How解构结果可视化

#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ How解构结果可视化脚本 V2 改进版： - 使用标签页展示多个帖子 - 参考 visualize_inspiration_points.py 的帖子详情展示 - 分层可折叠的匹配结果 """ import json from pathlib import Path from typing import Dict, List import sys import html as html_module # 添加项目根目录到路径 project_root = Path(__file__).parent.parent.parent sys.path.insert(0, str(project_root)) def get_relation_color(relation: str) -> str: """根据关系类型返回对应的颜色""" color_map = { "same": "#10b981", # 绿色 - 同义 "contains": "#3b82f6", # 蓝色 - 包含 "contained_by": "#8b5cf6", # 紫色 - 被包含 "coordinate": "#f59e0b", # 橙色 - 同级 "overlap": "#ec4899", # 粉色 - 部分重叠 "related": "#6366f1", # 靛蓝 - 相关 "unrelated": "#9ca3af" # 灰色 - 无关 } return color_map.get(relation, "#9ca3af") def get_relation_label(relation: str) -> str: """返回关系类型的中文标签""" label_map = { "same": "同义", "contains": "包含", "contained_by": "被包含", "coordinate": "同级", "overlap": "部分重叠", "related": "相关", "unrelated": "无关" } return label_map.get(relation, relation) def generate_historical_post_card_html(post_detail: Dict, inspiration_point: Dict) -> str: """生成历史帖子的紧凑卡片HTML""" title = post_detail.get("title", "无标题") body_text = post_detail.get("body_text", "") images = post_detail.get("images", []) like_count = post_detail.get("like_count", 0) collect_count = post_detail.get("collect_count", 0) comment_count = post_detail.get("comment_count", 0) author = post_detail.get("channel_account_name", "") link = post_detail.get("link", "#") publish_time = post_detail.get("publish_time", "") # 获取灵感点信息 point_name = inspiration_point.get("点的名称", "") point_desc = inspiration_point.get("点的描述", "") # 准备详情数据（用于模态框） import json post_detail_data = { "title": title, "body_text": body_text, "images": images, "like_count": like_count, "comment_count": comment_count, "collect_count": collect_count, "author": author, "publish_time": publish_time, "link": link } post_data_json = json.dumps(post_detail_data, ensure_ascii=False) post_data_json_escaped = html_module.escape(post_data_json) # 截取正文预览（前80个字符） body_preview = body_text[:80] + "..." if len(body_text) > 80 else body_text # 生成缩略图 thumbnail_html = "" if images: thumbnail_html = f'

' html = f'''

{thumbnail_html} {f'

{len(images)}

' if len(images) > 1 else ''}

{html_module.escape(title)}

灵感点 {html_module.escape(point_name)}

{html_module.escape(point_desc[:100])}{"..." if len(point_desc) > 100 else ""}

📅 {publish_time}

❤ {like_count} ⭐ {collect_count} 查看原帖 →

''' return html def generate_post_detail_html(post_data: Dict, post_idx: int) -> str: """生成帖子详情HTML（紧凑的卡片样式，点击可展开）""" post_detail = post_data.get("帖子详情", {}) title = post_detail.get("title", "无标题") body_text = post_detail.get("body_text", "") images = post_detail.get("images", []) like_count = post_detail.get("like_count", 0) comment_count = post_detail.get("comment_count", 0) collect_count = post_detail.get("collect_count", 0) author = post_detail.get("channel_account_name", "") publish_time = post_detail.get("publish_time", "") link = post_detail.get("link", "") post_id = post_data.get("帖子id", f"post-{post_idx}") # 准备详情数据（用于模态框） import json post_detail_data = { "title": title, "body_text": body_text, "images": images, "like_count": like_count, "comment_count": comment_count, "collect_count": collect_count, "author": author, "publish_time": publish_time, "link": link } post_data_json = json.dumps(post_detail_data, ensure_ascii=False) post_data_json_escaped = html_module.escape(post_data_json) # 生成缩略图HTML thumbnail_html = "" if images and len(images) > 0: # 使用第一张图片作为缩略图 thumbnail_html = f'

' else: thumbnail_html = '

📄

' # 截断正文用于预览 body_preview = body_text[:80] + "..." if len(body_text) > 80 else body_text html = f'''

{thumbnail_html} {f'

📷 {len(images)}

' if len(images) > 1 else ''}

{html_module.escape(title)}

{html_module.escape(body_preview) if body_preview else "暂无正文"}

👤 {html_module.escape(author)} 📅 {publish_time}

👍 {like_count} 💬 {comment_count if comment_count else 0} ⭐ {collect_count if collect_count else 0}

''' return html def generate_inspiration_detail_html(inspiration_point: Dict) -> str: """生成灵感点详情HTML""" name = inspiration_point.get("名称", "") desc = inspiration_point.get("描述", "") features = inspiration_point.get("特征列表", []) features_html = "".join([ f'{html_module.escape(f)}' for f in features ]) html = f'''

灵感点

{html_module.escape(name)}

描述:

{html_module.escape(desc)}

特征列表:

{features_html}

''' return html def load_feature_category_mapping() -> Dict: """加载特征名称到分类的映射""" script_dir = Path(__file__).parent project_root = script_dir.parent.parent mapping_file = project_root / "data" / "data_1118" / "特征名称_分类映射.json" try: with open(mapping_file, "r", encoding="utf-8") as f: return json.load(f) except Exception as e: print(f"警告: 无法加载特征分类映射文件: {e}") return {} def load_feature_source_mapping() -> Dict: """加载特征名称到帖子来源的映射""" script_dir = Path(__file__).parent project_root = script_dir.parent.parent mapping_file = project_root / "data" / "data_1118" / "特征名称_帖子来源.json" try: with open(mapping_file, "r", encoding="utf-8") as f: data = json.load(f) # 转换为便于查询的格式: {特征名称: [来源列表]} result = {} for feature_type in ["灵感点", "关键点", "目的点"]: if feature_type in data: for item in data[feature_type]: feature_name = item.get("特征名称") if feature_name: result[feature_name] = item.get("特征来源", []) return result except Exception as e: print(f"警告: 无法加载特征来源映射文件: {e}") return {} def generate_match_results_html(how_steps: List[Dict], feature_idx: int, insp_idx: int, post_idx: int, category_mapping: Dict = None, source_mapping: Dict = None) -> str: """生成可折叠的匹配结果HTML""" if not how_steps or len(how_steps) == 0: return "" step = how_steps[0] features = step.get("特征列表", []) if feature_idx >= len(features): return "" feature_data = features[feature_idx] feature_name = feature_data.get("特征名称", "") match_results = feature_data.get("匹配结果", []) if category_mapping is None: category_mapping = {} # 按分数排序 sorted_matches = sorted(match_results, key=lambda x: x.get("匹配结果", {}).get("score", 0), reverse=True) # 统计匹配类型 relation_counts = {} for match in match_results: relation = match.get("匹配结果", {}).get("relation", "unrelated") relation_counts[relation] = relation_counts.get(relation, 0) + 1 # 生成统计信息 stats_items = [] for relation, count in sorted(relation_counts.items(), key=lambda x: x[1], reverse=True): label = get_relation_label(relation) color = get_relation_color(relation) stats_items.append(f'{label}: {count}') stats_html = "".join(stats_items) # 生成匹配项 matches_html = "" for i, match in enumerate(sorted_matches): persona_name = match.get("人设特征名称", "") match_result = match.get("匹配结果", {}) relation = match_result.get("relation", "unrelated") score = match_result.get("score", 0.0) explanation = match_result.get("explanation", "") color = get_relation_color(relation) label = get_relation_label(relation) match_id = f"post-{post_idx}-insp-{insp_idx}-feat-{feature_idx}-match-{i}" # 获取该人设特征的分类信息 # 需要在三个类型中查找该特征 categories_html = "" if category_mapping and persona_name: found_categories = None # 依次在灵感点、关键点、目的点中查找 for persona_type in ["灵感点", "关键点", "目的点"]: if persona_type in category_mapping: type_mapping = category_mapping[persona_type] if persona_name in type_mapping: found_categories = type_mapping[persona_name].get("所属分类", []) break if found_categories: # 简洁样式：[大类/中类/小类] categories_reversed = list(reversed(found_categories)) categories_text = "/".join(categories_reversed) categories_html = f'[{html_module.escape(categories_text)}]' # 获取该人设特征的历史帖子来源 historical_posts_html = "" if source_mapping and persona_name and persona_name in source_mapping: source_list = source_mapping[persona_name] if source_list: historical_cards = [] for source_item in source_list: post_detail = source_item.get("帖子详情", {}) if post_detail: card_html = generate_historical_post_card_html(post_detail, source_item) historical_cards.append(card_html) if historical_cards: historical_posts_html = f'''

历史帖子来源

{"".join(historical_cards)}

''' matches_html += f'''

▶ {categories_html} {html_module.escape(persona_name)} {label} 分数: {score:.2f}

''' section_id = f"post-{post_idx}-insp-{insp_idx}-feat-{feature_idx}-section" html = f'''

▼

匹配结果: {html_module.escape(feature_name)}

{stats_html}

{matches_html}

''' return html def generate_toc_html(post_data: Dict, post_idx: int) -> str: """生成目录导航HTML""" how_result = post_data.get("how解构结果", {}) inspiration_list = how_result.get("灵感点列表", []) toc_items = [] # 帖子详情 toc_items.append(f'

帖子详情帖子信息

') # 灵感点 for insp_idx, inspiration_point in enumerate(inspiration_list): name = inspiration_point.get("名称", f"灵感点 {insp_idx + 1}") name_short = name[:18] + "..." if len(name) > 18 else name toc_items.append(f'

灵感点 {html_module.escape(name_short)}

') # 特征列表 how_steps = inspiration_point.get("how步骤列表", []) if how_steps: features = how_steps[0].get("特征列表", []) for feat_idx, feature_data in enumerate(features): feature_name = feature_data.get("特征名称", f"特征 {feat_idx + 1}") toc_items.append(f'

特征 {html_module.escape(feature_name)}

') return f'''

目录导航

{"".join(toc_items)}

''' def generate_post_content_html(post_data: Dict, post_idx: int, category_mapping: Dict = None, source_mapping: Dict = None) -> str: """生成单个帖子的完整内容HTML""" # 生成目录 toc_html = generate_toc_html(post_data, post_idx) # 1. 帖子详情 post_detail_html = generate_post_detail_html(post_data, post_idx) # 2. 灵感点详情和匹配结果 how_result = post_data.get("how解构结果", {}) inspiration_list = how_result.get("灵感点列表", []) # 生成所有灵感点的详情HTML（只包含灵感点详情，不包含匹配结果） inspirations_detail_html = "" for insp_idx, inspiration_point in enumerate(inspiration_list): inspiration_detail = generate_inspiration_detail_html(inspiration_point) inspirations_detail_html += f'''

{inspiration_detail}

''' # 生成所有匹配结果HTML，按照how步骤分组 all_matches_html = "" for insp_idx, inspiration_point in enumerate(inspiration_list): inspiration_name = inspiration_point.get("名称", f"灵感点 {insp_idx + 1}") how_steps = inspiration_point.get("how步骤列表", []) if how_steps: # 为每个灵感点创建一个区域 for step_idx, step in enumerate(how_steps): step_name = step.get("步骤名称", f"步骤 {step_idx + 1}") features = step.get("特征列表", []) # 生成该步骤下所有特征的匹配结果 features_html = "" for feat_idx, feature_data in enumerate(features): match_html = generate_match_results_html([step], feat_idx, insp_idx, post_idx, category_mapping, source_mapping) features_html += f'

{match_html}

' # 生成步骤区域（可折叠） step_section_id = f"post-{post_idx}-step-{insp_idx}-{step_idx}" all_matches_html += f'''

▼

{html_module.escape(step_name)}

来自: {html_module.escape(inspiration_name)}

{features_html}

''' html = f'''

{toc_html}

{post_detail_html}

{inspirations_detail_html}

{all_matches_html}

''' return html def generate_combined_html(posts_data: List[Dict], category_mapping: Dict = None, source_mapping: Dict = None) -> str: """生成包含所有帖子的单一HTML（带标签页）""" # 生成标签页按钮 tabs_html = "" for i, post in enumerate(posts_data): post_detail = post.get("帖子详情", {}) title = post_detail.get("title", "无标题") active_class = "active" if i == 0 else "" tabs_html += f'\n' # 生成标签页内容 contents_html = "" for i, post in enumerate(posts_data): active_class = "active" if i == 0 else "" content = generate_post_content_html(post, i, category_mapping, source_mapping) contents_html += f'''

{content}

''' html = f''' How解构结果可视化

{tabs_html}

{contents_html}

''' return html def main(): """主函数""" script_dir = Path(__file__).parent project_root = script_dir.parent.parent data_dir = project_root / "data" / "data_1118" input_dir = data_dir / "当前帖子_how解构结果" output_file = data_dir / "当前帖子_how解构结果_可视化.html" print(f"读取 how 解构结果: {input_dir}") # 加载特征分类映射 print(f"加载特征分类映射...") category_mapping = load_feature_category_mapping() print(f"已加载 {sum(len(v) for v in category_mapping.values())} 个特征分类") # 加载特征来源映射 print(f"加载特征来源映射...") source_mapping = load_feature_source_mapping() print(f"已加载 {len(source_mapping)} 个特征的来源信息") json_files = list(input_dir.glob("*_how.json")) print(f"找到 {len(json_files)} 个文件\n") posts_data = [] for i, file_path in enumerate(json_files, 1): print(f"读取文件 [{i}/{len(json_files)}]: {file_path.name}") with open(file_path, "r", encoding="utf-8") as f: post_data = json.load(f) posts_data.append(post_data) print(f"\n生成合并的 HTML...") html_content = generate_combined_html(posts_data, category_mapping, source_mapping) print(f"保存到: {output_file}") with open(output_file, "w", encoding="utf-8") as f: f.write(html_content) print(f"\n完成! 可视化文件已保存") print(f"请在浏览器中打开: {output_file}") if __name__ == "__main__": main()

{html_module.escape(name)}

历史帖子来源

匹配结果: {html_module.escape(feature_name)}

{html_module.escape(step_name)}

How 解构结果可视化