97 lines
3.4 KiB
Python
97 lines
3.4 KiB
Python
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import configparser
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import pandas as pd
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from sqlalchemy import create_engine
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from urllib.parse import quote_plus
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# 读取配置文件
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config = configparser.ConfigParser()
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config.read('config.ini')
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# 获取数据库连接配置
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source_config = {
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'host': config.get('source_db', 'host'),
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'user': config.get('source_db', 'user'),
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'password': config.get('source_db', 'password'),
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'database': config.get('source_db', 'database'),
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'port': config.getint('source_db', 'port')
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}
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target_config = {
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'host': config.get('target_db', 'host'),
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'user': config.get('target_db', 'user'),
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'password': config.get('target_db', 'password'),
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'database': config.get('target_db', 'database'),
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'port': config.getint('target_db', 'port')
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}
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# 创建数据库引擎
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source_engine = create_engine(
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f"mysql+pymysql://{source_config['user']}:{quote_plus(source_config['password'])}@{source_config['host']}:{source_config['port']}/{source_config['database']}"
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)
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target_engine = create_engine(
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f"mysql+pymysql://{target_config['user']}:{quote_plus(target_config['password'])}@{target_config['host']}:{target_config['port']}/{target_config['database']}"
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)
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# 定义状态映射
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status_mapping = {
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16: 0, # 待入库 → 0
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17: 1, # 在库 → 1
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18: 2, # 在用 → 2
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19: 3, # 退料检修 → 3
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23: 7, # 待报废 → 7
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24: 8, # 已报废 → 8
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64: 18, # 丢失 → 18
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133: 4 # 待审批 → 4
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}
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def normalize_date_string(s):
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if pd.isnull(s):
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return None
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if isinstance(s, str):
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s = s.replace('－', '-').strip()
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try:
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return pd.to_datetime(s, errors='coerce') # 自动识别格式
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except:
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return None
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return pd.to_datetime(s, errors='coerce') # 如果已经是日期，仍然尝试转化
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def process_machines():
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"""处理ma_machines表数据到ma_machine"""
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try:
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# 读取源数据
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df = pd.read_sql("SELECT * FROM ma_machine", source_engine)
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# 按照规则转换数据
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result = pd.DataFrame()
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result['ma_id'] = df['ID'] + 70000 # ID加70000
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result['type_id'] = df['MATYPE_ID'] + 6000 # 类型ID加6000
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result['ma_status'] = df['STATUS'].map(status_mapping) # 状态映射
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result['ma_code'] = df['CODE']
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result['out_fac_time'] = df['OUTFACTORT_TIME'].apply(normalize_date_string)
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result['out_fac_code'] = df['OUTCODE']
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result['ma_vender'] = df['SUPPLIER_ID'] + 500 # 供应商ID加500
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result['assets_code'] = df['ASSET_NUM']
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result['rfid_code'] = df['EPC_CODE']
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result['this_check_time'] = df['REPAIR_TIME'].apply(normalize_date_string)
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result['check_man'] = df['EXAMINER']
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result['next_check_time'] = df['NEXT_REPAIR_TIME'].apply(normalize_date_string)
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result['inspect_status'] = df['TESTRESULT']
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result['ex_code'] = df['EX_CODE']
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result['ex_url'] = df['EX_URL']
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result['ex_up_time'] = df['EX_UP_TIME'].apply(normalize_date_string)
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result['ex_name'] = df['EX_NAME']
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# 写入目标表
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result.to_sql('ma_machine', target_engine,
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if_exists='append', index=False)
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print(f"成功转换并导入 {len(result)} 条记录到 ma_machine")
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return True
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except Exception as e:
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print(f"处理 ma_machines 时发生错误: {str(e)}")
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return False
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if __name__ == "__main__":
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process_machines()
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