增长策略与激活：Surfer SEO AI优化

import json class SEOScorer:    def __init__(self, target_keywords, semantic_words):        self.target_keywords = target_keywords        self.semantic_words = semantic_words        self.weights = {'keyword_density': 0.3, 'semantic_coverage': 0.25,                        'structure': 0.2, 'readability': 0.15, 'length': 0.1}        def analyze_content(self, content, headings, word_count):        scores = {}        scores['keyword_density'] = self._score_keyword_density(content)        scores['semantic_coverage'] = self._score_semantic(content)        scores['structure'] = self._score_structure(headings)        scores['readability'] = self._score_readability(content)        scores['length'] = self._score_length(word_count)        total = sum(scores[k] * self.weights[k] for k in scores)        return {'total': round(total, 1), 'details': scores,                'suggestions': self._generate_suggestions(scores)}        def _score_keyword_density(self, content):        content_lower = content.lower()        total_words = len(content_lower.split())        keyword_count = sum(content_lower.count(kw.lower()) for kw in self.target_keywords)        density = keyword_count / max(total_words, 1) * 100        if 1.0 <= density <= 3.0:            return min(100, density * 33)        elif density < 1.0:            return density * 80        else:            return max(0, 100 - (density - 3.0) * 20)        def _score_semantic(self, content):        content_lower = content.lower()        found = sum(1 for sw in self.semantic_words if sw.lower() in content_lower)        coverage = found / max(len(self.semantic_words), 1)        return round(coverage * 100, 1)        def _score_structure(self, headings):        h2_count = sum(1 for h in headings if h.startswith('##'))        h3_count = sum(1 for h in headings if h.startswith('###'))        score = min(100, h2_count * 15 + h3_count * 8)        return score        def _score_readability(self, content):        sentences = content.replace('！','!').replace('？','?').replace('.','。').split('。')        sentences = [s.strip() for s in sentences if s.strip()]        if not sentences:            return 0        avg_len = sum(len(s) for s in sentences) / len(sentences)        if avg_len <= 30:            return 100        elif avg_len <= 60:            return 100 - (avg_len - 30) * 1.5        else:            return max(0, 55 - (avg_len - 60) * 0.5)        def _score_length(self, word_count):        if word_count >= 2000:            return 100        elif word_count >= 1000:            return 50 + (word_count - 1000) / 20        else:            return word_count / 20        def _generate_suggestions(self, scores):        suggestions = []        if scores['keyword_density'] < 60:            suggestions.append('关键词密度偏低，建议自然增加目标关键词的使用')        if scores['semantic_coverage'] < 70:            suggestions.append('语义相关词覆盖不足，建议补充遗漏的语义词')        if scores['structure'] < 60:            suggestions.append('标题结构不够清晰，建议增加H2/H3小标题')        if scores['readability'] < 70:            suggestions.append('段落过长影响可读性，建议拆分长段落')        if scores['length'] < 80:            suggestions.append('内容字数不足，建议补充更多有价值的信息')        return suggestions scorer = SEOScorer(    target_keywords=['SEO优化', '内容营销', '搜索排名'],    semantic_words=['关键词密度', '语义相关词', '竞品分析', '内容蓝图', '长尾关键词'])content = 'SEO优化是内容营销的核心策略。通过合理的关键词密度和语义相关词覆盖，可以提升搜索排名。竞品分析帮助了解竞争对手的内容策略，生成内容蓝图指导创作。长尾关键词是获取精准流量的重要途径。'headings = ['## 什么是SEO优化', '## 关键词策略', '### 长尾关键词', '## 内容营销技巧']result = scorer.analyze_content(content, headings, 120)print(json.dumps(result, ensure_ascii=False, indent=2))