Merge branch 'wwr' into 'develop'

Wwr

See merge request !27

unify_api/modules/alarm_manager/dao/list_alarm_dao.py

@@ -268,7 +268,7 @@ async def list_alarm_zdu_dao_new15(cid, points, start,
 
 async def wx_list_alarm_zdu_dao(cid, points, start, end):
     """智电u, wx小程序, 取当前范围最新100条"""
-    
+
     query_body = {
         "size": 100,
         "query": {
@@ -346,7 +346,7 @@ async def zdu_alarm_sort_dao(cid, start, end, page_size, page_num):
     return data
 
 
-async def alarm_content_time_distribution_dao(cid, start, end,):
+async def alarm_content_time_distribution_dao(cid, start, end, ):
     """
     智电温度漏电流电参数分布
     """
@@ -371,4 +371,26 @@ async def alarm_content_time_distribution_dao(cid, start, end,):
         """
     async with MysqlUtil() as conn:
         elec_data = await conn.fetchall(sql, )
-    return elec_data
+    return elec_data if elec_data else []
+
+
+async def zdu_summary_dao(cid, start, end):
+    sql = f"""
+        SELECT
+            pid,
+            count(*) coun
+            
+        FROM
+            point_1min_event 
+        WHERE
+            cid = {cid} 
+            AND event_datetime BETWEEN '{start}' 
+            AND '{end}' AND pid is not null
+        GROUP BY
+            pid
+    """
+    async with MysqlUtil() as conn:
+        summary_data = await conn.fetchall(sql, )
+        total_alarm_cnt = sum([i.get('coun') for i in summary_data])
+        alarm_points = len(summary_data)
+    return total_alarm_cnt, alarm_points

unify_api/modules/alarm_manager/dao/list_static_dao.py

@@ -187,7 +187,7 @@ async def sdu_alarm_limit_type_dao_new15(start, end, points):
           f"event_datetime BETWEEN '{start}' and '{end}' " \
           f"and event_type in {tuple(SDU_ALARM_LIST)} GROUP BY pid, event_type"
     async with MysqlUtil() as conn:
-        datas = await conn.fetchall(sql, args=(points, ))
+        datas = await conn.fetchall(sql, args=(points,))
     return datas
 
 
@@ -366,57 +366,24 @@ async def zdu_alarm_aggs_date_impotent(cid, start, end):
     """zdu求安全运行
        根据每日聚合,再根据等级聚合
     """
-    start_dt = datetime.strptime(start, "%Y-%m-%d %H:%M:%S")
-    end_dt = datetime.strptime(end, "%Y-%m-%d %H:%M:%S")
-    es_start_str = datetime(year=start_dt.year, month=start_dt.month,
-                            day=start_dt.day).strftime(
-        "%Y-%m-%dT%H:%M:%S+08:00")
-    es_end_str = end_dt.strftime("%Y-%m-%dT%H:%M:%S+08:00")
-    query_body = {
-        "size": 0,
-        "query": {
-            "bool": {
-                "must": [
-                    {
-                        "term": {
-                            "cid": cid
-                        }
-                    },
-                    {
-                        "range": {
-                            "datetime": {
-                                "gte": es_start_str,
-                                "lte": es_end_str
-                            }
-                        }
-                    }
-                ]
-            }
-        },
-        "aggs": {
-            "date_day": {
-                "date_histogram": {
-                    "field": "datetime",
-                    "interval": "day",
-                    "time_zone": "+08:00",
-                    "format": "yyyy-MM-dd",
-                    "min_doc_count": 0,
-                    "extended_bounds": {"min": start_dt.strftime("%Y-%m-%d"),
-                                        "max": end_dt.strftime(
-                                            "%Y-%m-%d")},
-                },
-                "aggs": {"important_cnt": {"terms": {"field": "importance"}}}
-            }
-        }
-    }
-    log.info("query_body={}".format(query_body))
-    async with EsUtil() as es:
-        es_result = await es.search_origin(body=query_body,
-                                           index=constants.POINT_1MIN_EVENT)
-        return es_result["aggregations"]["date_day"]["buckets"]
+    sql = f"""
+        SELECT DISTINCT
+            DATE_FORMAT( event_datetime, '%m-%d' ) dat
+        FROM
+            point_1min_event 
+        WHERE
+            cid = {cid} 
+            AND event_datetime BETWEEN '{start}' 
+            AND '{end}' 
+            AND importance !=1
+         
+    """
+    async with MysqlUtil() as conn:
+        datas = await conn.fetchall(sql)
+    return len(datas) if datas else 0
 
 
-async def sdu_alarm_aggs_date_importance(cid): # todo: 扬尘es待改
+async def sdu_alarm_aggs_date_importance(cid):  # todo: 扬尘es待改
     """按日期,再按等级聚合"""
     query_body = {
         "size": 0,

unify_api/modules/alarm_manager/service/alarm_static_service.py

@@ -24,7 +24,7 @@ from unify_api.modules.home_page.procedures.security_info_pds import \
     alarm_count_info_new15
 from unify_api.utils.common_utils import round_1, division_two
 from unify_api.modules.alarm_manager.dao.list_alarm_dao import \
-    zdu_alarm_sort_dao, alarm_content_time_distribution_dao
+    zdu_alarm_sort_dao, alarm_content_time_distribution_dao, zdu_summary_dao
 
 
 async def sdu_alarm_statistics_service(cids, start, end, product):
@@ -464,23 +464,17 @@ async def zdu_content_distribution_service(cid, start, end, product):
 async def zdu_summary_service(cid, start, end, product):
     """报警统计-统计概况信息-智电u"""
     # 1. 报警总数, 报警监测点数, 平均报警 = 报警总数除以报警监测点
-    total_alarm_cnt, alarm_points = await zdu_summary_info(cid, start, end)
+    # total_alarm_cnt, alarm_points = await zdu_summary_info(cid, start, end)
+    total_alarm_cnt, alarm_points = await zdu_summary_dao(cid, start, end)
     # 2. 安全运行, 本月累计安全运行天数，从月初算起, 未出现一级报警则加一天
-    es_buckets = await zdu_alarm_aggs_date_impotent(cid, start, end)
-    total_day = len(es_buckets)
-    has_alarm = 0
-    for bucket in es_buckets:
-        inner_buckets = bucket["important_cnt"]["buckets"]
-        for ib in inner_buckets:
-            if ib["key"] == 1:
-                has_alarm += 1
+    safe_run = await zdu_alarm_aggs_date_impotent(cid, start, end)
     # 3. 时段分布, 白天/黑夜/凌晨
     time_distribution_map = await alarm_time_distribution([cid], start, end)
     return ZsResp(
         total_alarm_cnt=total_alarm_cnt,
         alarm_points_cnt=alarm_points,
         aver_alarm=round_1(division_two(total_alarm_cnt, alarm_points)),
-        safe_run=total_day - has_alarm,
+        safe_run=safe_run,
         time_interval_distribution=TimeCount(
             daytime_cnt=time_distribution_map["day_alarm_cnt"],
             night_cnt=time_distribution_map["night_alarm_cnt"],