215 lines
6.3 KiB
Python
215 lines
6.3 KiB
Python
#!/usr/bin/env python3
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"""
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简化版质量检查脚本
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"""
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import os
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import re
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import sys
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from datetime import datetime
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def count_chinese_chars(text):
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"""统计中文字符数"""
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return len([c for c in text if '\u4e00' <= c <= '\u9fff'])
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def analyze_chapter(filepath):
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"""分析章节质量"""
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print(f"分析文件：{filepath}")
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with open(filepath, 'r', encoding='utf-8') as f:
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content = f.read()
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# 提取章节号
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filename = os.path.basename(filepath)
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match = re.search(r'(\d{4})_', filename)
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chapter_num = int(match.group(1)) if match else 0
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print(f"章节号：{chapter_num}")
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print(f"文件大小：{len(content)} 字符")
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# 1. 段落分析
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print("\n" + "="*60)
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print("段落分析：")
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lines = content.split('\n')
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paragraphs = []
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current_para = []
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for line in lines:
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stripped = line.strip()
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if not stripped:
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if current_para:
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paragraphs.append(''.join(current_para))
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current_para = []
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else:
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current_para.append(line)
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if current_para:
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paragraphs.append(''.join(current_para))
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# 过滤标题和空段落
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filtered_paras = []
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for para in paragraphs:
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para_stripped = para.strip()
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if para_stripped and not para_stripped.startswith('#'):
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filtered_paras.append(para_stripped)
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# 统计段落长度
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short_count = 0
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consecutive_short = 0
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max_consecutive = 0
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current_streak = 0
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lengths = []
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for para in filtered_paras:
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char_count = count_chinese_chars(para)
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lengths.append(char_count)
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if char_count < 35:
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short_count += 1
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current_streak += 1
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if current_streak > max_consecutive:
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max_consecutive = current_streak
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else:
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current_streak = 0
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total_paras = len(filtered_paras)
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short_ratio = short_count / total_paras if total_paras > 0 else 0
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avg_length = sum(lengths) / len(lengths) if lengths else 0
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print(f"总段落数：{total_paras}")
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print(f"短段落数(<35字)：{short_count}")
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print(f"短段落比例：{short_ratio*100:.1f}%")
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print(f"最长连续短段落：{max_consecutive}")
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print(f"平均段落长度：{avg_length:.1f}字")
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# 2. 爽点分析
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print("\n" + "="*60)
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print("爽点分析：")
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golden_keywords = ["打脸", "升级", "收获", "碾压", "反转", "爽点", "优势", "先知", "重生"]
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found_keywords = []
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for keyword in golden_keywords:
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if keyword in content:
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found_keywords.append(keyword)
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print(f"找到爽点关键词：{len(found_keywords)}/{len(golden_keywords)}")
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print(f"关键词：{', '.join(found_keywords)}")
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# 3. 对话分析
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print("\n" + "="*60)
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print("对话分析：")
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dialogue_pattern = r'["「](.+?)["」]'
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dialogues = re.findall(dialogue_pattern, content)
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total_chars = len(content)
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dialogue_chars = sum(len(d) for d in dialogues)
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dialogue_ratio = dialogue_chars / total_chars if total_chars > 0 else 0
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print(f"对话数量：{len(dialogues)}")
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print(f"对话比例：{dialogue_ratio*100:.1f}%")
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# 4. 问题识别
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print("\n" + "="*60)
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print("问题识别：")
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problems = []
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if short_ratio > 0.3:
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problems.append(f"短段落比例过高 ({short_ratio*100:.1f}%)")
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if max_consecutive > 3:
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problems.append(f"连续短段落过多 ({max_consecutive}个)")
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if len(found_keywords) < 3:
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problems.append(f"爽点不足 (找到{len(found_keywords)}个，需要至少3个)")
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if dialogue_ratio < 0.2:
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problems.append(f"对话比例偏低 ({dialogue_ratio*100:.1f}%)")
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if problems:
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print("⚠️ 发现问题：")
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for i, problem in enumerate(problems, 1):
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print(f" {i}. {problem}")
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else:
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print("✅ 未发现严重问题")
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# 5. 修复建议
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print("\n" + "="*60)
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print("修复建议：")
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recommendations = []
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if short_ratio > 0.3:
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recommendations.append("合并短段落，提高段落平均长度")
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if len(found_keywords) < 3:
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if chapter_num == 1:
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recommendations.append("第1章需要：1)明确重生优势 2)建立时间紧迫感 3)设置第一个目标")
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elif chapter_num <= 3:
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recommendations.append("黄金三章需要：1)兑现第一个爽点 2)打脸小反派 3)建立升级体系")
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else:
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recommendations.append("增加爽点密度：每章至少3个爽点")
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if dialogue_ratio < 0.2:
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recommendations.append("增加对话比例，目标30-40%")
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if recommendations:
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for i, rec in enumerate(recommendations, 1):
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print(f" {i}. {rec}")
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else:
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print(" ✅ 无需修复")
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# 6. 生成报告
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report = {
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"chapter": chapter_num,
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"file": filename,
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"timestamp": datetime.now().isoformat(),
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"metrics": {
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"paragraphs": {
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"total": total_paras,
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"short": short_count,
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"short_ratio": short_ratio,
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"max_consecutive_short": max_consecutive,
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"avg_length": avg_length
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},
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"golden_points": {
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"found": len(found_keywords),
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"keywords": found_keywords
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},
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"dialogue": {
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"count": len(dialogues),
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"ratio": dialogue_ratio
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}
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},
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"problems": problems,
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"recommendations": recommendations
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}
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# 保存报告
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report_file = f"quality_report_ch{chapter_num:04d}.json"
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import json
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with open(report_file, 'w', encoding='utf-8') as f:
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json.dump(report, f, ensure_ascii=False, indent=2)
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print(f"\n📄 报告已保存到：{report_file}")
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return report
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def main():
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if len(sys.argv) < 2:
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print("用法：python simple_quality_check.py <章节文件路径>")
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sys.exit(1)
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filepath = sys.argv[1]
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if not os.path.exists(filepath):
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print(f"错误：文件不存在 - {filepath}")
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sys.exit(1)
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analyze_chapter(filepath)
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if __name__ == "__main__":
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main() |