gov_commodity_zhejiang_city.py 6.9 KB

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  1. import time
  2. from pathlib import Path
  3. import pandas as pd
  4. from zhejiang import download_dir
  5. from utils import base_country_code, base_mysql
  6. from utils.base_country_code import format_sql_value
  7. from utils.log import log
  8. city_code_map = {
  9. "杭州地区": "330100",
  10. "宁波地区": "330200",
  11. "温州地区": "330300",
  12. "绍兴地区": "330400",
  13. "湖州地区": "330500",
  14. "嘉兴地区": "330600",
  15. "金华地区": "330700",
  16. "衢州地区": "330800",
  17. "舟山地区": "330900",
  18. "台州地区": "331000",
  19. "丽水地区": "331100"
  20. }
  21. def get_df(path, year_month):
  22. file_paths = list(Path(path).glob('*'))
  23. if not file_paths:
  24. log.info("未找到任何文件")
  25. return None
  26. flag = True
  27. file_path = file_paths[0]
  28. if len(file_paths) > 1:
  29. for file_path in file_paths:
  30. if '十一地市' in file_path.name:
  31. file_path = file_path
  32. flag = False
  33. break
  34. if flag:
  35. xls = pd.ExcelFile(file_path)
  36. df = pd.read_excel(xls, sheet_name=0, header=None)
  37. else:
  38. df = pd.read_excel(file_path, header=None)
  39. import_df = pd.DataFrame()
  40. export_df = pd.DataFrame()
  41. total_df = pd.DataFrame()
  42. temp_df = df[[1, 2]].rename(columns={1: 'commodity', 2: 'total'})
  43. temp_df['total'] = pd.to_numeric(temp_df['total'].replace('--', 0), errors='coerce').astype(float)
  44. if year_month and year_month == '2024-07':
  45. temp_df['total'] = temp_df['total'] / 10000
  46. total_df = pd.concat([total_df, temp_df])
  47. temp_df = df[[1, 3]].rename(columns={1: 'commodity', 3: 'import'})
  48. temp_df['import'] = pd.to_numeric(temp_df['import'].replace('--', 0), errors='coerce').astype(float)
  49. if year_month and year_month == '2024-07':
  50. temp_df['import'] = temp_df['import'] / 10000
  51. import_df = pd.concat([import_df, temp_df])
  52. temp_df = df[[1, 4]].rename(columns={1: 'commodity', 4: 'export'})
  53. temp_df['export'] = pd.to_numeric(temp_df['export'].replace('--', 0), errors='coerce').astype(float)
  54. if year_month and year_month == '2024-07':
  55. temp_df['export'] = temp_df['export'] / 10000
  56. export_df = pd.concat([export_df, temp_df])
  57. return import_df, export_df, total_df
  58. def process_folder(path):
  59. year, month = base_country_code.extract_year_month_from_path(path)
  60. year_month = f'{year}-{month:02d}'
  61. sql_arr = []
  62. res = get_df(path, None)
  63. if res is None:
  64. log.info(f"{year_month} prov_region_trade 未找到包含 地市 sheet")
  65. return
  66. import_df, export_df, total_df = res
  67. # 当月数据分组清洗
  68. curr_import = import_df.groupby('commodity')['import'].sum().reset_index()
  69. curr_export = export_df.groupby('commodity')['export'].sum().reset_index()
  70. total_df = total_df.groupby('commodity')['total'].sum().reset_index()
  71. if not month == 1:
  72. previous_month_dir = base_country_code.get_previous_month_dir(path)
  73. res = get_df(previous_month_dir, year_month)
  74. if res is None:
  75. log.info(f"{path} 上月目录里文件未找到包含 地市 sheet")
  76. return
  77. prev_import_df, prev_export_df, prev_total_df = res
  78. # 上月数据分组
  79. prev_import = prev_import_df.groupby('commodity')['import'].sum().reset_index()
  80. prev_export = prev_export_df.groupby('commodity')['export'].sum().reset_index()
  81. prev_total_df = prev_total_df.groupby('commodity')['total'].sum().reset_index()
  82. # 差值计算
  83. curr_import = pd.merge(curr_import, prev_import, on='commodity', how='left')
  84. curr_import['import'] = round(curr_import['import_x'] - curr_import['import_y'], 4)
  85. curr_export = pd.merge(curr_export, prev_export, on='commodity', how='left')
  86. curr_export['export'] = round(curr_export['export_x'] - curr_export['export_y'], 4)
  87. total_df = pd.merge(total_df, prev_total_df, on='commodity', how='left')
  88. total_df['total'] = round(total_df['total_x'] - total_df['total_y'], 4)
  89. log.info(f"合并文件: {path}*********{previous_month_dir}")
  90. # 合并进出口数据
  91. merged_df = pd.merge(curr_import, curr_export, on='commodity', how='outer')
  92. merged_df = pd.merge(merged_df, total_df, on='commodity', how='outer')
  93. for _, row in merged_df.iterrows():
  94. city_name = str(row['commodity']).strip()
  95. city_code = city_code_map.get(city_name)
  96. if not city_code:
  97. log.info(f"未找到省 '{city_name}' 对应市编码")
  98. continue
  99. # 提取数据并格式化
  100. if year == 2025 or (year == 2024 and month in [7, 8, 9, 10, 11, 12]):
  101. monthly_import = round(row['import'], 4)
  102. monthly_export = round(row['export'], 4)
  103. monthly_total = round(row['total'], 4)
  104. else:
  105. monthly_import = round(row['import'] / 10000, 4)
  106. monthly_export = round(row['export'] / 10000, 4)
  107. monthly_total = round(row['total'] / 10000, 4)
  108. yoy_import_export, yoy_import, yoy_export = 0, 0, 0
  109. # 组装 SQL 语句
  110. sql = (f"INSERT INTO t_yujin_crossborder_prov_region_trade "
  111. f"(crossborder_year, crossborder_year_month, prov_code, prov_name, city_code, city_name, monthly_total, monthly_export, monthly_import,yoy_import_export, yoy_import, yoy_export, create_time) VALUES "
  112. f"('{year}', '{year_month}', '330000', '浙江省', '{city_code}', '{city_name}', {format_sql_value(monthly_total)}, {format_sql_value(monthly_export)}, {format_sql_value(monthly_import)}, '{yoy_import_export}', '{yoy_import}', '{yoy_export}', now()) ON DUPLICATE KEY UPDATE create_time = now();\n")
  113. sql_arr.append(sql)
  114. log.info(f"√ {year_month} prov_region_trade 成功生成 SQL 文件 size {len(sql_arr)} ")
  115. base_mysql.bulk_insert(sql_arr)
  116. log.info(f"√ {year_month} prov_region_trade SQL 存表完成!")
  117. def hierarchical_traversal(root_path):
  118. root = Path(root_path)
  119. year_dirs = [
  120. item for item in root.iterdir()
  121. if item.is_dir() and base_country_code.YEAR_PATTERN.match(item.name)
  122. ]
  123. for year_dir in sorted(year_dirs, key=lambda x: x.name, reverse=True):
  124. log.info(f"\n年份:{year_dir.name} | 省份:zhejiang")
  125. month_dirs = []
  126. for item in year_dir.iterdir():
  127. if item.is_dir() and base_country_code.MONTH_PATTERN.match(item.name):
  128. month_dirs.append({"path": item, "month": int(item.name)})
  129. if month_dirs:
  130. for md in sorted(month_dirs, key=lambda x: x["month"], reverse=True):
  131. log.info(f" 月份:{md['month']:02d} | 路径:{md['path']}")
  132. process_folder(md['path'])
  133. if __name__ == '__main__':
  134. hierarchical_traversal(download_dir)
  135. log.info(f"浙江杭州海关城市所有文件处理完成!")
  136. time.sleep(5)
  137. base_mysql.update_january_yoy('浙江省')
  138. base_mysql.update_shandong_yoy('浙江省')
  139. log.info("同比sql处理完成")
  140. # root = Path(download_dir)/'2024'/'07'
  141. # process_folder(root)