#!/usr/bin/env python3
"""
研究阶段：为选题收集资料并生成研究笔记
"""

import json, datetime, logging, sys, re
from pathlib import Path
from typing import Dict, List

PROJECT_ROOT = Path(__file__).parent.parent
sys.path.insert(0, str(PROJECT_ROOT))

DATA_DIR = PROJECT_ROOT / "automation" / "data"
CASES_FILE = DATA_DIR / "sustainability_cases.json"
TOPICS_FILE = DATA_DIR / "sustainability_topics.json"
OUTPUT_DIR = DATA_DIR / "research"  # 研究笔记输出目录
LOGS_DIR = PROJECT_ROOT / "automation" / "logs"
TODAY = datetime.datetime.now().strftime("%Y-%m-%d")

logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s',
                    handlers=[logging.FileHandler(LOGS_DIR / f"research_{TODAY}.log"), logging.StreamHandler()])
logger = logging.getLogger(__name__)

class Researcher:
    def __init__(self, topic_id: str):
        self.topic_id = topic_id
        self.topic = self._load_topic()
        self.cases = self._load_cases()
        self.output_dir = OUTPUT_DIR / TODAY
        self.output_dir.mkdir(parents=True, exist_ok=True)

    def _load_topic(self) -> Dict:
        topics = json.loads(TOPICS_FILE.read_text(encoding='utf-8'))
        for t in topics:
            if t['id'] == self.topic_id:
                return t
        raise ValueError(f"Topic {self.topic_id} not found")

    def _load_cases(self) -> List[Dict]:
        if CASES_FILE.exists():
            return json.loads(CASES_FILE.read_text(encoding='utf-8'))
        return []

    def find_relevant_cases(self, top_k: int = 5) -> List[Dict]:
        """基于标题和字段匹配相关案例（简化）"""
        field = self.topic.get('field', '').lower()
        title = self.topic.get('title', '').lower()
        scored = []
        for case in self.cases:
            # 日期过滤：仅保留 2025 年及以后（支持 YYYY-MM-DD 或 YYYY 格式）
            case_date = case.get('date', '')
            if case_date:
                m = re.search(r'(\d{4})', str(case_date))
                if m and int(m.group(1)) < 2025:
                    continue
            score = 0
            if field and field in case.get('field', '').lower():
                score += 3
            # 标题关键词匹配
            case_title = case.get('title', '').lower()
            for word in title.split():
                if len(word) > 2 and word in case_title:
                    score += 1
            if score > 0:
                scored.append((score, case))
        scored.sort(key=lambda x: x[0], reverse=True)
        return [c for _, c in scored[:top_k]]

    def generate_notes(self) -> str:
        """生成研究笔记 Markdown"""
        cases = self.find_relevant_cases()
        lines = [
            f"# 研究笔记：{self.topic['title']}",
            f"\n## 选题信息",
            f"- **ID**: {self.topic['id']}",
            f"- **领域**: {self.topic.get('field')}",
            f"- **核心观点**: {self.topic.get('core_concept', '待补充')}",
            f"- **受众痛点**: {self.topic.get('audience_pain', '待补充')}",
            f"- **独特视角**: {self.topic.get('unique_angle', '待补充')}",
            f"\n## 相关案例（{len(cases)}个）\n"
        ]
        for i, case in enumerate(cases, 1):
            lines.extend([
                f"### 案例 {i}: {case.get('title')}",
                f"- **来源**: {case.get('source', '未知')}",
                f"- **日期**: {case.get('date', '未知')}",
                f"- **摘要**: {case.get('summary', case.get('description', '无'))}",
                f"- **关键数据**: {case.get('key_metrics', '无')}",
                ""
            ])
        lines.extend([
            "## 研究发现摘要",
            "- 待补充：从案例中提炼的趋势和洞察",
            "- 待补充：数据支撑",
            "",
            "## 待深入研究的问题",
            "- [ ] 需要更多本土数据",
            "- [ ] 需要验证某些结论的适用性",
            "",
            f"*生成时间：{TODAY}*"
        ])
        return "\n".join(lines)

    def save(self):
        notes = self.generate_notes()
        out_path = self.output_dir / f"{self.topic_id}_research.md"
        out_path.write_text(notes, encoding='utf-8')
        logger.info(f"研究笔记已保存: {out_path}")
        return out_path

def main():
    import argparse
    parser = argparse.ArgumentParser()
    parser.add_argument('--topic-id', required=True, help='选题ID')
    args = parser.parse_args()

    r = Researcher(args.topic_id)
    r.save()
    print(f"SUCCESS: Research notes created for {args.topic_id}")
    sys.exit(0)

if __name__ == "__main__":
    main()