13 changed files with 345005 additions and 176 deletions
@ -0,0 +1,165 @@ |
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import json |
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import re |
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import os |
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from neo4j import GraphDatabase |
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|
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# === 配置 === |
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NEO4J_URI = "bolt://localhost:7687" |
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NEO4J_USER = "neo4j" |
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NEO4J_PASSWORD = "12345678" # 👈 请确保密码正确 |
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RELATIONSHIP_FOLDER = r"D:\temp\669" |
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BATCH_SIZE = 100 |
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|
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|
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def sanitize_relationship_type(rel_type: str) -> str: |
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"""清理关系类型，确保合法""" |
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if not isinstance(rel_type, str): |
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rel_type = str(rel_type) |
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sanitized = re.sub(r"[^a-zA-Z0-9_]", "", rel_type) |
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if not sanitized or sanitized[0].isdigit(): |
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sanitized = "REL_" + sanitized |
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return sanitized or "RELATED" |
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|
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|
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def extract_start_end(rel: dict): |
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"""兼容多种字段名提取 start/end""" |
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for s_key, e_key in [("start", "end"), ("source", "target"), ("from", "to")]: |
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s = rel.get(s_key) |
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e = rel.get(e_key) |
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if s is not None and e is not None: |
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return s, e |
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return None, None |
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|
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|
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def load_relationships_from_file(filepath): |
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"""从单个 JSON 文件加载 relationships""" |
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with open(filepath, "r", encoding="utf-8-sig") as f: |
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data = json.load(f) |
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|
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relationships = [] |
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if isinstance(data, list): |
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for item in data: |
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if isinstance(item, dict) and "relationships" in item: |
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relationships.extend(item["relationships"]) |
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elif isinstance(item, dict): |
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relationships.append(item) |
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elif isinstance(data, dict) and "relationships" in data: |
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relationships = data["relationships"] |
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else: |
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relationships = data if isinstance(data, list) else [] |
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|
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return relationships |
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|
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|
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def process_relationships(relationships): |
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"""清洗并验证关系列表""" |
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valid_rels = [] |
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for rel in relationships: |
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start_id, end_id = extract_start_end(rel) |
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rel_type = rel.get("type", "RELATED") |
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props = rel.get("properties", {}) or {} |
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|
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if start_id is None or end_id is None: |
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continue |
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|
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try: |
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start_id = int(float(start_id)) |
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end_id = int(float(end_id)) |
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except (TypeError, ValueError): |
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continue |
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|
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valid_rels.append({ |
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"start": start_id, |
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"end": end_id, |
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"type": sanitize_relationship_type(rel_type), |
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"props": props |
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}) |
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return valid_rels |
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|
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|
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def import_relationships_in_batches(tx, rels, batch_size): |
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total = len(rels) |
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created_total = 0 |
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|
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for i in range(0, total, batch_size): |
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batch = rels[i:i + batch_size] |
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rel_groups = {} |
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for rel in batch: |
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rel_groups.setdefault(rel["type"], []).append({ |
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"start": rel["start"], |
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"end": rel["end"], |
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"props": rel["props"] |
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}) |
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|
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created_this_batch = 0 |
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for rel_type, group in rel_groups.items(): |
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cypher = f""" |
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UNWIND $rels AS r |
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MATCH (a {{nodeId: r.start}}) |
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MATCH (b {{nodeId: r.end}}) |
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WITH a, b, r |
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WHERE a IS NOT NULL AND b IS NOT NULL |
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MERGE (a)-[rel:`{rel_type}`]->(b) |
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SET rel += r.props |
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RETURN count(rel) AS c |
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""" |
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result = tx.run(cypher, rels=group).single() |
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created_this_batch += result["c"] |
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|
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created_total += created_this_batch |
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print(f" ➤ 本批创建关系: {created_this_batch} 条") |
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return created_total |
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def main(): |
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driver = GraphDatabase.driver(NEO4J_URI, auth=(NEO4J_USER, NEO4J_PASSWORD)) |
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|
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# 获取所有 JSON 文件，并按文件名排序（确保 relations_001.json 先于 002） |
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json_files = [f for f in os.listdir(RELATIONSHIP_FOLDER) if f.startswith("relations_") and f.endswith(".json")] |
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json_files.sort() # 按字典序排序，适用于 001, 002... 格式 |
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|
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if not json_files: |
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print("❌ 文件夹中没有找到 relations_*.json 文件") |
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return |
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total_global_created = 0 |
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total_global_processed = 0 |
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print(f"📁 找到 {len(json_files)} 个关系文件，开始逐个导入...\n") |
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for idx, filename in enumerate(json_files, 1): |
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filepath = os.path.join(RELATIONSHIP_FOLDER, filename) |
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print(f"\n📄 [{idx}/{len(json_files)}] 正在处理: {filename}") |
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try: |
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raw_rels = load_relationships_from_file(filepath) |
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print(f" ➤ 原始关系数: {len(raw_rels)}") |
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valid_rels = process_relationships(raw_rels) |
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print(f" ➤ 有效关系数: {len(valid_rels)}") |
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if not valid_rels: |
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print(" ⚠️ 跳过：无有效关系") |
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continue |
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with driver.session() as session: |
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created = session.execute_write(import_relationships_in_batches, valid_rels, BATCH_SIZE) |
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total_global_created += created |
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total_global_processed += len(valid_rels) |
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print(f" ✅ 文件 {filename} 导入完成，创建 {created} 条关系") |
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except Exception as e: |
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print(f" ❌ 处理 {filename} 时出错: {e}") |
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continue # 继续处理下一个文件 |
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print("\n" + "="*60) |
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print(f"🎉 全部导入完成！") |
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print(f"📊 总共处理有效关系: {total_global_processed}") |
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print(f"✅ 总共成功创建关系: {total_global_created}") |
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driver.close() |
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if __name__ == "__main__": |
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main() |
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@ -0,0 +1,100 @@ |
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import pandas as pd |
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from neo4j import GraphDatabase |
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import numpy as np |
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|
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# === 配置 === |
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EXCEL_PATH = r"C:\Users\hanyuqing\Desktop\最新国家医保ICD编码\最新国家医保ICD编码\ICD-10医保版数据.xlsx" |
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NEO4J_URI = "bolt://localhost:7687" |
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NEO4J_USER = "neo4j" |
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NEO4J_PASSWORD = "12345678" |
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|
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# === 读取 Excel === |
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df = pd.read_excel( |
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EXCEL_PATH, |
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header=1, |
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dtype=str, # 关键：防止 A00.0 变成 A00 |
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engine='openpyxl' |
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) |
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|
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# 清理列名 |
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df.columns = df.columns.astype(str).str.strip() |
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|
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# 必需列 |
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required_cols = [ |
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"条目（诊断）名称", "条目（诊断）代码", |
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"亚目名称", "亚目代码", |
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"章代码范围", "节代码范围", "类目代码" |
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] |
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|
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# 检查列是否存在 |
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missing = [col for col in required_cols if col not in df.columns] |
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if missing: |
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raise ValueError(f"缺少必要列: {missing}") |
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|
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# 替换 NaN 为 None（便于后续判断） |
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df = df.replace({np.nan: None}) |
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|
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# === 构造 name 和 code 字段（按你的逻辑）=== |
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def get_disease_name(row): |
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diag_name = row["条目（诊断）名称"] |
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subcat_name = row["亚目名称"] |
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# 如果诊断名称为空（None 或 空白），用亚目名称 |
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if not diag_name or str(diag_name).strip() == "": |
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return str(subcat_name).strip() if subcat_name else None |
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return str(diag_name).strip() |
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|
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def get_diagnosis_code(row): |
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code = row["条目（诊断）代码"] |
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# 如果为空，返回空字符串 "" |
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if not code or str(code).strip() == "": |
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return "" |
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return str(code).strip() |
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|
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# 应用逻辑 |
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df["_disease_name"] = df.apply(get_disease_name, axis=1) |
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df["_diagnosis_code"] = df.apply(get_diagnosis_code, axis=1) |
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# 过滤掉 name 仍为 None 的行（即 诊断名 + 亚目名 都为空） |
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df = df[df["_disease_name"].notna() & (df["_disease_name"] != "")] |
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print(f"✅ 共准备 {len(df)} 条疾病记录用于导入") |
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|
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# === Neo4j 连接 === |
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driver = GraphDatabase.driver(NEO4J_URI, auth=(NEO4J_USER, NEO4J_PASSWORD)) |
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|
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def upsert_disease(tx, record): |
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cypher = """ |
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MERGE (d:Disease {name: $name}) |
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ON CREATE SET |
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d.diagnosisCode = $diagnosisCode, |
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d.chapterRange = $chapterRange, |
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d.sectionRange = $sectionRange, |
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d.categoryCode = $categoryCode, |
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d.subcategoryCode = $subcategoryCode |
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ON MATCH SET |
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d.diagnosisCode = $diagnosisCode, |
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d.chapterRange = $chapterRange, |
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d.sectionRange = $sectionRange, |
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d.categoryCode = $categoryCode, |
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d.subcategoryCode = $subcategoryCode |
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""" |
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tx.run(cypher, { |
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"name": record["_disease_name"], |
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"diagnosisCode": record["_diagnosis_code"], |
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"chapterRange": record.get("章代码范围") or "", |
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"sectionRange": record.get("节代码范围") or "", |
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"categoryCode": record.get("类目代码") or "", |
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"subcategoryCode": record.get("亚目代码") or "" |
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}) |
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|
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# === 批量导入 === |
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with driver.session() as session: |
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for idx, row in df.iterrows(): |
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try: |
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session.execute_write(upsert_disease, row.to_dict()) |
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except Exception as e: |
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print(f"❌ 第 {idx + 2} 行失败: {e}") |
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continue |
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|
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print("✅ 数据导入完成！") |
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driver.close() |
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@ -0,0 +1,173 @@ |
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import pandas as pd |
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import json |
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import numpy as np |
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import re |
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|
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# === 配置 === |
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EXCEL_PATH = r"C:\Users\hanyuqing\Desktop\最新国家医保ICD编码\最新国家医保ICD编码\ICD-10医保版数据.xlsx" |
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OUTPUT_JSON_PATH = "icd10_tree_with_level.json" |
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|
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# === 章 code 格式化 === |
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def extract_chapter_number(text): |
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if not text: |
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return None |
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text = str(text).strip() |
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match = re.search(r'第([一二三四五六七八九十百\d]+)章', text) |
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if match: |
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num_str = match.group(1) |
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chinese_num_map = { |
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'一': 1, '二': 2, '三': 3, '四': 4, '五': 5, |
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'六': 6, '七': 7, '八': 8, '九': 9, '十': 10, |
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'十一': 11, '十二': 12, '十三': 13, '十四': 14, '十五': 15, |
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'十六': 16, '十七': 17, '十八': 18, '十九': 19, '二十': 20, |
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'二十一': 21, '二十二': 22 |
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} |
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if num_str in chinese_num_map: |
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return chinese_num_map[num_str] |
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elif num_str.isdigit(): |
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return int(num_str) |
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if text.isdigit(): |
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return int(text) |
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if text.endswith('.') and text[:-1].isdigit(): |
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return int(text[:-1]) |
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return None |
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|
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def format_chapter_code(original): |
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num = extract_chapter_number(original) |
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if num is not None: |
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return f"第{num}章" |
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return str(original).strip() if original else "" |
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|
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def get_clean(val): |
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if val is None or str(val).strip().lower() in ("", "nan", "none"): |
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return None |
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return str(val).strip() |
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|
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def make_fields(code, name): |
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code_str = code or "" |
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label_str = name or "" |
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title_str = f"{code_str} {label_str}" if code_str and label_str else (code_str or label_str) |
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return code_str, label_str, title_str |
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|
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# === 带 level 的树节点 === |
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class TreeNode: |
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def __init__(self, code="", label="", title="", level=""): |
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self.code = code |
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self.label = label |
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self.title = title |
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self.level = level # 新增字段 |
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self.children = [] |
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self._child_key_set = set() # (code, label) |
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|
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def add_or_get_child(self, code, label, title, level): |
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key = (code, label) |
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if key in self._child_key_set: |
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for child in self.children: |
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if child.code == code and child.label == label: |
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return child |
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else: |
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new_child = TreeNode(code=code, label=label, title=title, level=level) |
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self.children.append(new_child) |
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self._child_key_set.add(key) |
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return new_child |
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return None |
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|
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# === 构建树 === |
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root = TreeNode() |
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chapter_map = {} |
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|
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df = pd.read_excel( |
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EXCEL_PATH, |
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header=1, |
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dtype=str, |
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engine='openpyxl' |
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) |
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df.columns = df.columns.astype(str).str.strip() |
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df = df.replace({np.nan: None}) |
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|
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for idx, row in df.iterrows(): |
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raw_chapter = get_clean(row.get("章")) |
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chapter_name = get_clean(row.get("章的名称")) |
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|
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section_code = get_clean(row.get("节代码范围")) |
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section_name = get_clean(row.get("节名称")) |
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|
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category_code = get_clean(row.get("类目代码")) |
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category_name = get_clean(row.get("类目名称")) |
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|
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subcategory_code = get_clean(row.get("亚目代码")) |
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subcategory_name = get_clean(row.get("亚目名称")) |
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|
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diagnosis_code = get_clean(row.get("条目（诊断）代码")) |
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diagnosis_name = get_clean(row.get("条目（诊断）名称")) |
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|
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if not raw_chapter and not chapter_name: |
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continue |
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|
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# === 章 === |
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chapter_code = format_chapter_code(raw_chapter) |
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chap_label = chapter_name or chapter_code |
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chap_title = f"{chapter_code} {chapter_name}" if chapter_name else chapter_code |
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chap_key = (chapter_code, chap_label) |
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|
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if chap_key not in chapter_map: |
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chapter_node = TreeNode( |
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code=chapter_code, |
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label=chap_label, |
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title=chap_title, |
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level="chapter" |
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) |
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root.children.append(chapter_node) |
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chapter_map[chap_key] = chapter_node |
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else: |
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chapter_node = chapter_map[chap_key] |
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|
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current = chapter_node |
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|
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# === 节 === |
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if section_code or section_name: |
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sec_code, sec_label, sec_title = make_fields(section_code, section_name) |
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current = current.add_or_get_child(sec_code, sec_label, sec_title, "section") |
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|
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# === 类目 === |
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if category_code or category_name: |
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cat_code, cat_label, cat_title = make_fields(category_code, category_name) |
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current = current.add_or_get_child(cat_code, cat_label, cat_title, "category") |
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|
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# === 亚目 === |
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if subcategory_code or subcategory_name: |
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sub_code, sub_label, sub_title = make_fields(subcategory_code, subcategory_name) |
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current = current.add_or_get_child(sub_code, sub_label, sub_title, "subcategory") |
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|
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# === 条目 === |
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if diagnosis_code or diagnosis_name: |
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diag_code, diag_label, diag_title = make_fields(diagnosis_code, diagnosis_name) |
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current.add_or_get_child(diag_code, diag_label, diag_title, "diagnosis") |
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|
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# === 转为带 id 的 dict === |
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next_id = 1 |
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|
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def node_to_dict(node): |
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global next_id |
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item = { |
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"id": next_id, |
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"code": node.code, |
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"label": node.label, |
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"title": node.title, |
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"level": node.level # 新增 |
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} |
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next_id += 1 |
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|
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if node.children: |
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item["children"] = [node_to_dict(child) for child in node.children] |
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|
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return item |
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|
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treeData = [node_to_dict(chap) for chap in root.children] |
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|
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# === 保存 === |
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with open(OUTPUT_JSON_PATH, 'w', encoding='utf-8') as f: |
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json.dump(treeData, f, ensure_ascii=False, indent=2) |
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|
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print(f"✅ 树形结构已生成，共 {len(treeData)} 个章节点") |
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print(f"📄 输出文件: {OUTPUT_JSON_PATH}") |
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File diff suppressed because it is too large
@ -1,4 +1,8 @@ |
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import { createApp } from 'vue' |
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import App from './App.vue' |
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import ElementPlus from 'element-plus' |
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import 'element-plus/dist/index.css' |
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|
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createApp(App).mount('#app') |
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const app = createApp(App) |
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app.use(ElementPlus) |
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app.mount('#app') |
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|
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Reference in new issue