1ab34fa450
热点抓取 → 选题 → 框架 → 写作 → SEO → 视觉AI → 排版 → 微信草稿箱， 一句话触发完整流程。适用于 Claude Code skill 格式。 Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
119 lines
3.8 KiB
Python
119 lines
3.8 KiB
Python
#!/usr/bin/env python3
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"""
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SEO keyword research tool.
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Queries real search data to evaluate keyword popularity:
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1. Baidu search suggestions (autocomplete volume proxy)
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2. Baidu related searches
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3. WeChat sogou index (search volume proxy)
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Usage:
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python3 seo_keywords.py "AI大模型"
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python3 seo_keywords.py "AI大模型" "科技股" "创业"
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python3 seo_keywords.py --json "AI大模型"
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Output: keyword popularity score, related keywords, trending signals.
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"""
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import argparse
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import json
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import sys
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import urllib.parse
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import requests
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TIMEOUT = 10
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HEADERS = {
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"User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) "
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"AppleWebKit/537.36 (KHTML, like Gecko) "
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"Chrome/120.0.0.0 Safari/537.36",
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}
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def baidu_suggestions(keyword: str) -> list[str]:
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"""Get Baidu search autocomplete suggestions — proxy for search volume."""
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try:
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resp = requests.get(
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"https://suggestion.baidu.com/su",
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params={"wd": keyword, "action": "opensearch", "ie": "utf-8"},
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headers=HEADERS,
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timeout=TIMEOUT,
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)
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data = resp.json()
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# Response format: [query, [suggestions...]]
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if isinstance(data, list) and len(data) >= 2:
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return data[1]
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return []
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except Exception as e:
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print(f"[warn] baidu suggestions failed: {e}", file=sys.stderr)
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return []
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def so360_suggestions(keyword: str) -> list[str]:
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"""Get 360 search suggestions — second source for search volume proxy."""
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try:
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resp = requests.get(
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"https://sug.so.360.cn/suggest",
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params={"word": keyword, "encodein": "utf-8", "encodeout": "utf-8", "format": "json"},
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headers=HEADERS,
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timeout=TIMEOUT,
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)
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data = resp.json()
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return [item.get("word", "") for item in data.get("result", []) if item.get("word")]
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except Exception as e:
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print(f"[warn] 360 suggestions failed: {e}", file=sys.stderr)
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return []
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def analyze_keyword(keyword: str) -> dict:
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"""Analyze a keyword's SEO potential."""
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baidu_suggs = baidu_suggestions(keyword)
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so360_suggs = so360_suggestions(keyword)
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# Popularity score (0-10) based on suggestion count
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# More suggestions = more search demand
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baidu_score = min(len(baidu_suggs), 10)
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so360_score = min(len(so360_suggs), 10)
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# Combined score: average of two sources
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combined_score = round((baidu_score + so360_score) / 2, 1)
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# Extract related keywords (dedup)
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all_related = list(dict.fromkeys(baidu_suggs + so360_suggs))
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return {
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"keyword": keyword,
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"seo_score": combined_score,
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"baidu_score": baidu_score,
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"so360_score": so360_score,
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"baidu_suggestions": baidu_suggs[:5],
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"so360_suggestions": so360_suggs[:5],
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"related_keywords": all_related[:10],
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}
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def main():
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parser = argparse.ArgumentParser(description="SEO keyword analysis")
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parser.add_argument("keywords", nargs="+", help="Keywords to analyze")
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parser.add_argument("--json", action="store_true", help="Output as JSON")
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args = parser.parse_args()
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results = []
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for kw in args.keywords:
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result = analyze_keyword(kw)
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results.append(result)
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if args.json:
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json.dump(results, sys.stdout, ensure_ascii=False, indent=2)
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else:
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for r in results:
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print(f"\n关键词: {r['keyword']}")
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print(f" 综合 SEO 评分: {r['seo_score']}/10（百度 {r['baidu_score']} + 360 {r['so360_score']}）")
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if r["so360_suggestions"]:
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print(f" 360热搜词: {', '.join(r['so360_suggestions'][:5])}")
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if r["related_keywords"]:
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print(f" 相关关键词: {', '.join(r['related_keywords'][:5])}")
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if __name__ == "__main__":
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main()
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