width|height)=)', html, re.I)
|
||||||
|
if imgs_no_dim:
|
||||||
|
score -= 5
|
||||||
|
issues.append({"category": "performance", "severity": "low", "issue": f"存在 {len(imgs_no_dim)} 张无宽高属性的图片", "recommendation": "为图片添加 width/height 属性，减少布局偏移(CLS)"})
|
||||||
|
|
||||||
|
return max(0, score), issues
|
||||||
|
|
||||||
|
|
||||||
|
def extract_mobile(html):
|
||||||
|
"""分析移动端适配"""
|
||||||
|
score = 100
|
||||||
|
issues = []
|
||||||
|
|
||||||
|
viewport = re.search(r'<meta\s+name=["\']viewport["\'][^>]*content=["\']([^"\']*)["\']', html, re.I)
|
||||||
|
if not viewport:
|
||||||
|
score -= 40
|
||||||
|
issues.append({"category": "mobile", "severity": "high", "issue": "缺少 viewport meta 标签", "recommendation": "添加 <meta name=\"viewport\" content=\"width=device-width, initial-scale=1\"> 确保移动端正确渲染"})
|
||||||
|
|
||||||
|
# Check for responsive CSS
|
||||||
|
media_queries = re.findall(r'@media\s', html, re.I)
|
||||||
|
if not media_queries:
|
||||||
|
score -= 15
|
||||||
|
issues.append({"category": "mobile", "severity": "medium", "issue": "未检测到响应式 CSS", "recommendation": "实现响应式设计，使用媒体查询适配不同屏幕尺寸"})
|
||||||
|
|
||||||
|
# Check font size
|
||||||
|
font_small = re.findall(r'font-size\s*:\s*(?:10|11|12)px', html, re.I)
|
||||||
|
if font_small:
|
||||||
|
score -= 5
|
||||||
|
issues.append({"category": "mobile", "severity": "low", "issue": "检测到小字体 (≤12px)", "recommendation": "移动端正文字号建议至少 16px 防止 iOS 自动缩放"})
|
||||||
|
|
||||||
|
return max(0, score), issues
|
||||||
|
|
||||||
|
|
||||||
|
def audit_url(url, name=None):
|
||||||
|
"""对单个 URL 执行完整 SEO 审计"""
|
||||||
|
import urllib.request
|
||||||
|
import ssl
|
||||||
|
|
||||||
|
parsed = urlparse(url)
|
||||||
|
domain = parsed.netloc
|
||||||
|
page_name = name or domain
|
||||||
|
|
||||||
|
logger.info(f"审计: {page_name} ({url})")
|
||||||
|
|
||||||
|
try:
|
||||||
|
ctx = ssl.create_default_context()
|
||||||
|
ctx.check_hostname = False
|
||||||
|
ctx.verify_mode = ssl.CERT_NONE
|
||||||
|
req = urllib.request.Request(url, headers={
|
||||||
|
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36',
|
||||||
|
'Accept': 'text/html,application/xhtml+xml',
|
||||||
|
'Accept-Language': 'zh-CN,zh;q=0.9',
|
||||||
|
})
|
||||||
|
resp = urllib.request.urlopen(req, timeout=15, context=ctx)
|
||||||
|
html = resp.read().decode('utf-8', errors='ignore')
|
||||||
|
logger.info(f" 获取成功: {len(html)} bytes")
|
||||||
|
except Exception as e:
|
||||||
|
logger.error(f" 获取失败: {e}")
|
||||||
|
return None
|
||||||
|
|
||||||
|
meta_score, meta_issues = extract_meta(html)
|
||||||
|
heading_score, heading_issues = extract_headings(html)
|
||||||
|
content_score, content_issues, content_info = extract_content(html)
|
||||||
|
perf_score, perf_issues = extract_performance(html)
|
||||||
|
links_score, links_issues, links_info = extract_links(html, url)
|
||||||
|
mobile_score, mobile_issues = extract_mobile(html)
|
||||||
|
|
||||||
|
all_issues = meta_issues + heading_issues + content_issues + perf_issues + links_issues + mobile_issues
|
||||||
|
overall_score = round(
|
||||||
|
meta_score * 0.20 +
|
||||||
|
heading_score * 0.15 +
|
||||||
|
content_score * 0.25 +
|
||||||
|
perf_score * 0.10 +
|
||||||
|
links_score * 0.10 +
|
||||||
|
mobile_score * 0.20,
|
||||||
|
1
|
||||||
|
)
|
||||||
|
|
||||||
|
raw_data = {
|
||||||
|
"url": url,
|
||||||
|
"title": re.search(r'<title[^>]*>(.*?)</title>', html, re.I | re.S).group(1).strip() if re.search(r'<title[^>]*>(.*?)</title>', html, re.I | re.S) else None,
|
||||||
|
"content_info": content_info,
|
||||||
|
"links_info": links_info,
|
||||||
|
"issues_count": len(all_issues),
|
||||||
|
"issues_by_severity": {
|
||||||
|
"high": sum(1 for i in all_issues if i.get("severity") == "high"),
|
||||||
|
"medium": sum(1 for i in all_issues if i.get("severity") == "medium"),
|
||||||
|
"low": sum(1 for i in all_issues if i.get("severity") == "low"),
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
result = {
|
||||||
|
"url": url,
|
||||||
|
"page_name": page_name,
|
||||||
|
"overall_score": overall_score,
|
||||||
|
"meta_score": meta_score,
|
||||||
|
"heading_score": heading_score,
|
||||||
|
"content_score": content_score,
|
||||||
|
"perf_score": perf_score,
|
||||||
|
"links_score": links_score,
|
||||||
|
"mobile_score": mobile_score,
|
||||||
|
"issues_found": len(all_issues),
|
||||||
|
"raw_data": raw_data,
|
||||||
|
"issues": all_issues,
|
||||||
|
}
|
||||||
|
|
||||||
|
logger.info(f" 总分: {overall_score}/100 (Meta:{meta_score} 标题:{heading_score} 内容:{content_score} 性能:{perf_score} 链接:{links_score} 移动端:{mobile_score})")
|
||||||
|
logger.info(f" 发现问题: {len(all_issues)} ({raw_data['issues_by_severity']['high']}高/{raw_data['issues_by_severity']['medium']}中/{raw_data['issues_by_severity']['low']}低)")
|
||||||
|
|
||||||
|
return result
|
||||||
|
|
||||||
|
|
||||||
|
def save_audit_to_db(product_id, result):
|
||||||
|
"""将审计结果写入 DB"""
|
||||||
|
try:
|
||||||
|
from app.database import SessionLocal
|
||||||
|
from app.models import ExternalProduct, SEOAudit, OptimizationTask
|
||||||
|
|
||||||
|
db = SessionLocal()
|
||||||
|
try:
|
||||||
|
product = db.query(ExternalProduct).filter(ExternalProduct.id == product_id).first()
|
||||||
|
if not product:
|
||||||
|
logger.error(f"产品 {product_id} 不存在")
|
||||||
|
return False
|
||||||
|
|
||||||
|
audit = SEOAudit(
|
||||||
|
product_id=product_id,
|
||||||
|
audit_type="full",
|
||||||
|
overall_score=result["overall_score"],
|
||||||
|
meta_score=result["meta_score"],
|
||||||
|
heading_score=result["heading_score"],
|
||||||
|
content_score=result["content_score"],
|
||||||
|
perf_score=result["perf_score"],
|
||||||
|
links_score=result["links_score"],
|
||||||
|
mobile_score=result["mobile_score"],
|
||||||
|
raw_data=result.get("raw_data"),
|
||||||
|
page_count=1,
|
||||||
|
issues_found=result["issues_found"],
|
||||||
|
org_id=product.org_id,
|
||||||
|
)
|
||||||
|
db.add(audit)
|
||||||
|
db.flush()
|
||||||
|
|
||||||
|
for issue in result.get("issues", []):
|
||||||
|
task = OptimizationTask(
|
||||||
|
audit_id=audit.id,
|
||||||
|
product_id=product_id,
|
||||||
|
category=issue.get("category", "other"),
|
||||||
|
severity=issue.get("severity", "medium"),
|
||||||
|
issue=issue.get("issue", ""),
|
||||||
|
recommendation=issue.get("recommendation"),
|
||||||
|
status="open",
|
||||||
|
org_id=product.org_id,
|
||||||
|
)
|
||||||
|
db.add(task)
|
||||||
|
|
||||||
|
db.commit()
|
||||||
|
logger.info(f" 审计结果已保存: audit_id={audit.id}, tasks={len(result.get('issues', []))}")
|
||||||
|
return True
|
||||||
|
except Exception as e:
|
||||||
|
db.rollback()
|
||||||
|
logger.error(f" DB 保存失败: {e}")
|
||||||
|
return False
|
||||||
|
finally:
|
||||||
|
db.close()
|
||||||
|
except ImportError as e:
|
||||||
|
logger.error(f" 无法导入应用模块: {e}")
|
||||||
|
logger.info(" (审计结果仅输出到日志)")
|
||||||
|
return False
|
||||||
|
|
||||||
|
|
||||||
|
def run_for_product(product_id):
|
||||||
|
"""为指定产品执行 SEO 审计"""
|
||||||
|
sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'platform', 'backend'))
|
||||||
|
try:
|
||||||
|
from app.database import SessionLocal
|
||||||
|
from app.models import ExternalProduct
|
||||||
|
db = SessionLocal()
|
||||||
|
try:
|
||||||
|
product = db.query(ExternalProduct).filter(ExternalProduct.id == product_id).first()
|
||||||
|
if not product:
|
||||||
|
logger.error(f"产品 {product_id} 不存在")
|
||||||
|
return
|
||||||
|
url = product.url
|
||||||
|
name = product.name
|
||||||
|
finally:
|
||||||
|
db.close()
|
||||||
|
except ImportError:
|
||||||
|
logger.error("无法连接到数据库，请确保在项目根目录运行")
|
||||||
|
return
|
||||||
|
|
||||||
|
if not url:
|
||||||
|
logger.error(f"产品 {name} 没有配置 URL")
|
||||||
|
return
|
||||||
|
|
||||||
|
result = audit_url(url, name)
|
||||||
|
if not result:
|
||||||
|
logger.error("审计失败")
|
||||||
|
return
|
||||||
|
|
||||||
|
save_audit_to_db(product_id, result)
|
||||||
|
return result
|
||||||
|
|
||||||
|
|
||||||
|
def run_for_url(url, name=None):
|
||||||
|
"""为指定 URL 执行审计（不保存到 DB）"""
|
||||||
|
result = audit_url(url, name)
|
||||||
|
return result
|
||||||
|
|
||||||
|
|
||||||
|
if __name__ == "__main__":
|
||||||
|
import argparse
|
||||||
|
parser = argparse.ArgumentParser(description="SEO Auditor - 外部网站 SEO 审计")
|
||||||
|
parser.add_argument("--product-id", type=int, help="产品 ID（从 DB 读取 URL）")
|
||||||
|
parser.add_argument("--url", help="直接指定 URL")
|
||||||
|
parser.add_argument("--name", help="页面名称")
|
||||||
|
args = parser.parse_args()
|
||||||
|
|
||||||
|
if args.product_id:
|
||||||
|
run_for_product(args.product_id)
|
||||||
|
elif args.url:
|
||||||
|
result = run_for_url(args.url, args.name)
|
||||||
|
if result:
|
||||||
|
print(json.dumps(result, ensure_ascii=False, indent=2))
|
||||||
|
else:
|
||||||
|
parser.print_help()
|
||||||
Reference in New Issue
Block a user