saas1.6

back_ground_module/datasource/saas_private_mini_program.py

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+from datetime import date, timedelta, datetime
+import holidays
+from config import Config
+import psycopg2
+import pandas as pd
+
+class GetProvateMiniProgram(Config):
+    def get_private_mini_program_details(self, days_back=1):
+        """
+        从固定的数据库中获取前几天的NGV明细。
+        参数 `days_back` 表示相对于今天的天数偏移量，默认为1（即前一天）。
+        返回包含NGV明细的pandas DataFrame。
+        """
+        try:
+            # 获得连接
+            conn = psycopg2.connect(**self.conn)
+            cursor = conn.cursor()
+
+            # 获取指定天数前的日期
+            now_time = datetime.now()
+            target_time = now_time + timedelta(days=-days_back)
+            target_date_id = int(target_time.strftime('%Y%m%d'))  # 获取目标日期
+
+            # sql语句查询
+            sql = f"""
+                SELECT * FROM "public"."holo_ads_report_saas_profile_ngv_detail_d" WHERE "date_id" = '{target_date_id}' ;
+                """
+
+            # 执行语句并获取结果集
+            cursor.execute(sql)
+            rows = cursor.fetchall()
+            all_fields = cursor.description
+
+            # 执行结果转化为dataframe
+            col = [i[0] for i in all_fields]
+            data_NGV = pd.DataFrame(rows, columns=col)
+
+            # 尝试自动解析日期时间字符串
+            time_format = "%Y-%m-%d %H:%M:%S"
+            if 'saas_create_time' in data_NGV.columns:
+                data_NGV['saas_create_time'] = pd.to_datetime(data_NGV['saas_create_time'], format=time_format,
+                                                              errors='coerce')
+                data_NGV['saas_create_time'] = data_NGV['saas_create_time'].dt.strftime('%Y-%m-%d')
+
+            # 关闭游标和连接
+            cursor.close()
+            conn.close()
+
+            return data_NGV
+
+        except Exception as e:
+            print(f"Error occurred: {e}")
+            return None