-- ----------------------------
-- Table structure for dingdan
-- ----------------------------
DROP TABLE IF EXISTS `dingdan`;
CREATE TABLE `dingdan`  (
  `d_id` int(11) NOT NULL,
  `UPC` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
  PRIMARY KEY (`d_id`) USING BTREE
) ENGINE = InnoDB CHARACTER SET = utf8 COLLATE = utf8_general_ci ROW_FORMAT = Dynamic;

-- ----------------------------
-- Records of dingdan
-- ----------------------------
INSERT INTO `dingdan` VALUES (1, '6972470560664');
INSERT INTO `dingdan` VALUES (2, '6972470560664');
INSERT INTO `dingdan` VALUES (3, '6972470561227');
INSERT INTO `dingdan` VALUES (4, '6972470561890');
INSERT INTO `dingdan` VALUES (5, '6972470561906');

SET FOREIGN_KEY_CHECKS = 1;


-- ----------------------------
-- Table structure for shangpin
-- ----------------------------
DROP TABLE IF EXISTS `shangpin`;
CREATE TABLE `shangpin`  (
  `UPC` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL,
  `商品` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
  PRIMARY KEY (`UPC`) USING BTREE
) ENGINE = InnoDB CHARACTER SET = utf8 COLLATE = utf8_general_ci ROW_FORMAT = Dynamic;

-- ----------------------------
-- Records of shangpin
-- ----------------------------
INSERT INTO `shangpin` VALUES ('6972470560657', 'A');
INSERT INTO `shangpin` VALUES ('6972470560664', 'A');
INSERT INTO `shangpin` VALUES ('6972470561210', 'D');
INSERT INTO `shangpin` VALUES ('6972470561227', 'B');
INSERT INTO `shangpin` VALUES ('6972470561890', 'C');
INSERT INTO `shangpin` VALUES ('6972470651791', 'B');

SET FOREIGN_KEY_CHECKS = 1;

-- 搜索未下單的商品信息
SELECT *,
if(bb.UPC IS NULL,'未下單', '下單') as 下單情況

FROM shangpin aa

LEFT JOIN dingdan bb
ON aa.UPC = bb.UPC

import pymysql  #導入PyMySQL庫 
import datetime
import warnings
import pandas as pd
import matplotlib.pyplot as plt
warnings.filterwarnings('ignore')

# 1. 連接數(shù)據(jù)庫，創(chuàng)建連接對象 db
# 連接對象作用是：連接數(shù)據(jù)庫、發(fā)送數(shù)據(jù)庫信息、處理回滾操作（查詢中斷時，數(shù)據(jù)庫回到最初狀態(tài)）、
# 創(chuàng)建新的光標對象 
def connect_database(database, password):
     db = pymysql.connect(host ="localhost", #host屬性 
                              user ="sys", #用戶名  
                              password = password, #此處填登錄數(shù)據(jù)庫的密碼 
                              database = database, #數(shù)據(jù)庫名 
                              charset="utf8"  # 如果中文顯示亂碼,則需要添加charset = "utf8"
                         )
     return db

def read_data(db):
     # 2. 使用 cursor() 方法創(chuàng)建一個游標對象 cursor
     cursor = db.cursor()
     # 3. 利用MySQL語句查找數(shù)據(jù)并轉化為FrameData（包含列名）
     try:
          # 使用 execute() 方法執(zhí)行 SQL 查詢
          mysql = "SELECT *, if(bb.UPC IS NULL,'未下單', '下單') as 下單情況 FROM shangpin aa LEFT JOIN dingdan bb ON aa.UPC = bb.UPC" # SQL語句
          cursor.execute(mysql)
          data = cursor.fetchall()

          # 下面為將獲取的數(shù)據(jù)轉化為 dataframe 格式
          columnDes = cursor.description #獲取連接對象的描述信息
          #print("cursor.description中的內容：",columnDes)
          columnNames = [columnDes[i][0] for i in range(len(columnDes))] #獲取列名
          df = pd.DataFrame([list(i) for i in data],columns=columnNames) #得到的data為二維元組，逐行取出，轉化為列表，再轉化為df
          print(df)

          """
          db.commit()若對數(shù)據(jù)庫進行了修改，需進行提交之后再關閉
          """
          # 提交到數(shù)據(jù)庫執(zhí)行
          #db.commit()
          #print("OK")
     except:
          # 如果發(fā)生錯誤則回滾
          db.rollback()
          print("失敗")
     """
     使用完成之后需關閉游標和數(shù)據(jù)庫連接，減少資源占用,cursor.close(),db.close()
     db.commit()若對數(shù)據(jù)庫進行了修改，需進行提交之后再關閉
     """
     # 關閉數(shù)據(jù)庫連接
     cursor.close()
     db.close()
     return df    

     ## 定時任務
     import time
     from apscheduler.schedulers.blocking import BlockingScheduler
     
     def job():
       dt = time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))
       print('{} --- {}'.format(text, t))
       database = 'sys' #數(shù)據(jù)庫名稱
       password = 'sys' #數(shù)據(jù)庫用戶密碼
       db = connect_database(database, password)
       data_sp = read_data(db)
       data_sp.to_excel('../data/data_ans.xlsx', sheet_name='未下單情況')
       
     scheduler = BlockingScheduler()
     # 在每天22和23點的25分，運行一次 job 方法
     scheduler.add_job(job, 'cron', hour='22-23', minute='25')
     scheduler.start()
     
     ## 測試
     # 執(zhí)行任務
     def time_printer():
         # 輸出時間
         now = datetime.datetime.now()
         ts = now.strftime('%Y-%m-%d %H:%M:%S')
         print('do func time :', ts)
     # 定時任務
     def loop_monitor():
         while True:
             time.sleep(20)  # 暫停20秒
             
     if __name__ == "__main__":
         loop_monitor()

import pandas as pd
def taskTime():
## 1. 分別導入2個表的數(shù)據(jù)
    product = pd.read_excel('d:/python_code/crontab/data/taskdata.xlsx', sheet_name='商品') # 換成自己的路徑和sheet名稱
    order = pd.read_excel('d:/python_code/crontab/data/taskdata.xlsx', sheet_name='訂單') 

    ## 2. 抽取數(shù)據(jù)
    product=product.rename(columns={'UPC':'ID'}) # 對商品表里面的UPC重命名未ID（為了保留訂單表里面的CPU著一列）
    PO=pd.merge(product,order,left_on='ID', right_on='UPC',how='left') # 左連接抽取數(shù)據(jù)
    PO.loc[pd.isnull(PO['UPC']), '下單情況'] = '未下單' # 找到選中但是未下單的數(shù)據(jù)標注為未下單
    PO['下單情況'] = PO['下單情況'].fillna(value='下單') # 找到下單的數(shù)據(jù)，在'下單情況'這一列中標注為下單

    ## 3. 以excel的形式導出查詢好的數(shù)據(jù)
    PO = PO.loc[:, ['ID', 'UPC', '下單情況', '產品名稱E', '產品參數(shù)C', '價格', '建議零售價','訂單日期', '品牌', 'PO#', 'SKU','配置', '單價', '數(shù)量', '銷售金額', '成本單價', '成本', '成本價含稅/未稅']] # 按列名導出需要的數(shù)據(jù)
    PO.to_excel('d:/python_code/crontab/data/data_python.xlsx', sheet_name='未下單情況')  # 導出excel表
    return PO

if __name__ == "__main__":
  taskTime()
    print('執(zhí)行成功')

   ## 2. 定時處理
   import datetime
   from apscheduler.schedulers.blocking import BlockingScheduler
   
   def job():
     now = datetime.datetime.now()
     ts = now.strftime('%Y-%m-%d %H:%M:%S')
     print('執(zhí)行時間 :', ts)   # 輸出時間
     taskTime()  # 執(zhí)行代碼
   
   scheduler = BlockingScheduler() ## 定時 
   # 在每天17和23點的25分，運行一次 job 方法
 scheduler.add_job(job, 'cron', hour='17-23', minute='22')
   scheduler.start()

python d:\python_code\crontab\code\test.py

 python 路徑\文件名.py