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- """
- 药典 PDF 解析器
- 将药典 PDF 文件解析为结构化的药品条目 JSON
- """
- import json
- import logging
- from pathlib import Path
- from typing import Optional
- logger = logging.getLogger(__name__)
- class PharmacopoeiaParser:
- def __init__(self, pdf_path: Path):
- self.pdf_path = pdf_path
- self.drug_entries = []
- def parse(self) -> list[dict]:
- """
- 解析流程：
- 1. PyMuPDF 提取文本 + 坐标
- 2. 基于字体大小/位置识别标题层级
- 3. 正则匹配药品条目边界
- 4. 按条目切分 → 结构化输出
- Phase 2 实现。
- """
- logger.info(f"Parsing pharmacopoeia PDF: {self.pdf_path}")
- return []
- def _extract_text_with_position(self, page_num: int) -> list[dict]:
- """提取页面文本块及其位置信息"""
- return []
- def _detect_entry_boundaries(self, blocks: list[dict]) -> list[tuple[int, int]]:
- """检测药品条目边界"""
- return []
- def _parse_entry_sections(self, text: str) -> dict:
- """
- 解析条目内各栏目：
- 性状、鉴别、检查、含量测定、类别、贮藏、制剂
- """
- sections = {
- "性状": "", "鉴别": "", "检查": "",
- "含量测定": "", "类别": "", "贮藏": "", "制剂": "",
- }
- return sections
- def export_json(self, output_path: Path):
- """导出为 JSON 文件"""
- entries = self.parse()
- with open(output_path, "w", encoding="utf-8") as f:
- json.dump(entries, f, ensure_ascii=False, indent=2)
- logger.info(f"Exported {len(entries)} drug entries to {output_path}")
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