145 lines
5.3 KiB
Python
145 lines
5.3 KiB
Python
import openpyxl
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import json
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import os
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from typing import List, Dict, Any
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from Config.Config import EXCEL_PATH
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from Util.AreaUtil import query_area_info
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# ======================= 配置常量 =======================
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DATA_DIR = os.path.join(os.path.dirname(os.path.dirname(__file__)), 'Data')
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JSON_PATH = os.path.join(DATA_DIR, 'RenKou.json')
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SHEET_NAME = '人口' # 工作表名称
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REGION_NAME_COLUMN = 'A' # 区域名称所在列
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START_ROW = 3 # 数据起始行
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YEAR_RANGE = range(2015, 2025) # 年份范围
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# 数据列配置 (指标: (起始列, 结束列))
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DATA_COLUMNS = {
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'total_population': ('B', 'K'), # 年末总人口
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'urban_population': ('L', 'U'), # 城镇人口
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'rural_population': ('V', 'AE'), # 乡村人口
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'urbanization_rate': ('AF', 'AO'), # 城镇化率
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'birth_population': ('AP', 'AY') # 出生人口
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}
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# ======================= 工具函数 =======================
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def init_directories() -> None:
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"""初始化数据目录"""
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os.makedirs(DATA_DIR, exist_ok=True)
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def process_value(value: Any) -> int | float | int:
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"""处理单元格值，转换为合适的数值类型"""
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if value is None or str(value).strip() == '':
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return 0
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try:
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if isinstance(value, str):
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value = value.replace(',', '').strip()
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return float(value) if '.' in str(value) else int(value)
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except (ValueError, TypeError):
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return 0
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# ======================= 核心逻辑 =======================
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def extract_area_data(sheet: openpyxl.worksheet.worksheet.Worksheet) -> List[Dict[str, Any]]:
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"""从工作表提取区域数据"""
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population_data: List[Dict[str, Any]] = []
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conversion_records: List[Dict[str, str]] = []
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name_conversion_errors: List[str] = []
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# 遍历数据行
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for row_num in range(START_ROW, sheet.max_row + 1):
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row = sheet[row_num]
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raw_name = str(row[openpyxl.utils.column_index_from_string(REGION_NAME_COLUMN)-1].value or '未知地区').strip()
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if not raw_name:
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continue
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# 区域名称转换
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area_info = query_area_info(raw_name)
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if area_info:
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area_name = area_info['full_name']
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area_code = area_info['area_code']
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if raw_name != area_name:
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conversion_records.append({
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'row': row_num,
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'raw_name': raw_name,
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'converted_name': area_name
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})
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else:
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area_name = raw_name
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area_code = 'unknown'
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name_conversion_errors.append(f"行 {row_num}: '{raw_name}'")
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# 构建区域数据
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area_data = {
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'area_name': area_name,
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'area_code': area_code,
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'raw_name': raw_name
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}
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# 提取各指标年度数据
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for metric, (start_col, end_col) in DATA_COLUMNS.items():
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start_idx = openpyxl.utils.column_index_from_string(start_col) - 1
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end_idx = openpyxl.utils.column_index_from_string(end_col) - 1
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year_data = {}
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for col_idx, year in zip(range(start_idx, end_idx + 1), YEAR_RANGE):
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cell_value = row[col_idx].value
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year_data[str(year)] = process_value(cell_value)
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area_data[metric] = year_data
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population_data.append(area_data)
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# 输出转换统计
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print_conversion_stats(conversion_records, name_conversion_errors)
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return population_data
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def print_conversion_stats(conversion_records: List[Dict[str, str]], errors: List[str]) -> None:
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"""打印名称转换统计信息"""
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print("\n=== 名称转换记录 ===")
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for record in conversion_records:
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print(f"🔄 行 {record['row']}: {record['raw_name']} → {record['converted_name']}")
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print(f"📊 共检测到 {len(conversion_records)} 项名称转换")
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if errors:
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print(f"⚠️ 发现 {len(errors)} 个区域名称转换失败：")
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for error in errors:
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print(f" - {error}")
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else:
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print("✅ 所有区域名称均成功转换为全称")
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# ======================= 主函数 =======================
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def main() -> None:
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"""人口数据提取主函数"""
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init_directories()
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try:
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# 加载工作簿
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workbook = openpyxl.load_workbook(EXCEL_PATH, read_only=True, data_only=True)
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if SHEET_NAME not in workbook.sheetnames:
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print(f"❌ 错误：未找到'{SHEET_NAME}'工作表")
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return
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# 提取并处理数据
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sheet = workbook[SHEET_NAME]
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population_data = extract_area_data(sheet)
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# 保存结果
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with open(JSON_PATH, 'w', encoding='utf-8') as f:
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json.dump(population_data, f, ensure_ascii=False, indent=2)
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print(f"✅ 人口数据提取完成，已保存至：{JSON_PATH}")
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print(f"📊 共处理 {len(population_data)} 条地区数据")
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except FileNotFoundError:
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print(f"🔴 错误：Excel文件 '{EXCEL_PATH}' 不存在")
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except Exception as e:
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print(f"🔴 处理数据时发生错误：{str(e)}")
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finally:
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try:
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workbook.close()
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except:
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pass
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if __name__ == '__main__':
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main() |