74 lines
3.1 KiB
Python
74 lines
3.1 KiB
Python
import pandas as pd
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import json
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import os
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from typing import Dict, List, Optional
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JSON_INPUT_DIR = "./output/json"
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CSV_OUTPUT_PATH = "./家庭教育档案总表.csv"
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def read_single_json(json_file_path: str) -> Optional[Dict]:
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"""
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读取单个JSON文件，处理解析失败/文件损坏问题
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:param json_file_path: JSON文件绝对路径
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:return: 解析后的字典/None（失败则返回None）
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"""
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try:
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with open(json_file_path, "r", encoding="utf-8") as f:
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json_data = json.load(f)
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# 简单校验：必须包含核心字段"文件名称"，避免无效JSON
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if "文件名称" not in json_data:
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print(f"跳过无效JSON：{os.path.basename(json_file_path)}（缺失核心字段「文件名称」）")
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return None
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return json_data
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except json.JSONDecodeError:
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print(f"解析失败：{os.path.basename(json_file_path)}（JSON文件损坏/格式错误）")
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return None
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except Exception as e:
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print(f"读取失败：{os.path.basename(json_file_path)} - 错误：{str(e)[:50]}")
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return None
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def batch_json_to_csv():
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"""批量将JSON文件夹转为单张CSV数据表"""
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json_files = [
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f for f in os.listdir(JSON_INPUT_DIR)
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if f.lower().endswith(".json")
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]
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all_json_data: List[Dict] = []
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success_count = 0
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fail_count = 0
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for json_file in json_files:
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json_file_path = os.path.join(JSON_INPUT_DIR, json_file)
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json_data = read_single_json(json_file_path)
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if json_data:
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all_json_data.append(json_data)
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success_count += 1
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else:
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fail_count += 1
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df = pd.DataFrame(all_json_data)
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EXTRACT_FIELDS = [
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"监护人1姓名", "家庭角色", "文化程度", "职业", "年龄", "性格特征", "联系方式",
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"监护人2姓名", "家庭角色_2", "文化程度_2", "职业_2", "年龄_2", "性格特征_2", "联系方式_2",
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"孩子姓名", "性别", "孩子年龄", "年级", "孩子性格特征", "学习成绩",
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"家庭地址", "家庭基本情况", "家庭氛围", "亲子关系", "家长有无教育分歧",
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"是否经常否定孩子", "有无打骂教育", "孩子是否在父母身边长大",
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"还有谁参与孩子的养育", "孩子成长过程中有何重大影响事件", "既往病史",
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"孩子的优点", "孩子的缺点", "孩子目前情况的描述", "参加指导最想解决", "问卷评估"
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]
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# 固定列顺序：文件名称为首列，其余按提取顺序排列
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df = df[["文件名称"] + EXTRACT_FIELDS]
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try:
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df.to_csv(
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CSV_OUTPUT_PATH,
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index=False, # 不生成行索引
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encoding="utf-8-sig", # 兼容Excel/记事本的中文编码
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na_rep="" # 缺失字段/Null转为空白单元格，更整洁
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)
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except Exception as e:
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print(f"保存CSV失败 - 错误：{str(e)[:60]}")
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return
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if __name__ == "__main__":
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batch_json_to_csv() |