Gzh Search Crawler
- 265 installs
- 316 repo stars
- Updated August 4, 2026
- redfox-data/redfox-community
Search and crawl Gzhonghao (WeChat Official Accounts) content; enables content teams to research trends and gather inspiration.
About
Crawler skill for searching and analyzing content from Gzhonghao (WeChat Official Accounts). Part of redfox-data community skills; enables Claude Code and content teams to discover trending topics, research content strategies, and gather inspiration from Chinese social platforms.
- WeChat content search
- Trend discovery
- Content research
- Crawler automation
Gzh Search Crawler by the numbers
- 265 all-time installs (skills.sh)
- +19 installs in the week ending Aug 4, 2026 (Skillselion tracking)
- Ranked #183 of 550 CLI & Terminal skills by installs in the Skillselion catalog
- Data as of Aug 5, 2026 (Skillselion catalog sync)
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| Installs | 265 |
|---|---|
| repo stars | ★ 316 |
| Last updated | August 4, 2026 |
| Repository | redfox-data/redfox-community ↗ |
What it does
Search and crawl Gzhonghao (WeChat Official Accounts) content; enables content teams to research trends and gather inspiration.
Who is it for?
Content strategy research in Chinese markets
Skip if: English-speaking markets without Chinese content focus
Files
公众号搜索爬虫
输入关键词搜索微信公众号文章，终端表格展示 + CSV 导出 + 交互式 HTML 报告。
API 请求均携带 公众号搜索爬虫-SkillHub 标识。需先配置 API Key，通过环境变量 REDFOX_API_KEY 或 --api-key 参数传入。爬取范围：腰部以上公众号近 30 天内发布的文章。
关键词限制：不超过 10 个字符，超出会提示精简。
---
使用场景
当你需要执行以下任务时，应优先使用本技能：
| 场景 | 示例 |
|---|---|
| 行业热点追踪 | 搜 "AI" 了解近期 AI 领域公众号都在讨论什么 |
| 竞品内容分析 | 搜 "大模型" 爬取竞争对手公众号的文章策略 |
| 素材灵感搜集 | 搜 "小红书运营" 获取爆款选题和写作角度 |
| 趋势研究报告 | 搜 "2026 经济" 批量导出 CSV 做数据分析 |
| 寻找优质账号 | 搜 "科技" 发现相关领域的头部公众号 |
| 话题舆情监控 | 搜 "品牌名" 查看公众号对该品牌的讨论风向 |
如果你想搜某个特定公众号的全部历史文章，应使用 gzh-subscribe 技能（公众号文章订阅），它专门针对单账号订阅追踪。---
使用方法
# 基础搜索
python3 "$SKILL_PATH/assets/search.py" "关键词"
# 指定数量（多页自动翻页）
python3 "$SKILL_PATH/assets/search.py" "AI" --count 50
# 仅导出 CSV
python3 "$SKILL_PATH/assets/search.py" "大模型" --csv-only
# 不自动打开浏览器
python3 "$SKILL_PATH/assets/search.py" "AI" --no-open终端输出按综合评分（关键词相关性 + 阅读热度 + 时效新鲜度）降序排列，同分时按阅读量高的优先；结果较少或无结果时自动分层提示。
HTML 报告特性：深色主题 · 实时搜索（300ms 防抖）· 文章卡片点击跳转原文 · 分页加载 · 零结果时引导热门话题。
CSV / HTML 默认保存在 ~/Downloads/QoderGzhSearch/。
---
参数说明
| 参数 | 说明 | 默认值 |
|---|---|---|
keyword | 搜索关键词（必填，位置参数） | — |
--count | 获取文章数量 | 20 |
--sort-type | 排序方式：default / time | default |
--output-dir | 输出目录 | ~/Downloads/QoderGzhSearch |
--api-key | 指定 API Key | — |
--no-open | 不自动打开浏览器 | — |
--csv-only | 仅生成 CSV，不生成 HTML | — |
--port | HTML 本地服务端口 | 8766 |
---
API Key 配置
任选一种方式配置个人 Key：
| 方式 | 命令 |
|---|---|
| 环境变量（推荐） | export REDFOX_API_KEY=ak_你的密钥 |
| 命令行参数 | --api-key ak_你的密钥 |
| 配置文件 | echo '{"api_key":"ak_你的密钥"}' > ~/.qoder/apis/redfox.json |
注册地址：redfox.hk
---
功能特点
- 关键词搜索：实时查询全量微信公众号文章
- 智能评分排序：三因子（相关性 + 热度 + 时效）综合评分，同分按阅读量降序
- 分层响应降级：充足时正常浏览 / 较少时引导宽泛搜索 / 无结果时热门兜底
- 终端表格：标题、作者、阅读、点赞、分享、收藏、发布时间、文章链接
- CSV 导出：自动生成 UTF-8 BOM 编码的 CSV
- HTML 交互报告：内置搜索框，支持封面图展示，点击卡片跳转原文
- 本地代理服务：避免浏览器跨域限制
---
依赖
pip3 install requests---
常见问题
Q：搜索范围？ A：目前覆盖腰部以上公众号近 30 天内发布的文章，不保证覆盖所有账号和全部历史。
Q：我想搜某个特定公众号的所有文章怎么办？ A：请使用 gzh-subscribe 技能（公众号文章订阅），它支持按公众号 ID 订阅追踪单账号的全部文章。
Q：最多返回多少条？ A：单次默认 20 条，通过 --count 调整，HTML 页面支持分页加载更多。
Q：数据保存在哪？ A：~/Downloads/QoderGzhSearch/，文件名格式 公众号搜索_[关键词]_YYYY-MM-DD.csv/html。
Q：为什么需要本地服务？ A：浏览器直接打开 HTML 有跨域限制，内置 HTTP 代理中转 API 请求。
Q：额度用完怎么办？ A：前往 redfox.hk 注册获取 Token。
<!DOCTYPE html>
<html lang="zh-CN">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>公众号搜索 · {{KEYWORD}} | {{DATE}}</title>
<!-- Fonts: Space Grotesk (body) + Inter (fallback) -->
<link rel="preconnect" href="https://fonts.googleapis.com">
<link rel="preconnect" href="https://fonts.gstatic.com" crossorigin>
<link href="https://fonts.googleapis.com/css2?family=Space+Grotesk:wght@300;400;500;600;700&display=swap" rel="stylesheet">
<style>
/* ═══════════════════════════════════════════════
CSS CUSTOM PROPERTIES — EMERALD SEARCH
═══════════════════════════════════════════════ */
:root {
--bg-primary: #0a0f0a;
--bg-secondary: #0f1a0f;
--bg-card: #141f14;
--bg-card-hover: #1a2a1a;
--text-primary: #e8efe8;
--text-secondary: #8a9a8a;
--text-muted: #556655;
--accent: #2ECC71;
--accent-light: #58D68D;
--accent-glow: rgba(46, 204, 113, 0.12);
--accent-border: rgba(46, 204, 113, 0.25);
--border: rgba(255, 255, 255, 0.05);
--border-hover: rgba(46, 204, 113, 0.3);
--success: #27AE60;
--warning: #F39C12;
--error: #E74C3C;
--font-body: 'Space Grotesk', -apple-system, sans-serif;
--radius: 12px;
--radius-sm: 8px;
--ease-out: cubic-bezier(0.16, 1, 0.3, 1);
}
/* ═══════════════════════════════════════════════
RESET & BASE
═══════════════════════════════════════════════ */
* { margin: 0; padding: 0; box-sizing: border-box; }
html { scroll-behavior: smooth; }
body {
font-family: var(--font-body);
background: var(--bg-primary);
color: var(--text-primary);
line-height: 1.6;
min-height: 100vh;
}
/* ═══════════════════════════════════════════════
HEADER
═══════════════════════════════════════════════ */
.main-header {
text-align: center;
padding: 2.5rem 1.5rem 1.5rem;
position: relative;
max-width: 900px;
margin: 0 auto;
}
.main-header::after {
content: '';
position: absolute;
bottom: 0;
left: 50%;
transform: translateX(-50%);
width: 60px;
height: 2px;
background: var(--accent);
border-radius: 1px;
opacity: 0.5;
}
.main-header h1 {
font-size: clamp(1.4rem, 3vw, 2rem);
font-weight: 700;
color: var(--accent);
letter-spacing: -0.02em;
margin-bottom: 0.3rem;
}
.main-header .subtitle {
color: var(--text-secondary);
font-size: clamp(0.8rem, 1.2vw, 0.9rem);
font-weight: 300;
}
/* ═══════════════════════════════════════════════
STATS BAR
═══════════════════════════════════════════════ */
.stats-bar {
display: flex;
justify-content: center;
gap: 2rem;
padding: 1rem 1rem;
margin: 0 auto;
max-width: 600px;
flex-wrap: wrap;
}
.stat-item {
text-align: center;
min-width: 60px;
}
.stat-value {
font-size: clamp(1.1rem, 2vw, 1.4rem);
font-weight: 700;
color: var(--accent);
}
.stat-label {
font-size: clamp(0.65rem, 0.8vw, 0.75rem);
color: var(--text-muted);
text-transform: uppercase;
letter-spacing: 0.05em;
}
/* ═══════════════════════════════════════════════
SEARCH BAR
═══════════════════════════════════════════════ */
.search-container {
position: sticky;
top: 0;
z-index: 100;
background: linear-gradient(180deg, var(--bg-primary) 80%, transparent);
padding: 1rem 1.5rem 1.5rem;
backdrop-filter: blur(12px);
-webkit-backdrop-filter: blur(12px);
}
.search-wrapper {
max-width: 640px;
margin: 0 auto;
display: flex;
gap: 0.6rem;
align-items: center;
}
.search-input {
flex: 1;
padding: 0.75rem 1.2rem;
border: 1.5px solid var(--border);
border-radius: var(--radius);
background: var(--bg-secondary);
color: var(--text-primary);
font-size: 0.95rem;
font-family: var(--font-body);
outline: none;
transition: all 0.2s var(--ease-out);
}
.search-input::placeholder {
color: var(--text-muted);
}
.search-input:focus {
border-color: var(--accent);
box-shadow: 0 0 0 3px var(--accent-glow);
}
.search-info {
margin-top: 0.6rem;
text-align: center;
font-size: 0.75rem;
color: var(--text-muted);
}
/* ═══════════════════════════════════════════════
RESULTS GRID
═══════════════════════════════════════════════ */
.results-container {
max-width: 900px;
margin: 0 auto;
padding: 0.5rem 1.5rem 2rem;
}
.results-grid {
display: flex;
flex-direction: column;
gap: 0.5rem;
}
/* ── Article Card ── */
.article-card {
display: flex;
align-items: flex-start;
gap: 0.9rem;
padding: 0.9rem 1rem;
background: var(--bg-card);
border: 1px solid var(--border);
border-radius: var(--radius-sm);
cursor: pointer;
text-decoration: none;
color: inherit;
transition: all 0.15s var(--ease-out);
position: relative;
}
.article-card:hover {
background: var(--bg-card-hover);
border-color: var(--border-hover);
transform: translateX(2px);
}
.article-card:active {
transform: scale(0.995);
}
/* ── Card Left: Avatar ── */
.card-avatar {
width: 42px;
height: 42px;
min-width: 42px;
border-radius: var(--radius-sm);
background: var(--accent-glow);
border: 1px solid var(--accent-border);
display: flex;
align-items: center;
justify-content: center;
font-size: 1rem;
font-weight: 700;
color: var(--accent);
user-select: none;
}
/* ── Card Right: Content ── */
.card-content {
flex: 1;
min-width: 0;
}
.card-title {
font-size: 0.92rem;
font-weight: 500;
line-height: 1.45;
color: var(--text-primary);
margin-bottom: 0.35rem;
display: -webkit-box;
-webkit-line-clamp: 2;
-webkit-box-orient: vertical;
overflow: hidden;
}
.card-meta {
display: flex;
flex-wrap: wrap;
align-items: center;
gap: 0.5rem 1rem;
font-size: 0.75rem;
color: var(--text-secondary);
}
.card-meta .author {
color: var(--accent-light);
font-weight: 500;
max-width: 120px;
overflow: hidden;
text-overflow: ellipsis;
white-space: nowrap;
}
.card-meta .metric {
display: inline-flex;
align-items: center;
gap: 0.2rem;
white-space: nowrap;
}
.card-meta .pub-time {
color: var(--text-muted);
margin-left: auto;
}
/* ═══════════════════════════════════════════════
STATUS & LOADING
═══════════════════════════════════════════════ */
.status-message {
text-align: center;
padding: 3rem 1rem;
color: var(--text-secondary);
font-size: 0.9rem;
}
.status-message.loading {
color: var(--accent);
}
.status-message.error {
color: var(--error);
}
.status-message.empty {
color: var(--text-muted);
}
.loading-dots::after {
content: '';
animation: dots 1.5s steps(4, end) infinite;
}
@keyframes dots {
0% { content: ''; }
25% { content: '.'; }
50% { content: '..'; }
75% { content: '...'; }
100% { content: ''; }
}
/* ═══════════════════════════════════════════════
LOAD MORE
═══════════════════════════════════════════════ */
.load-more-bar {
display: flex;
justify-content: center;
padding: 1.5rem 1rem 3rem;
}
.load-more-btn {
padding: 0.65rem 2.2rem;
border: 1.5px solid var(--border);
border-radius: var(--radius);
background: var(--bg-card);
color: var(--text-secondary);
font-size: 0.85rem;
font-family: var(--font-body);
cursor: pointer;
transition: all 0.2s var(--ease-out);
}
.load-more-btn:hover {
border-color: var(--accent-border);
color: var(--accent);
background: var(--bg-card-hover);
}
.load-more-btn:disabled {
opacity: 0.4;
cursor: not-allowed;
}
/* ═══════════════════════════════════════════════
FOOTER
═══════════════════════════════════════════════ */
.footer {
text-align: center;
padding: 2rem 1rem;
color: var(--text-muted);
font-size: 0.72rem;
border-top: 1px solid var(--border);
max-width: 900px;
margin: 0 auto;
}
/* ═══════════════════════════════════════════════
RESPONSIVE
═══════════════════════════════════════════════ */
@media (max-width: 640px) {
.main-header { padding: 1.8rem 1rem 1rem; }
.search-wrapper { flex-direction: column; }
.search-input { padding: 0.7rem 1rem; }
.article-card { padding: 0.75rem 0.8rem; gap: 0.7rem; }
.card-title { font-size: 0.85rem; }
.card-meta { font-size: 0.7rem; gap: 0.4rem 0.6rem; }
.card-meta .pub-time { margin-left: 0; }
.stats-bar { gap: 1.2rem; }
}
/* ═══════════════════════════════════════════════
ANIMATIONS
═══════════════════════════════════════════════ */
@keyframes fadeInUp {
from { opacity: 0; transform: translateY(8px); }
to { opacity: 1; transform: translateY(0); }
}
.article-card {
animation: fadeInUp 0.3s var(--ease-out) both;
}
.article-card:nth-child(1) { animation-delay: 0.00s; }
.article-card:nth-child(2) { animation-delay: 0.03s; }
.article-card:nth-child(3) { animation-delay: 0.06s; }
.article-card:nth-child(4) { animation-delay: 0.09s; }
.article-card:nth-child(5) { animation-delay: 0.12s; }
.article-card:nth-child(6) { animation-delay: 0.15s; }
.article-card:nth-child(7) { animation-delay: 0.18s; }
.article-card:nth-child(8) { animation-delay: 0.21s; }
.article-card:nth-child(9) { animation-delay: 0.24s; }
.article-card:nth-child(10) { animation-delay: 0.27s; }
.article-card:nth-child(n+11) { animation-delay: 0.30s; }
/* ── Layered Banner ── */
.layered-banner {
display: none; max-width: 900px; margin: 0 auto 1rem; padding: 0.7rem 1.2rem;
border-radius: var(--radius-sm); font-size: 0.82rem; text-align: center;
}
.layered-banner.warning {
display: block; background: rgba(243,156,18,0.08); border: 1px solid rgba(243,156,18,0.2);
color: var(--warning);
}
.layered-banner.info {
display: block; background: rgba(52,152,219,0.08); border: 1px solid rgba(52,152,219,0.2);
color: #5DADE2;
}
/* ── Enhanced Empty State ── */
.empty-guidance {
display: none; max-width: 500px; margin: 2rem auto; text-align: center; padding: 2rem;
}
.empty-guidance .guidance-icon { font-size: 2.5rem; margin-bottom: 1rem; }
.empty-guidance .guidance-title { font-size: 0.95rem; color: var(--text-secondary); margin-bottom: 0.8rem; }
.empty-guidance .guidance-tips { list-style: none; font-size: 0.8rem; color: var(--text-muted); margin: 1rem 0; }
.empty-guidance .guidance-tips li { margin: 0.4rem 0; }
.empty-guidance .guidance-tips li::before { content: '\270F '; color: var(--accent); }
.suggestion-tags { margin-top: 1.5rem; }
.suggestion-label { font-size: 0.72rem; color: var(--text-muted); text-transform: uppercase; margin-bottom: 0.6rem; }
.tag-cloud { display: flex; gap: 0.5rem; flex-wrap: wrap; justify-content: center; }
.suggestion-tag {
padding: 0.35rem 0.9rem; border: 1px solid var(--accent-border);
border-radius: 20px; font-size: 0.78rem; color: var(--accent-light);
cursor: pointer; transition: all 0.15s; background: var(--bg-card);
}
.suggestion-tag:hover { background: var(--accent-glow); border-color: var(--accent); color: var(--accent); }
.fallback-list { margin-top: 1rem; }
.fallback-list a {
display: block; padding: 0.5rem 0.8rem; font-size: 0.82rem; color: var(--text-secondary);
text-decoration: none; border-radius: 6px; transition: background 0.15s;
}
.fallback-list a:hover { background: var(--bg-card-hover); color: var(--accent); }
</style>
</head>
<body>
<!-- ═══════════ HEADER ═══════════ -->
<header class="main-header">
<h1>公众号搜索爬虫</h1>
<p class="subtitle">{{DATE}} | 输入关键词实时搜索微信公众号文章</p>
</header>
<!-- ═══════════ STATS ═══════════ -->
<div class="stats-bar" id="statsBar">
<div class="stat-item">
<div class="stat-value" id="statTotal">{{TOTAL_COUNT}}</div>
<div class="stat-label">结果总数</div>
</div>
<div class="stat-item">
<div class="stat-value" id="statKeyword">{{KEYWORD}}</div>
<div class="stat-label">当前关键词</div>
</div>
<div class="stat-item">
<div class="stat-value" id="statLoaded">{{TOTAL_COUNT}}</div>
<div class="stat-label">已加载</div>
</div>
</div>
<!-- ═══════════ SEARCH BAR ═══════════ -->
<div class="search-container">
<div class="search-wrapper">
<input
type="text"
class="search-input"
id="searchInput"
placeholder="输入关键词搜索公众号文章（不超过 10 个字）..."
value="{{KEYWORD}}"
autofocus
>
</div>
<div class="search-info" id="searchInfo">
输入关键词后自动搜索（300ms 防抖） | 点击文章跳转原文阅读
</div>
</div>
<!-- ═══════════ RESULTS ═══════════ -->
<main class="results-container">
<div class="results-grid" id="resultsGrid">
<!-- 动态填充 -->
</div>
<div class="status-message loading" id="statusMsg" style="display:none;">
<span class="loading-dots">搜索中</span>
</div>
<div class="status-message empty" id="emptyMsg" style="display:none;">
暂无搜索结果，请尝试其他关键词
</div>
<!-- 分层提示横幅 -->
<div class="layered-banner" id="layeredBanner"></div>
<!-- 零结果增强引导 -->
<div class="empty-guidance" id="emptyGuidance">
<div class="guidance-icon">🔍</div>
<div class="guidance-title" id="guidanceTitle">抱歉，未找到相关结果</div>
<ul class="guidance-tips">
<li>尝试更短或更宽泛的关键词</li>
<li>使用英文关键词重试</li>
<li>浏览下方的热门话题</li>
</ul>
<div class="suggestion-tags" id="suggestionTags">
<div class="suggestion-label">🔥 热门话题参考</div>
<div class="tag-cloud" id="tagCloud"></div>
</div>
<div class="fallback-list" id="fallbackList"></div>
</div>
<div class="load-more-bar" id="loadMoreBar" style="display:none;">
<button class="load-more-btn" id="loadMoreBtn" onclick="loadMore()">加载更多结果</button>
</div>
</main>
<!-- ═══════════ FOOTER ═══════════ -->
<footer class="footer">
Generated at {{TIMESTAMP}} by 公众号搜索 Skill | Powered by redfox.hk
</footer>
<!-- ═══════════ SCRIPTS ═══════════ -->
<script>
// ─── 配置 ────────────────────────────────────────────────────────────────────
const API_URL = '{{API_URL}}';
const API_KEY = '{{API_KEY}}';
const SOURCE = '{{SOURCE}}';
const INITIAL_DATA = {{INITIAL_DATA}};
// ─── 状态 ────────────────────────────────────────────────────────────────────
let currentKeyword = '{{KEYWORD}}';
let currentOffset = 0;
let hasMore = true;
let totalCount = {{TOTAL_COUNT}};
let isLoading = false;
let accumulatedArticles = [];
// ─── DOM 引用 ─────────────────────────────────────────────────────────────────
const resultsGrid = document.getElementById('resultsGrid');
const statusMsg = document.getElementById('statusMsg');
const emptyMsg = document.getElementById('emptyMsg');
const loadMoreBar = document.getElementById('loadMoreBar');
const loadMoreBtn = document.getElementById('loadMoreBtn');
const searchInput = document.getElementById('searchInput');
const searchInfo = document.getElementById('searchInfo');
const statTotal = document.getElementById('statTotal');
const statLoaded = document.getElementById('statLoaded');
const statKeyword = document.getElementById('statKeyword');
// ─── 工具函数 ─────────────────────────────────────────────────────────────────
function formatNum(n) {
if (n == null || n === undefined) return '0';
n = Number(n);
if (isNaN(n)) return '0';
if (n >= 10000) return (n / 10000).toFixed(1) + 'w';
if (n >= 1000) return (n / 1000).toFixed(1) + 'k';
return String(n);
}
function escapeHTML(str) {
const div = document.createElement('div');
div.textContent = str || '';
return div.innerHTML;
}
function getAvatarChar(title) {
if (!title) return '文';
// 取第一个非标点非空格的中文或英文字符
const cleaned = title.replace(/[^\w\u4e00-\u9fff]/g, '').trim();
return cleaned.charAt(0) || '文';
}
// ─── 三因子评分 ─────────────────────────────────────────────────────────────
function scoreRelevance(keyword, article) {
const kw = (keyword || '').toLowerCase().trim();
const title = (article.title || '').toLowerCase();
const summary = (article.summary || '').toLowerCase();
if (!kw) return 5;
if (kw === title) return 10;
if (title.startsWith(kw)) return 9;
if (title.includes(kw)) return 8;
const words = kw.split(/\s+/).filter(w => w.length >= 2);
const titleHits = words.filter(w => title.includes(w)).length;
if (titleHits >= Math.ceil(words.length * 0.5) && words.length >= 2) return 6;
if (summary && summary.slice(0, Math.floor(summary.length/3)).includes(kw)) return 5;
if (summary && summary.includes(kw)) return 4;
if (titleHits > 0) return 3;
if (summary && words.some(w => summary.includes(w))) return 2;
return 1;
}
function scoreHeat(article) {
const r = article.readCount || article.clicksCount || 0;
if (r >= 100000) return 3;
if (r >= 50000) return 2.5;
if (r >= 10000) return 2;
if (r >= 5000) return 1.5;
if (r >= 1000) return 1;
return 0.5;
}
function scoreFreshness(article) {
try {
const pt = (article.publishTime || article.publicTime || '').slice(0,10);
if (!pt) return 0;
const days = (Date.now() - new Date(pt).getTime()) / 86400000;
if (days <= 7) return 2;
if (days <= 15) return 1.5;
if (days <= 30) return 1;
if (days <= 60) return 0.5;
return 0;
} catch(e) { return 0; }
}
function calculateScore(kw, article) {
return scoreRelevance(kw, article) + scoreHeat(article) + scoreFreshness(article);
}
// ─── 渲染文章列表 ─────────────────────────────────────────────────────────────
function renderArticleCard(article) {
const title = article.title || '无标题';
const author = article.author || '未知作者';
const reads = formatNum(article.readCount || article.clicksCount);
const likes = formatNum(article.likeCount);
const shares = formatNum(article.shareCount);
const collects = formatNum(article.collectCount);
const pubTime = (article.publishTime || article.publicTime || '').slice(0, 10);
const url = article.workUrl || article.url || '#';
const cover = article.coverUrl || '';
const avatar = getAvatarChar(title);
let avatarHTML;
if (cover) {
avatarHTML = `<img src="${cover}" alt="" loading="lazy">`;
} else {
avatarHTML = escapeHTML(avatar);
}
const card = document.createElement('a');
card.className = 'article-card';
card.href = url;
card.target = '_blank';
card.rel = 'noopener noreferrer';
card.innerHTML = `
<div class="card-avatar">${avatarHTML}</div>
<div class="card-content">
<div class="card-title">${escapeHTML(title)}</div>
<div class="card-meta">
<span class="author" title="${escapeHTML(author)}">${escapeHTML(author)}</span>
<span class="metric">👁 ${reads}</span>
<span class="metric">👍 ${likes}</span>
<span class="metric">📤 ${shares}</span>
<span class="metric">⭐ ${collects}</span>
${pubTime ? `<span class="pub-time">${pubTime}</span>` : ''}
</div>
</div>`;
return card;
}
function renderArticles(articles, append) {
if (!append) {
resultsGrid.innerHTML = '';
}
articles.forEach(article => {
resultsGrid.appendChild(renderArticleCard(article));
});
}
function updateUI() {
statTotal.textContent = totalCount || accumulatedArticles.length;
statLoaded.textContent = accumulatedArticles.length;
statKeyword.textContent = currentKeyword || '-';
loadMoreBar.style.display = hasMore ? 'flex' : 'none';
}
// ─── 数据获取 ─────────────────────────────────────────────────────────────────
function fetchArticles(keyword, offset, append) {
return fetch(API_URL, {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'X-API-KEY': API_KEY,
},
body: JSON.stringify({
keyword: keyword,
offset: offset,
sortType: 'default',
source: SOURCE,
}),
})
.then(r => r.json())
.then(res => {
if (res.code === 200 || res.code === 2000) {
const data = res.data || {};
const list = data.list || [];
hasMore = data.hasMore === 1;
totalCount = list.length > 0 ? (totalCount || list.length) : totalCount;
return list;
} else {
throw new Error(res.msg || 'API 返回错误');
}
});
}
function setLoading(loading) {
isLoading = loading;
if (loading) {
statusMsg.style.display = 'block';
emptyMsg.style.display = 'none';
loadMoreBtn.disabled = true;
} else {
statusMsg.style.display = 'none';
loadMoreBtn.disabled = false;
}
}
function showError(msg) {
statusMsg.style.display = 'block';
statusMsg.className = 'status-message error';
statusMsg.textContent = msg;
isLoading = false;
loadMoreBtn.disabled = false;
}
// ─── 分层 UI ─────────────────────────────────────────────────────────────────
function showLayeredBanner(count, keyword) {
const banner = document.getElementById('layeredBanner');
const guidance = document.getElementById('emptyGuidance');
guidance.style.display = 'none';
if (count >= 10) { banner.style.display = 'none'; return; }
banner.style.display = 'block';
if (count <= 2) {
banner.className = 'layered-banner info';
banner.textContent = '💡 相关结果较少（仅 ' + count + ' 条），建议尝试更短或更宽泛的关键词';
} else {
banner.className = 'layered-banner warning';
banner.textContent = '仅找到 ' + count + ' 条结果，以下为您展示全部';
}
}
function showEnhancedEmpty(keyword, fallbackArticles) {
document.getElementById('resultsGrid').innerHTML = '';
document.getElementById('statusMsg').style.display = 'none';
document.getElementById('loadMoreBar').style.display = 'none';
document.getElementById('layeredBanner').style.display = 'none';
const guidance = document.getElementById('emptyGuidance');
guidance.style.display = 'block';
document.getElementById('guidanceTitle').textContent = '抱歉，未找到与「' + keyword + '」直接相关的内容';
// suggestion tags
const defaultTags = ['AI', 'DeepSeek', '大模型', 'Claude', 'ChatGPT', '科技', '创业', '副业'];
const tc = document.getElementById('tagCloud');
tc.innerHTML = defaultTags.map(t => '<span class="suggestion-tag" onclick="quickSearch(\'' + t + '\')">' + t + '</span>').join('');
// fallback list
const fl = document.getElementById('fallbackList');
if (fallbackArticles && fallbackArticles.length) {
fl.innerHTML = '<div class="suggestion-label" style="margin-top:1rem">📄 热门文章推荐</div>' +
fallbackArticles.slice(0, 5).map(function(a) {
return '<a href="' + (a.workUrl || a.url || '#') + '" target="_blank">' +
escapeHTML(a.title || '无标题') + ' — ' + (a.author || '') + '</a>';
}).join('');
} else {
fl.innerHTML = '';
}
}
function quickSearch(kw) {
document.getElementById('searchInput').value = kw;
doSearch();
}
// ─── 搜索 ─────────────────────────────────────────────────────────────────────
function doSearch() {
const kw = searchInput.value.trim();
if (!kw) {
showEmpty();
return;
}
// 重置状态
currentKeyword = kw;
currentOffset = 0;
hasMore = true;
totalCount = 0;
accumulatedArticles = [];
resultsGrid.innerHTML = '';
document.getElementById('layeredBanner').style.display = 'none';
document.getElementById('emptyGuidance').style.display = 'none';
setLoading(true);
updateUI();
fetchArticles(kw, 0, false)
.then(articles => {
if (!articles || articles.length === 0) {
// 尝试兜底搜索
fetchArticles(kw.slice(0,2) || 'AI', 0, false).then(function(fallback) {
showEnhancedEmpty(kw, fallback || []);
}).catch(function() {
showEnhancedEmpty(kw, []);
});
setLoading(false);
return;
}
// 客户端评分排序（相关性优先、同分按阅读量降序）
articles.sort(function(a, b) {
var sd = calculateScore(kw, b) - calculateScore(kw, a);
if (sd !== 0) return sd;
return (b.readCount || b.clicksCount || 0) - (a.readCount || a.clicksCount || 0);
});
accumulatedArticles = articles;
currentOffset = articles.length;
renderArticles(articles, false);
setLoading(false);
updateUI();
showLayeredBanner(articles.length, kw);
searchInfo.textContent = '关键词 "' + kw + '" · 已加载 ' + articles.length + ' 条 (按综合评分排序)';
})
.catch(err => {
showError('搜索失败: ' + err.message);
});
}
function loadMore() {
if (isLoading || !hasMore) return;
setLoading(true);
fetchArticles(currentKeyword, currentOffset, true)
.then(articles => {
if (!articles || articles.length === 0) {
hasMore = false;
setLoading(false);
updateUI();
return;
}
accumulatedArticles = accumulatedArticles.concat(articles);
currentOffset += articles.length;
renderArticles(articles, true);
setLoading(false);
updateUI();
searchInfo.textContent = `关键词 "${currentKeyword}" · 已加载 ${accumulatedArticles.length} 条 (按综合评分排序)`;
})
.catch(err => {
showError('加载失败: ' + err.message);
});
}
function showEmpty() {
resultsGrid.innerHTML = '';
statusMsg.style.display = 'none';
emptyMsg.style.display = 'block';
loadMoreBar.style.display = 'none';
statTotal.textContent = '0';
statLoaded.textContent = '0';
}
// ─── 防抖搜索 ─────────────────────────────────────────────────────────────────
let debounceTimer;
searchInput.addEventListener('input', function() {
clearTimeout(debounceTimer);
debounceTimer = setTimeout(doSearch, 300);
});
searchInput.addEventListener('keydown', function(e) {
if (e.key === 'Enter') {
clearTimeout(debounceTimer);
doSearch();
}
});
// ─── 初始化 ───────────────────────────────────────────────────────────────────
function init() {
if (INITIAL_DATA && INITIAL_DATA.length > 0) {
accumulatedArticles = INITIAL_DATA;
currentOffset = INITIAL_DATA.length;
totalCount = INITIAL_DATA.length;
renderArticles(INITIAL_DATA, false);
updateUI();
searchInfo.textContent = `初始结果 · 共 ${INITIAL_DATA.length} 条 (按综合评分排序) | 输入新关键词自动搜索`;
// 初始数据加载后，hasMore 取决于 API 返回，此处设为可能有更多
statusMsg.style.display = 'none';
} else {
showEmpty();
searchInfo.textContent = '输入关键词开始搜索公众号文章';
}
}
init();
</script>
</body>
</html>
#!/usr/bin/env python3
"""
公众号搜索爬虫 — 关键字搜索微信公众号文章
=========================================
输入关键词，实时搜索公众号文章，终端表格展示，
自动导出 CSV + 生成带搜索框的交互式 HTML 报告。
Usage:
python3 search.py "人工智能"
python3 search.py "AI" --count 30
python3 search.py "大模型" --csv-only
"""
import argparse
import csv
import json
import os
import subprocess
import sys
import time
import threading
from datetime import datetime, timedelta
from http.server import HTTPServer, SimpleHTTPRequestHandler
from pathlib import Path
from urllib.parse import urlparse, parse_qs
try:
import requests
HAS_REQUESTS = True
except ImportError:
HAS_REQUESTS = False
# ─── 配置 ─────────────────────────────────────────────────────────────────────────
API_URL = "https://redfox.hk/story/api/gzhData/searchArticle"
CONFIG_DIR = Path.home() / ".qoder" / "apis"
CONFIG_FILE = CONFIG_DIR / "redfox.json"
ENV_KEY = "REDFOX_API_KEY"
SOURCE = "公众号搜索爬虫-GitHub"
DEFAULT_OUTPUT_DIR = Path.home() / "Downloads" / "QoderGzhSearch"
DEFAULT_COUNT = 100
DEFAULT_PORT = 8766
# ─── 终端颜色 ──────────────────────────────────────────────────────────────────────
GREEN = "\033[92m"
YELLOW = "\033[93m"
RED = "\033[91m"
CYAN = "\033[96m"
BOLD = "\033[1m"
RESET = "\033[0m"
def info(msg):
print(f"{GREEN}[✓]{RESET} {msg}")
def warn(msg):
print(f"{YELLOW}[!]{RESET} {msg}")
def error(msg):
print(f"{RED}[✗]{RESET} {msg}")
def step(msg):
print(f"{CYAN}[→]{RESET} {msg}")
# ─── API Key 管理 ──────────────────────────────────────────────────────────────────
def get_api_key(cli_key=None):
if cli_key:
return cli_key
env_key = os.environ.get(ENV_KEY)
if env_key:
return env_key
if CONFIG_FILE.exists():
try:
data = json.loads(CONFIG_FILE.read_text())
key = data.get("api_key")
if key:
return key
except (json.JSONDecodeError, OSError):
pass
return None
# ─── 字段兼容（新旧 API 格式）───────────────────────────────────────────────────────
def _reads(a):
return a.get("readCount") or a.get("clicksCount") or 0
def _likes(a):
return a.get("likeCount") or 0
def _shares(a):
return a.get("shareCount") or 0
def _collects(a):
return a.get("collectCount") or 0
def _url(a):
return a.get("workUrl") or a.get("url") or ""
def _uid(a):
return a.get("workUuid") or a.get("uuid") or ""
def _pub_time(a):
return a.get("publishTime") or a.get("publicTime") or ""
def _cover(a):
return a.get("coverUrl") or ""
def _title(a):
return a.get("title") or "无标题"
def _author(a):
return a.get("author") or "-"
def _summary(a):
return a.get("summary") or ""
def _account_type(a):
return a.get("accountType") or ""
# ─── 数据获取 ──────────────────────────────────────────────────────────────────────
def fetch_articles_batch(session, keyword, offset=0, sort_type="default"):
payload = {
"keyword": keyword,
"offset": offset,
"sortType": sort_type,
"source": SOURCE,
}
try:
resp = session.post(API_URL, json=payload, timeout=15)
result = resp.json()
except Exception as e:
error(f"请求失败: {e}")
return None
code = result.get("code")
if code == 3108:
warn("限频，等待 5s 后重试...")
time.sleep(5)
try:
resp = session.post(API_URL, json=payload, timeout=15)
result = resp.json()
code = result.get("code")
except Exception:
return None
if code not in (200, 2000):
if code in (3106, 3107):
error(f"API Key 错误 (code {code}): {result.get('msg', '')}")
else:
error(f"API 返回错误 (code {code}): {result.get('msg', '')}")
return None
data = result.get("data", {})
articles = data.get("list", [])
has_more = data.get("hasMore", 0)
return {"articles": articles, "hasMore": has_more}
def fetch_articles(session, keyword, max_count=100, sort_type="default"):
all_articles = []
seen_ids = set()
offset = 0
has_more = True
batch_count = 0
while len(all_articles) < max_count and has_more and batch_count < 5:
batch = fetch_articles_batch(session, keyword, offset=offset, sort_type=sort_type)
if batch is None:
break
batch_count += 1
new_count = 0
for article in batch["articles"]:
pid = _uid(article)
if pid and pid not in seen_ids:
seen_ids.add(pid)
all_articles.append(article)
new_count += 1
has_more = batch["hasMore"] == 1
offset += len(batch["articles"])
if new_count == 0:
break
if len(all_articles) < max_count:
time.sleep(0.3)
return {"articles": all_articles[:max_count], "hasMore": 1 if (has_more or len(all_articles) >= max_count) else 0}
def fetch_fallback_articles(session, keyword):
"""零结果时用宽泛词 + 热门词兜底搜索"""
candidates = set()
if len(keyword) >= 2:
candidates.add(keyword[:2])
if len(keyword) >= 1:
candidates.add(keyword[:1])
candidates.add("AI")
candidates.discard(keyword)
for broad_kw in sorted(candidates, key=len, reverse=True):
r = fetch_articles(session, broad_kw, max_count=10)
if r and r["articles"]:
return r["articles"]
return []
def format_number(n):
if n is None:
return "0"
if n >= 10000:
return f"{n/10000:.1f}w"
if n >= 1000:
return f"{n/1000:.1f}k"
return str(n)
# ─── 三因子评分 ────────────────────────────────────────────────────────────────────
def score_relevance(keyword, article):
"""相关性得分 0-10：关键词在标题 > 摘要中的命中情况"""
kw = keyword.lower().strip()
title = (_title(article) or "").lower()
summary = (_summary(article) or "").lower()
if not kw:
return 5.0
if kw == title:
return 10.0
if title.startswith(kw):
return 9.0
if kw in title:
return 8.0
words = [w for w in kw.split() if len(w) >= 2]
title_matches = sum(1 for w in words if w in title)
if title_matches >= len(words) * 0.5 and len(words) >= 2:
return 6.0
if summary and kw in summary[:len(summary)//3]:
return 5.0
if summary and kw in summary:
return 4.0
if title_matches > 0:
return 3.0
if summary and any(w in summary for w in words):
return 2.0
return 1.0
def score_heat(article):
"""热度得分 0.5-3.0：基于阅读数"""
r = _reads(article)
if r >= 100000: return 3.0
if r >= 50000: return 2.5
if r >= 10000: return 2.0
if r >= 5000: return 1.5
if r >= 1000: return 1.0
return 0.5
def score_freshness(article):
"""时效得分 0-2.0：基于发布时间"""
pt = _pub_time(article)
if not pt:
return 0
try:
pub_dt = datetime.fromisoformat(pt[:19])
days = (datetime.now() - pub_dt).days
if days <= 7: return 2.0
if days <= 15: return 1.5
if days <= 30: return 1.0
if days <= 60: return 0.5
return 0
except Exception:
return 0
def calculate_score(keyword, article):
"""综合评分 = 相关性 + 热度 + 时效（满分 15）"""
return score_relevance(keyword, article) + score_heat(article) + score_freshness(article)
# ─── 终端表格 ──────────────────────────────────────────────────────────────────────
def print_terminal_table(articles, keyword):
if not articles:
print(f"\n{YELLOW}[✗] 关键词 \"{keyword}\" 暂无搜索结果{RESET}")
return
count = len(articles)
print(f"\n{BOLD}{'=' * 120}{RESET}")
print(f"{BOLD} 公众号搜索爬虫 · \"{keyword}\" · 共 {count} 条结果{RESET}")
print(f"{BOLD}{'=' * 120}{RESET}")
header = (f" {'序号':<4}{'标题':<26}{'作者':<12}"
f"{'阅读':>7}{'点赞':>5}{'分享':>5}{'收藏':>5}{'发布时间':<12}{'文章链接':<36}")
print(f" {YELLOW}{'─' * 112}{RESET}")
print(f" {YELLOW}{header}{RESET}")
print(f" {YELLOW}{'─' * 112}{RESET}")
for i, a in enumerate(articles, 1):
title = _title(a)
author = _author(a)
reads = format_number(_reads(a))
likes = format_number(_likes(a))
shares = format_number(_shares(a))
collects = format_number(_collects(a))
pub_time = _pub_time(a)[:10] if _pub_time(a) else ""
link = _url(a)
display_title = title[:24] + ".." if len(title) > 26 else title
display_author = author[:10] + ".." if len(author) > 12 else author
display_link = link[:34] + ".." if len(link) > 36 else link
print(f" {i:<4}{display_title:<26}{display_author:<12}"
f"{reads:>7}{likes:>5}{shares:>5}{collects:>5}{pub_time:<12}{display_link:<36}")
print(f" {YELLOW}{'─' * 112}{RESET}")
# 分层提示
if count <= 2:
print(f" {YELLOW}💡 相关结果较少 (仅 {count} 条)，建议尝试更短或更宽泛的关键词{RESET}")
elif count <= 9:
print(f" {YELLOW}💡 仅找到 {count} 条结果，以下为您展示全部{RESET}")
print()
# ─── CSV 导出 ──────────────────────────────────────────────────────────────────────
def export_csv(articles, keyword, output_dir):
output_dir = Path(output_dir)
output_dir.mkdir(parents=True, exist_ok=True)
date_str = datetime.now().strftime("%Y-%m-%d")
filename = f"公众号搜索_{keyword}_{date_str}.csv"
filepath = output_dir / filename
fieldnames = ["标题", "作者", "阅读数", "点赞数", "分享数", "收藏数",
"发布时间", "文章链接", "摘要", "公众号分类"]
with open(filepath, "w", newline="", encoding="utf-8-sig") as f:
writer = csv.DictWriter(f, fieldnames=fieldnames)
writer.writeheader()
for a in articles:
writer.writerow({
"标题": _title(a),
"作者": _author(a),
"阅读数": _reads(a),
"点赞数": _likes(a),
"分享数": _shares(a),
"收藏数": _collects(a),
"发布时间": _pub_time(a),
"文章链接": _url(a),
"摘要": _summary(a),
"公众号分类": _account_type(a),
})
return filepath
# ─── HTML 报告生成 ─────────────────────────────────────────────────────────────────
def generate_html(articles, keyword, api_key):
template_path = Path(__file__).parent / "report_template.html"
if template_path.exists():
template = template_path.read_text(encoding="utf-8")
else:
template = get_fallback_template()
date_str = datetime.now().strftime("%Y-%m-%d")
timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
initial_data = json.dumps(articles, ensure_ascii=False)
html = template
html = html.replace("{{KEYWORD}}", keyword)
html = html.replace("{{DATE}}", date_str)
html = html.replace("{{TIMESTAMP}}", timestamp)
html = html.replace("{{TOTAL_COUNT}}", str(len(articles)))
html = html.replace("{{INITIAL_DATA}}", initial_data)
html = html.replace("{{API_KEY}}", api_key)
html = html.replace("{{API_URL}}", API_URL)
html = html.replace("{{SOURCE}}", SOURCE)
return html
def get_fallback_template():
return '''<!DOCTYPE html>
<html lang="zh-CN">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>公众号搜索 - {{KEYWORD}} | {{DATE}}</title>
<style>
* { margin: 0; padding: 0; box-sizing: border-box; }
:root {
--bg: #0a0f0a; --bg-card: #141f14; --bg-card-hover: #1a2a1a;
--text: #e8efe8; --text-secondary: #8a9a8a; --text-muted: #556655;
--accent: #2ECC71; --accent-glow: rgba(46,204,113,0.12);
--accent-border: rgba(46,204,113,0.25);
--border: rgba(255,255,255,0.05);
--font: 'Space Grotesk', -apple-system, sans-serif;
--radius: 12px; --radius-sm: 8px;
}
body {
font-family: var(--font); background: var(--bg);
color: var(--text); min-height: 100vh;
}
.main-header {
text-align: center; padding: 2.5rem 1.5rem 1.5rem;
max-width: 900px; margin: 0 auto; position: relative;
}
.main-header::after {
content: ''; position: absolute; bottom: 0; left: 50%;
transform: translateX(-50%); width: 60px; height: 2px;
background: var(--accent); opacity: 0.5;
}
.main-header h1 { font-size: 1.6rem; font-weight: 700; color: var(--accent); }
.main-header .subtitle { color: var(--text-secondary); font-size: 0.85rem; margin-top: 0.3rem; }
.stats-bar {
display: flex; justify-content: center; gap: 2rem;
padding: 1rem; max-width: 600px; margin: 0 auto; flex-wrap: wrap;
}
.stat-item { text-align: center; }
.stat-value { font-size: 1.2rem; font-weight: 700; color: var(--accent); }
.stat-label { font-size: 0.7rem; color: var(--text-muted); text-transform: uppercase; }
.search-container {
position: sticky; top: 0; z-index: 100;
background: linear-gradient(180deg, var(--bg) 80%, transparent);
padding: 1rem 1.5rem 1.5rem; backdrop-filter: blur(12px);
}
.search-wrapper {
max-width: 640px; margin: 0 auto; display: flex; gap: 0.6rem;
}
.search-input {
flex: 1; padding: 0.75rem 1.2rem;
border: 1.5px solid var(--border); border-radius: var(--radius);
background: #0f1a0f; color: var(--text); font-size: 0.95rem;
font-family: var(--font); outline: none;
transition: all 0.2s cubic-bezier(0.16,1,0.3,1);
}
.search-input:focus { border-color: var(--accent); box-shadow: 0 0 0 3px var(--accent-glow); }
.search-input::placeholder { color: var(--text-muted); }
.search-info { margin-top: 0.6rem; text-align: center; font-size: 0.75rem; color: var(--text-muted); }
.results-container { max-width: 900px; margin: 0 auto; padding: 0.5rem 1.5rem 2rem; }
.results-grid { display: flex; flex-direction: column; gap: 0.5rem; }
.article-card {
display: flex; align-items: flex-start; gap: 0.9rem;
padding: 0.9rem 1rem; background: var(--bg-card);
border: 1px solid var(--border); border-radius: var(--radius-sm);
cursor: pointer; text-decoration: none; color: inherit;
transition: all 0.15s cubic-bezier(0.16,1,0.3,1);
}
.article-card:hover {
background: var(--bg-card-hover); border-color: var(--accent-border);
transform: translateX(2px);
}
.card-avatar {
width: 48px; height: 48px; min-width: 48px;
border-radius: var(--radius-sm); overflow: hidden;
background: var(--accent-glow); border: 1px solid var(--accent-border);
display: flex; align-items: center; justify-content: center;
font-size: 1rem; font-weight: 700; color: var(--accent);
user-select: none;
}
.card-avatar img {
width: 100%; height: 100%; object-fit: cover;
}
.card-content { flex: 1; min-width: 0; }
.card-title {
font-size: 0.92rem; font-weight: 500; line-height: 1.45;
margin-bottom: 0.35rem;
display: -webkit-box; -webkit-line-clamp: 2; -webkit-box-orient: vertical; overflow: hidden;
}
.card-meta {
display: flex; flex-wrap: wrap; align-items: center; gap: 0.5rem 1rem;
font-size: 0.75rem; color: var(--text-secondary);
}
.card-meta .author { color: #58D68D; font-weight: 500; max-width: 120px; overflow: hidden; text-overflow: ellipsis; white-space: nowrap; }
.card-meta .pub-time { color: var(--text-muted); margin-left: auto; }
.status-message { text-align: center; padding: 3rem 1rem; color: var(--text-secondary); font-size: 0.9rem; }
.load-more-bar { display: flex; justify-content: center; padding: 1.5rem 1rem 3rem; }
.load-more-btn {
padding: 0.65rem 2.2rem; border: 1.5px solid var(--border);
border-radius: var(--radius); background: var(--bg-card);
color: var(--text-secondary); font-size: 0.85rem;
font-family: var(--font); cursor: pointer;
transition: all 0.2s cubic-bezier(0.16,1,0.3,1);
}
.load-more-btn:hover { border-color: var(--accent-border); color: var(--accent); }
.load-more-btn:disabled { opacity: 0.4; cursor: not-allowed; }
.footer {
text-align: center; padding: 2rem 1rem; color: var(--text-muted);
font-size: 0.72rem; border-top: 1px solid var(--border);
max-width: 900px; margin: 0 auto;
}
@keyframes fadeInUp {
from { opacity: 0; transform: translateY(8px); }
to { opacity: 1; transform: translateY(0); }
}
.article-card { animation: fadeInUp 0.3s cubic-bezier(0.16,1,0.3,1) both; }
.article-card:nth-child(1){animation-delay:0s}.article-card:nth-child(2){animation-delay:.03s}
.article-card:nth-child(3){animation-delay:.06s}.article-card:nth-child(4){animation-delay:.09s}
.article-card:nth-child(5){animation-delay:.12s}.article-card:nth-child(6){animation-delay:.15s}
.article-card:nth-child(7){animation-delay:.18s}.article-card:nth-child(8){animation-delay:.21s}
.article-card:nth-child(9){animation-delay:.24s}.article-card:nth-child(10){animation-delay:.27s}
.article-card:nth-child(n+11){animation-delay:.30s}
@media (max-width: 640px) {
.main-header { padding: 1.5rem 1rem 1rem; }
.article-card { padding: 0.75rem 0.8rem; gap: 0.7rem; }
.card-title { font-size: 0.85rem; }
.card-meta { font-size: 0.7rem; gap: 0.4rem 0.6rem; }
.card-meta .pub-time { margin-left: 0; }
.stats-bar { gap: 1.2rem; }
}
</style>
<link href="https://fonts.googleapis.com/css2?family=Space+Grotesk:wght@300;400;500;600;700&display=swap" rel="stylesheet">
</head>
<body>
<div class="main-header"><h1>公众号搜索爬虫</h1><p class="subtitle">{{DATE}} | 输入关键词实时搜索微信公众号文章</p></div>
<div class="stats-bar">
<div class="stat-item"><div class="stat-value" id="statTotal">{{TOTAL_COUNT}}</div><div class="stat-label">结果总数</div></div>
<div class="stat-item"><div class="stat-value" id="statKeyword">{{KEYWORD}}</div><div class="stat-label">当前关键词</div></div>
<div class="stat-item"><div class="stat-value" id="statLoaded">{{TOTAL_COUNT}}</div><div class="stat-label">已加载</div></div>
</div>
<div class="search-container">
<div class="search-wrapper">
<input type="text" class="search-input" id="searchInput"
placeholder="输入关键词搜索公众号文章..." value="{{KEYWORD}}" autofocus>
</div>
<div class="search-info" id="searchInfo">输入关键词后自动搜索（300ms 防抖）| 点击文章跳转原文阅读</div>
</div>
<main class="results-container">
<div class="results-grid" id="resultsGrid"></div>
<div class="status-message" id="statusMsg" style="display:none">搜索中...</div>
<div class="status-message" id="emptyMsg" style="display:none;color:var(--text-muted)">暂无搜索结果，请尝试其他关键词</div>
<div class="load-more-bar" id="loadMoreBar" style="display:none">
<button class="load-more-btn" id="loadMoreBtn" onclick="loadMore()">加载更多结果</button>
</div>
</main>
<footer class="footer">Generated at {{TIMESTAMP}} by 公众号搜索 Skill | Powered by redfox.hk</footer>
<script>
const API_URL = '{{API_URL}}';
const API_KEY = '{{API_KEY}}';
const SOURCE = '{{SOURCE}}';
const INITIAL_DATA = {{INITIAL_DATA}};
let currentKeyword = '{{KEYWORD}}';
let currentOffset = 0;
let hasMore = true;
let totalCount = {{TOTAL_COUNT}};
let isLoading = false;
let accumulatedArticles = [];
const resultsGrid = document.getElementById('resultsGrid');
const statusMsg = document.getElementById('statusMsg');
const emptyMsg = document.getElementById('emptyMsg');
const loadMoreBar = document.getElementById('loadMoreBar');
const loadMoreBtn = document.getElementById('loadMoreBtn');
const searchInput = document.getElementById('searchInput');
const searchInfo = document.getElementById('searchInfo');
const statTotal = document.getElementById('statTotal');
const statLoaded = document.getElementById('statLoaded');
const statKeyword = document.getElementById('statKeyword');
function formatNum(n) {
if (n == null || n === undefined) return '0';
n = Number(n);
if (isNaN(n)) return '0';
if (n >= 10000) return (n/10000).toFixed(1)+'w';
if (n >= 1000) return (n/1000).toFixed(1)+'k';
return String(n);
}
function escapeHTML(str) {
const div = document.createElement('div');
div.textContent = str || '';
return div.innerHTML;
}
function getArticleUrl(a) { return a.workUrl || a.url || '#'; }
function getCoverUrl(a) { return a.coverUrl || ''; }
function getReadCount(a) { return a.readCount || a.clicksCount || 0; }
function getPubTime(a) { return (a.publishTime || a.publicTime || '').slice(0,10); }
function renderArticleCard(article) {
const title = article.title || '无标题';
const author = article.author || '未知作者';
const reads = formatNum(getReadCount(article));
const likes = formatNum(article.likeCount);
const shares = formatNum(article.shareCount);
const collects = formatNum(article.collectCount);
const pubTime = getPubTime(article);
const url = getArticleUrl(article);
const cover = getCoverUrl(article);
const card = document.createElement('a');
card.className = 'article-card';
card.href = url;
card.target = '_blank';
card.rel = 'noopener noreferrer';
let avatarHTML;
if (cover) {
avatarHTML = '<img src="'+cover+'" alt="" loading="lazy">';
} else {
const ch = (title.replace(/[^\\w\\u4e00-\\u9fff]/g,'').trim().charAt(0)||'文');
avatarHTML = escapeHTML(ch);
}
card.innerHTML = '<div class="card-avatar">'+avatarHTML+'</div>' +
'<div class="card-content">' +
'<div class="card-title">'+escapeHTML(title)+'</div>' +
'<div class="card-meta">' +
'<span class="author" title="'+escapeHTML(author)+'">'+escapeHTML(author)+'</span>' +
'<span>👁 '+reads+'</span>' +
'<span>👍 '+likes+'</span>' +
'<span>📤 '+shares+'</span>' +
'<span>⭐ '+collects+'</span>' +
(pubTime ? '<span class="pub-time">'+pubTime+'</span>' : '') +
'</div></div>';
return card;
}
function renderArticles(articles, append) {
if (!append) resultsGrid.innerHTML = '';
articles.forEach(a => resultsGrid.appendChild(renderArticleCard(a)));
}
function updateUI() {
statTotal.textContent = totalCount || accumulatedArticles.length;
statLoaded.textContent = accumulatedArticles.length;
statKeyword.textContent = currentKeyword || '-';
loadMoreBar.style.display = hasMore ? 'flex' : 'none';
}
function setLoading(loading) {
isLoading = loading;
statusMsg.style.display = loading ? 'block' : 'none';
emptyMsg.style.display = 'none';
loadMoreBtn.disabled = loading;
}
function fetchArticlesFromAPI(keyword, offset) {
return fetch(API_URL, {
method: 'POST',
headers: {'Content-Type':'application/json','X-API-KEY':API_KEY},
body: JSON.stringify({keyword,offset,sortType:'default',source:SOURCE})
}).then(r => r.json()).then(res => {
if (res.code===200||res.code===2000) {
const list = res.data.list||[];
hasMore = res.data.hasMore===1;
return list;
} else {
throw new Error(res.msg||'API error');
}
});
}
function doSearch() {
const kw = searchInput.value.trim();
if (!kw) { showEmpty(); return; }
currentKeyword = kw;
currentOffset = 0;
hasMore = true;
totalCount = 0;
accumulatedArticles = [];
resultsGrid.innerHTML = '';
setLoading(true);
updateUI();
fetchArticlesFromAPI(kw,0).then(list => {
if (!list||!list.length) { showEmpty(); return; }
accumulatedArticles = list;
currentOffset = list.length;
renderArticles(list, false);
setLoading(false);
updateUI();
searchInfo.textContent = '关键词 "'+kw+'" · 已加载 '+list.length+' 条结果';
}).catch(e => {
statusMsg.style.display='block'; statusMsg.textContent='搜索失败: '+e.message;
isLoading = false;
});
}
function loadMore() {
if (isLoading||!hasMore) return;
setLoading(true);
fetchArticlesFromAPI(currentKeyword,currentOffset).then(list => {
if (!list||!list.length) { hasMore=false; setLoading(false); updateUI(); return; }
accumulatedArticles = accumulatedArticles.concat(list);
currentOffset += list.length;
renderArticles(list, true);
setLoading(false);
updateUI();
searchInfo.textContent = '关键词 "'+currentKeyword+'" · 已加载 '+accumulatedArticles.length+' 条结果';
}).catch(e => {
statusMsg.style.display='block'; statusMsg.textContent='加载失败: '+e.message;
isLoading = false;
});
}
function showEmpty() {
resultsGrid.innerHTML = '';
statusMsg.style.display='none';
emptyMsg.style.display='block';
loadMoreBar.style.display='none';
statTotal.textContent='0'; statLoaded.textContent='0';
}
let debounceTimer;
searchInput.addEventListener('input',function() {
clearTimeout(debounceTimer);
debounceTimer = setTimeout(doSearch,300);
});
searchInput.addEventListener('keydown',function(e) {
if (e.key==='Enter') { clearTimeout(debounceTimer); doSearch(); }
});
function init() {
if (INITIAL_DATA && INITIAL_DATA.length>0) {
accumulatedArticles = INITIAL_DATA;
currentOffset = INITIAL_DATA.length;
totalCount = INITIAL_DATA.length;
renderArticles(INITIAL_DATA, false);
updateUI();
statusMsg.style.display='none';
searchInfo.textContent = '初始结果 · 共 '+INITIAL_DATA.length+' 条 | 输入新关键词自动搜索';
} else {
showEmpty();
searchInfo.textContent = '输入关键词开始搜索公众号文章';
}
}
init();
</script>
</body>
</html>'''
# ─── API 代理 HTTP 服务 ─────────────────────────────────────────────────────────────
class ProxyHTTPHandler(SimpleHTTPRequestHandler):
api_key = None
def do_GET(self):
parsed = urlparse(self.path)
if parsed.path == "/api/search":
self._handle_search(parsed)
else:
super().do_GET()
def do_POST(self):
parsed = urlparse(self.path)
if parsed.path == "/api/search":
self._handle_search_post()
else:
self.send_error(404)
def _handle_search(self, parsed):
params = parse_qs(parsed.query)
keyword = params.get("keyword", [""])[0]
offset = int(params.get("offset", ["0"])[0])
sort_type = params.get("sortType", ["default"])[0]
if not keyword:
self._send_json({"code": -1, "msg": "missing keyword"})
return
self._do_proxy_request({"keyword": keyword, "offset": offset, "sortType": sort_type, "source": SOURCE})
def _handle_search_post(self):
content_length = int(self.headers.get("Content-Length", 0))
body = self.rfile.read(content_length) if content_length else b"{}"
try:
req_data = json.loads(body)
except json.JSONDecodeError:
self._send_json({"code": -1, "msg": "invalid json"})
return
keyword = req_data.get("keyword", "")
offset = req_data.get("offset", 0)
sort_type = req_data.get("sortType", "default")
if not keyword:
self._send_json({"code": -1, "msg": "missing keyword"})
return
self._do_proxy_request({"keyword": keyword, "offset": offset, "sortType": sort_type, "source": SOURCE})
def _do_proxy_request(self, payload):
try:
resp = requests.post(API_URL, json=payload,
headers={"Content-Type": "application/json", "X-API-KEY": self.api_key}, timeout=15)
self._send_json(resp.json())
except Exception as e:
self._send_json({"code": -1, "msg": str(e)})
def _send_json(self, data):
body = json.dumps(data, ensure_ascii=False).encode("utf-8")
self.send_response(200)
self.send_header("Content-Type", "application/json; charset=utf-8")
self.send_header("Access-Control-Allow-Origin", "*")
self.send_header("Content-Length", str(len(body)))
self.end_headers()
self.wfile.write(body)
def do_OPTIONS(self):
self.send_response(204)
self.send_header("Access-Control-Allow-Origin", "*")
self.send_header("Access-Control-Allow-Methods", "GET, POST, OPTIONS")
self.send_header("Access-Control-Allow-Headers", "Content-Type, X-API-KEY")
self.end_headers()
def log_message(self, format, *args):
pass
def start_server(output_dir, api_key, port=8766):
ProxyHTTPHandler.api_key = api_key
os.chdir(str(output_dir))
server = HTTPServer(("127.0.0.1", port), ProxyHTTPHandler)
t = threading.Thread(target=server.serve_forever, daemon=True)
t.start()
info(f"本地服务已启动: http://127.0.0.1:{port}")
return server
# ─── 主流程 ────────────────────────────────────────────────────────────────────────
def main():
parser = argparse.ArgumentParser(
description="公众号搜索爬虫 — 关键字搜索微信公众号文章",
formatter_class=argparse.RawDescriptionHelpFormatter,
epilog="""
Examples:
python3 search.py "人工智能"
python3 search.py "AI Agent" --count 30
python3 search.py "大模型" --csv-only
python3 search.py "AI" --no-open --output-dir ~/Desktop
""",
)
parser.add_argument("keyword", nargs="?", default="", help="搜索关键词（必填）")
parser.add_argument("--count", type=int, default=DEFAULT_COUNT, help=f"获取文章数量 (默认: {DEFAULT_COUNT})")
parser.add_argument("--sort-type", default="default", help="排序方式: default / time (默认: default)")
parser.add_argument("--output-dir", help=f"输出目录 (默认: ~/Downloads/QoderGzhSearch)")
parser.add_argument("--api-key", help="API Key")
parser.add_argument("--no-open", action="store_true", help="不自动打开浏览器")
parser.add_argument("--csv-only", action="store_true", help="仅生成 CSV 文件")
parser.add_argument("--port", type=int, default=DEFAULT_PORT, help=f"HTTP 服务端口 (默认: {DEFAULT_PORT})")
args = parser.parse_args()
banner = f"""{CYAN}{BOLD}
╔══════════════════════════════════════════╗
║ 公众号搜索爬虫 · GZH Crawler ║
║ 关键词查询 · 数据导出 · 交互报告 ║
╚══════════════════════════════════════════╝{RESET}
"""
print(banner)
if not HAS_REQUESTS:
error("缺少 requests 库，请安装: pip3 install requests")
sys.exit(1)
api_key = get_api_key(cli_key=args.api_key)
if not api_key:
print(f"{RED}╔══════════════════════════════════════════════════╗{RESET}")
print(f"{RED}║ 未配置 API Key，请通过以下方式之一配置： ║{RESET}")
print(f"{RED}║ ║{RESET}")
print(f"{RED}║ export REDFOX_API_KEY=ak_你的密钥 ║{RESET}")
print(f"{RED}║ python3 search.py --api-key ak_你的密钥 ║{RESET}")
print(RED + "║ echo '{\"api_key\":\"ak_你的密钥\"}' > ~/.qoder/apis/redfox.json ║" + RESET)
print(f"{RED}║ ║{RESET}")
print(f"{RED}║ 注册获取 Key: https://redfox.hk/settings/api-keys ║{RESET}")
print(f"{RED}╚══════════════════════════════════════════════════╝{RESET}")
sys.exit(1)
if not args.keyword:
try:
args.keyword = input(f"{CYAN}请输入搜索关键词: {RESET}").strip()
except (EOFError, KeyboardInterrupt):
print()
sys.exit(0)
if not args.keyword:
error("搜索关键词不能为空")
sys.exit(1)
keyword = args.keyword
if len(keyword) > 10:
error(f"关键词长度不能超过 10 个字符（当前 {len(keyword)} 个），请精简后重试")
sys.exit(1)
max_count = args.count
sort_type = args.sort_type
output_dir = args.output_dir or str(DEFAULT_OUTPUT_DIR)
output_dir = os.path.expanduser(output_dir)
session = requests.Session()
session.headers.update({"Content-Type": "application/json", "X-API-KEY": api_key})
step(f"搜索关键词: \"{keyword}\" (最多 {max_count} 条)...")
result = fetch_articles(session, keyword, max_count=max_count, sort_type=sort_type)
if result is None:
error("搜索失败，请检查网络或 API Key")
sys.exit(1)
articles = result["articles"]
has_more = result["hasMore"]
# ── 客户端排序（相关性优先、同分按阅读量降序）──
if articles:
articles.sort(key=lambda a: (calculate_score(keyword, a), _reads(a)), reverse=True)
# ── 零结果处理 ──
if not articles:
print(f"\n{YELLOW}[✗] 抱歉，未找到与「{BOLD}{keyword}{RESET}{YELLOW}」直接相关的内容{RESET}\n")
step("尝试搜索热门内容...")
fallback = fetch_fallback_articles(session, keyword)
if fallback:
fallback.sort(key=lambda a: (calculate_score("", a), _reads(a)), reverse=True)
info(f"为您推荐 {len(fallback)} 篇热门文章（非直接相关）：")
print_terminal_table(fallback, keyword)
articles = fallback
else:
print(f" {YELLOW}建议:{RESET} 尝试更短的关键词（如「{keyword[:2] if len(keyword)>=2 else 'AI'}」）")
print(f" {YELLOW}建议:{RESET} 使用英文关键词重试")
warn("如需搜索全量公众号内容，请访问 https://redfox.hk/settings/api-keys?source=github")
sys.exit(0)
# 表格展示（有结果时）
if articles:
print_terminal_table(articles, keyword)
reads_list = [_reads(a) for a in articles]
total_reads = sum(reads_list)
max_reads = max(reads_list) if reads_list else 0
print(f" {BOLD}统计:{RESET} 共 {len(articles)} 条 (按综合评分排序) | 总阅读 {format_number(total_reads)} | "
f"最高阅读 {format_number(max_reads)} | {'还有更多数据' if has_more else '已加载全部'}")
step("导出 CSV ...")
csv_path = export_csv(articles, keyword, output_dir)
info(f"CSV 已保存: {csv_path}")
if not args.csv_only:
step("生成 HTML 报告 ...")
html_content = generate_html(articles, keyword, api_key)
date_str = datetime.now().strftime("%Y-%m-%d")
html_filename = f"公众号搜索_{keyword}_{date_str}.html"
html_dir = Path(output_dir)
html_dir.mkdir(parents=True, exist_ok=True)
html_path = html_dir / html_filename
html_path.write_text(html_content, encoding="utf-8")
info(f"HTML 报告已保存: {html_path}")
server = start_server(output_dir, api_key, args.port)
url = f"http://127.0.0.1:{args.port}/{html_filename}"
if not args.no_open:
step("打开浏览器...")
try:
subprocess.run(["open", url], check=True)
except Exception:
print(f" 请手动打开: {url}")
print(f"\n{GREEN}╔══════════════════════════════════════════════════╗{RESET}")
print(f"{GREEN}║ ✓ 搜索完成! HTML 报告: {url}{RESET}")
print(f"{GREEN}║ 按 Ctrl+C 停止本地服务 ║{RESET}")
print(f"{GREEN}╚══════════════════════════════════════════════════╝{RESET}\n")
try:
while True:
time.sleep(1)
except KeyboardInterrupt:
print(f"\n{YELLOW} [→] 服务已停止{RESET}")
else:
print(f"\n{GREEN}╔══════════════════════════════════════════════════╗{RESET}")
print(f"{GREEN}║ ✓ 搜索完成! CSV: {csv_path}{RESET}")
print(f"{GREEN}╚══════════════════════════════════════════════════╝{RESET}\n")
if __name__ == "__main__":
main()
WeChat Article Search Crawler / gzh-search-crawler
---
Overview
Search WeChat public account articles by keyword, display results in a terminal table, and auto-export CSV + interactive HTML reports.
Core Value
- Keyword Search: Real-time full-database search of verified public account articles from the past 30 days
- Smart Scoring: Three-factor ranking (relevance + popularity + recency)
- Multi-Format Output: Terminal table + CSV export + interactive HTML report
- Interactive Report: Built-in search box, cover image display, click-to-open original articles
Target Users
- 🔍 Industry Researchers — Track industry trends, batch export data for analysis
- 📝 Content Creators — Discover trending topics and creative inspiration
- 🏢 Competitive Analysts — Monitor competitor content strategies
---
Features
Core Features
- Keyword Search: Search by any keyword (max 10 characters), real-time results
- Smart Ranking: Three-factor scoring (relevance + popularity + recency), ties broken by reads
- Tiered Fallback: Ample results → normal browsing / fewer results → broader search / zero results → trending topics
- Terminal Table: Title, author, reads, likes, shares, favorites, publish date, article link
- CSV Export: Auto-generated UTF-8 BOM CSV for data analysis
- HTML Report: Built-in search (300ms debounce), cover display, paginated loading
---
API Key Acquisition & Security
- The skill uses the environment variable:
REDFOX_API_KEY. REDFOX_API_KEYis provided by RedFoxHub (https://redfox.hk).- Visit RedFoxHub to register and obtain your
REDFOX_API_KEY. - Configure the device environment variable
REDFOX_API_KEYbefore using this skill. - Before providing your key, verify its origin, scope, validity period, and whether reset/revocation is supported.
- Never hardcode or expose the key in code, prompts, logs, or output files.
---
Usage
Just say the keyword you want to search.
Quick Reference
| Intent | Example | Result |
|---|---|---|
| Hot search | "Search AI-related public account articles" | Returns trending AI articles, ranked by score |
| Competitor analysis | "Search recent articles on LLMs" | Captures competitor content, exports CSV for analysis |
| Inspiration | "Search trending articles on Xiaohongshu operations" | Gets topic angles and writing approaches |
| Trend research | "Search 2026 economy articles from public accounts" | Batch exports data for research reports |
---
Use Cases
| Scenario | Role | Example Query | Benefit |
|---|---|---|---|
| Industry tracking | Industry analyst | "What's being discussed in AI lately?" | Quick overview of industry trends |
| Competitor analysis | Content ops | "Search competitor public account articles" | Understand content strategy and viral patterns |
| Inspiration gathering | Creator | "Search trending topics on content creation" | Get track-aligned inspiration, boost efficiency |
| Trend research | Researcher | "Batch export articles on a specific topic" | CSV export for deep data analysis |
公众号搜索爬虫 / gzh-search-crawler
---
简介
输入关键词搜索微信公众号文章，终端表格展示并自动导出 CSV + 交互式 HTML 报告。
核心价值
- 关键词搜索：实时查询全量微信公众号文章，覆盖腰部以上公众号近 30 天内容
- 智能评分排序：综合关键词相关性、阅读热度、时效新鲜度三维评分
- 多格式输出：终端表格 + CSV 导出 + 交互式 HTML 报告，满足不同场景
- 交互式报告：HTML 页面内置搜索框，支持封面图展示、卡片点击跳转原文
适用对象
- 🔍 行业研究员 — 追踪行业热点，批量导出数据做趋势分析
- 📝 内容创作者 — 发现爆款选题，搜集素材灵感
- 🏢 竞品分析师 — 监控竞争对手公众号内容策略
---
功能特性
核心功能
- 关键词搜索：输入任意关键词（不超过 10 字），实时搜索公众号文章
- 智能排序：三维评分（相关性 + 热度 + 时效），同分按阅读量降序
- 分层降级：充足时正常浏览 / 较少时引导宽泛搜索 / 无结果时热门兜底
- 终端表格：标题、作者、阅读、点赞、分享、收藏、发布时间、文章链接
- CSV 导出：自动生成 UTF-8 BOM 编码 CSV，便于数据分析
- HTML 报告：内置搜索框（300ms 防抖），封面图展示，分页加载
---
密钥获取与安全说明
- 本技能需要使用环境变量：
REDFOX_API_KEY。 REDFOX_API_KEY由 红狐 hub (https://redfox.hk)提供。- 请前往 红狐 hub 注册账号，获取
REDFOX_API_KEY。 - 配置设备环境变量
REDFOX_API_KEY后使用本技能。 - 在提供密钥前，请先确认密钥来源、可用范围、有效期及是否支持重置/撤销。
- 禁止在代码、提示词、日志或输出文件中硬编码/明文暴露密钥。
---
使用指南
直接用自然语言说出你想搜的关键词即可。
常用说法速查
| 意图 | 示例话术 | 效果 |
|---|---|---|
| 搜索热点 | 「搜一下 AI 相关的公众号文章」 | 返回 AI 相关热门文章，按评分排序 |
| 竞品分析 | 「搜大模型方向最近的文章」 | 抓取竞品内容策略，导出 CSV 分析 |
| 素材搜集 | 「搜小红书运营的爆款文章」 | 获取同赛道选题和写作角度 |
| 趋势研究 | 「搜 2026 经济相关的公众号文章」 | 批量导出数据做研究报告 |
---
使用场景
| 场景 | 角色 | 示例问法 | 收益 |
|---|---|---|---|
| 行业热点追踪 | 行业分析师 | 「AI 领域最近在讨论什么？」 | 快速了解行业动态与讨论风向 |
| 竞品内容分析 | 内容运营 | 「搜一下竞品公众号的文章」 | 掌握竞品发文策略与爆款规律 |
| 素材灵感搜集 | 创作者 | 「搜小红书运营的爆款选题」 | 获取同赛道灵感，提升创作效率 |
| 趋势研究报告 | 研究员 | 「批量导出某话题的文章数据」 | CSV 导出，方便深度数据分析 |
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