remove es 2023-6-2

unify_api/modules/anshiu/procedures/scope_operations_pds.py

 import asyncio
 import datetime
 import json
-import math
-
 from pot_libs.qingstor_util.qs_client import QsClient
-from pot_libs.es_util.es_utils import EsUtil
 from pot_libs.logger import log
 from pot_libs.mysql_util.mysql_util import MysqlUtil
-from unify_api import constants
-from unify_api.modules.anshiu.components.scope_operations_cps import \
-    ScopeDetail
 from unify_api.modules.anshiu.dao.fine_monitor_dao import get_mtid_by_pid_dao
 from unify_api.modules.anshiu.dao.scope_operations_dao import \
     get_scope_url_by_pid
-
-from unify_api.modules.electric.procedures.electric_util import \
-    get_wiring_type_new15
 from unify_api.utils.log_utils import LOGGER
 
 

unify_api/modules/anshiu/service/scope_operations_serv.py

 import json
 import math
 from pot_libs.qingstor_util.qs_client import QsClient
-import pandas as pd
-from pandas.core.dtypes.inference import is_number
-
 from unify_api.modules.zhiwei_u.fault_foreast.actionFile import actionFilemin
 from unify_api.modules.zhiwei_u.fault_foreast.test import leakage_reg
 from unify_api.utils.log_utils import LOGGER
@@ -16,8 +13,6 @@ from pot_libs.es_util.es_utils import EsUtil
 from pot_libs.logger import log
 from pot_libs.utils.exc_util import BusinessException
 from pot_libs.utils.pendulum_wrapper import my_pendulum
-from pot_libs.utils.time_format import convert_dt_to_timestr, \
-    convert_to_es_str, time_str_to_str
 from unify_api.modules.anshiu.components.scope_operations_cps import \
     ScopeListItem, ScopeContent, ScopeDetailsResp, GetScopeConfigList, \
     init_scope_config_example, ScopeItemDownload, ScopeDetail, ScopeDetails
@@ -27,16 +22,12 @@ from unify_api.modules.anshiu.dao.scope_operations_dao import \
 from unify_api.modules.anshiu.procedures.scope_operations_pds import \
     get_scope_config_by_pid, set_scope_config_by_pid, add_scope_config_by_pid, \
     get_scope_list_by_pid
-from unify_api.modules.common.dao.common_dao import point_by_points, \
-    points_by_cid
 from unify_api.modules.device_cloud.procedures.mqtt_helper import \
     change_param_to_config
 from unify_api.modules.electric.procedures.electric_util import \
     get_wiring_type_new15
 from unify_api.modules.zhiwei_u import config
-from unify_api.modules.zhiwei_u.dao.data_es_dao import query_search_scope_pids, \
-    query_search_scope
-from unify_api.utils import time_format
+from unify_api.modules.zhiwei_u.dao.data_es_dao import query_search_scope
 from unify_api.utils.time_format import get_time_duration, \
     get_current_datetime_str, convert_str_to_timestamp
 

unify_api/modules/common/dao/common_dao.py

@@ -359,7 +359,7 @@ async def get_fields_by_mtid(mtid, table_name="monitor", fields="m_type"):
     return result
 
 
-async def sql_point_15min_index_new15(start, end, pid):
+async def load_point_pttl_mean(start, end, pid):
     sql = f"SELECT pttl_mean, create_time FROM `point_15min_electric` " \
           f"where pid=%s and create_time BETWEEN '{start}' and '{end}'"
     async with MysqlUtil() as conn:

unify_api/modules/elec_charge/service/elec_charge_service.py

@@ -8,8 +8,7 @@ from unify_api.modules.elec_charge.dao.elec_charge_dao import \
     query_charge_aggs_points
 from unify_api.modules.electric.dao.electric_dao import \
     monitor_point_join_by_points
-from unify_api.modules.home_page.procedures.count_info_pds import current_load, \
-    current_load_new15
+from unify_api.modules.home_page.procedures.count_info_pds import real_time_load
 from unify_api.utils.common_utils import round_2, division_two
 
 
@@ -107,9 +106,9 @@ async def kwh_card_level_service(cid, point_list, start, end):
 
 async def load_info_service(cid_list):
     # 实时负荷
-    cur_load = await current_load_new15(cid_list)
+    cur_load = await real_time_load(cid_list)
     yesterday_dt = pendulum.now(tz="Asia/Shanghai").subtract(days=1)
-    yes_load = await current_load_new15(cid_list, yesterday_dt)
+    yes_load = await real_time_load(cid_list, yesterday_dt)
     load_percent = round((cur_load - yes_load) / yes_load,
                          2) if cur_load and yes_load else ""
     return cur_load, yes_load, load_percent

unify_api/modules/home_page/procedures/count_info_pds.py

@@ -260,60 +260,7 @@ async def normal_rate_of_location(cid):
     return temperature_qr, residual_current_qr
 
 
-async def current_load(company_id):
-    """
-    实时负荷
-    :param company_id:
-    :return:
-    """
-    async with MysqlUtil() as conn:
-        point_sql = "select pid from point where cid= %s " \
-                    "and add_to_company = 1"
-        points = await conn.fetchall(point_sql, args=(company_id,))
-        point_ids = [p["pid"] for p in points]
-
-    if not point_ids:
-        return ""
-
-    async with MysqlUtil() as conn:
-        meter_sql = (
-            "SELECT pid, mid FROM change_meter_record WHERE pid in %s ORDER BY pid, start_time"
-        )
-        change_meters = await conn.fetchall(meter_sql,
-                                            args=(tuple(point_ids),))
-        # 正序排序，最后这个map存储的是按照start_time是最近的mid
-        change_meter_map = {m["pid"]: m["mid"] for m in change_meters if
-                            m["mid"] is not None}
-
-    newest_mids = list(change_meter_map.values())
-
-    meterdata_currents = []
-    if newest_mids:
-        meterdata_currents = await RedisUtils().hmget(METERDATA_CURRENT_KEY,
-                                                      *newest_mids)
-    now_tt = int(time.time())
-
-    if meterdata_currents:
-        total = 0
-        for item in meterdata_currents:
-            # 这里是有可能item为None的
-            if item:
-                item = json.loads(item.decode())
-                mdptime_tt = None
-                if "mdptime" in item:
-                    mdptime = datetime.strptime(item["mdptime"],
-                                                "%Y-%m-%d %H:%M:%S")
-                    mdptime_tt = time.mktime(mdptime.timetuple())
-                item_tt = item.get("timestamp") or mdptime_tt
-                if item_tt:
-                    # 小于2分钟内的数据相加为实时负荷
-                    if now_tt - item_tt <= 2 * 60:
-                        total += item["pttl"]
-        return total
-    return ""
-
-
-async def current_load_new15(cid, end_dt=None):
+async def real_time_load(cid, end_dt=None):
     """实时负荷"""
     datas = await get_elec_mtid_sid_by_cid(cid)
     td_mt_tables = tuple(
@@ -362,7 +309,7 @@ async def power_count_info(cid):
     end_time = now.strftime("%Y-%m-%d %H:%M:%S")
 
     max_30d_load, _time = await pttl_max_new15(cid, start_time, end_time, -1)
-    cur_load = await current_load_new15(cid)
+    cur_load = await real_time_load(cid)
     return round_2(cur_load), round_2(max_30d_load)
 
 

unify_api/modules/home_page/service/count_info_service.py

@@ -19,10 +19,10 @@ from unify_api.modules.home_page.dao.count_info_dao import \
     alarm_aggs_point_location
 from unify_api.modules.home_page.procedures.count_info_pds import other_info, \
     electric_use_info, cid_alarm_importance_count, \
-    alarm_importance_count_total, current_load, \
+    alarm_importance_count_total, \
     get_company_charge_price, health_status_res, carbon_status_res_web, \
     optimization_count_info, economic_index_desc, \
-    cal_power_factor, current_load_new15
+    cal_power_factor, real_time_load
 from unify_api.modules.home_page.procedures.count_info_proxy_pds import \
     alarm_percentage_count, alarm_safe_power
 from unify_api.modules.tsp_water.dao.drop_dust_dao import \
@@ -270,7 +270,7 @@ async def alarm_price_costtl_service(cid):
     # 2. 实时功率因数， 上月功率因数
     cos_ttl, last_month_cos = await cal_power_factor(cid)
     # 3. 实时负荷
-    cur_load = await current_load_new15(cid)
+    cur_load = await real_time_load(cid)
     # 4. 平均电价
     # 昨天
     yesterday_start, yesterday_end = yesterday_range()

unify_api/modules/tsp_water/dao/tsp_dao.py

@@ -12,7 +12,7 @@ TSP_15MIN = "poweriot_tsp_15min"
 async def meterdata_tsp_current(tsp_id):
     """根据tsp_id获取redis实时数据"""
     res = await RedisUtils().hget(TSP_CURRENT, tsp_id)
-    res =json.loads(res) if res else {}
+    res = json.loads(res) if res else {}
     return res
 
 
@@ -76,201 +76,13 @@ async def tsp_histogram_tsp_id(date_start, date_end, tsp_id, interval):
     return es_re["aggregations"]["quarter_time"]["buckets"]
 
 
-async def tsp_index_statistics(date_start, date_end, tsp_id):
-    """TSP信息-指标统计"""
-    start_es = convert_es_str(date_start)
-    end_es = convert_es_str(date_end)
-
-    query_body = {
-        "query": {
-            "bool": {
-                "must": [
-                    {
-                        "term": {
-                            "tsp_id": tsp_id
-                        }
-                    },
-                    {
-                        "range": {
-                            "quarter_time": {
-                                "gte": start_es,
-                                "lte": end_es
-                            }
-                        }
-                    }
-                ]
-            }
-        },
-        "size": 0,
-        "aggs": {
-            "pm25_max": {
-                "top_hits": {
-                    "sort": [
-                        {
-                            "pm25_max": {
-                                "order": "desc"
-                            }
-                        }
-                    ],
-                    "size": 1,
-                    "_source": ["pm25_max", "pm25_max_time"]
-                }
-            },
-            "pm25_min": {
-                "top_hits": {
-                    "sort": [
-                        {
-                            "pm25_min": {
-                                "order": "asc"
-                            }
-                        }
-                    ],
-                    "size": 1,
-                    "_source": ["pm25_min", "pm25_min_time"]
-                }
-            },
-            "pm10_max": {
-                "top_hits": {
-                    "sort": [
-                        {
-                            "pm10_max": {
-                                "order": "desc"
-                            }
-                        }
-                    ],
-                    "size": 1,
-                    "_source": ["pm10_max", "pm10_max_time"]
-                }
-            },
-            "pm10_min": {
-                "top_hits": {
-                    "sort": [
-                        {
-                            "pm10_min": {
-                                "order": "asc"
-                            }
-                        }
-                    ],
-                    "size": 1,
-                    "_source": ["pm10_min", "pm10_min_time"]
-                }
-            },
-            "tsp_max": {
-                "top_hits": {
-                    "sort": [
-                        {
-                            "tsp_max": {
-                                "order": "desc"
-                            }
-                        }
-                    ],
-                    "size": 1,
-                    "_source": ["tsp_max", "tsp_max_time"]
-                }
-            },
-            "tsp_min": {
-                "top_hits": {
-                    "sort": [
-                        {
-                            "tsp_min": {
-                                "order": "asc"
-                            }
-                        }
-                    ],
-                    "size": 1,
-                    "_source": ["tsp_min", "tsp_min_time"]
-                }
-            },
-            "pm25_avg": {
-                "avg": {
-                    "field": "pm25_max"
-                }
-            },
-            "pm10_avg": {
-                "avg": {
-                    "field": "pm10_max"
-                }
-            },
-            "tsp_avg": {
-                "avg": {
-                    "field": "tsp_max"
-                }
-            }
-        }
-    }
-    log.info(query_body)
-    async with EsUtil() as es:
-        es_re = await es.search_origin(body=query_body, index=TSP_15MIN)
-    return es_re["aggregations"]
-
-
-async def tsp_aggs_tsp_id(date_start, date_end, tsp_list):
-    """1. 按tsp_id聚合
-       2. 分别求平均值
-    """
-    start_es = convert_es_str(date_start)
-    end_es = convert_es_str(date_end)
-
-    query_body = {
-        "size": 0,
-        "query": {
-            "bool": {
-                "must": [
-                    {
-                        "terms": {
-                            "tsp_id": tsp_list
-                        }
-                    },
-                    {
-                        "range": {
-                            "quarter_time": {
-                                "gte": start_es,
-                                "lte": end_es
-                            }
-                        }
-                    }
-                ]
-            }
-        },
-        "aggs": {
-            "tsps": {
-                "terms": {
-                    "field": "tsp_id",
-                    "size": 1000
-                },
-                "aggs": {
-                    "pm25": {
-                        "avg": {
-                            "field": "pm25_mean"
-                        }
-                    },
-                    "pm10": {
-                        "avg": {
-                            "field": "pm10_mean"
-                        }
-                    },
-                    "tsp": {
-                        "avg": {
-                            "field": "tsp_mean"
-                        }
-                    }
-                }
-            }
-        }
-    }
-    log.info(query_body)
-    async with EsUtil() as es:
-        es_re = await es.search_origin(body=query_body, index=TSP_15MIN)
-    return es_re["aggregations"]["tsps"]["buckets"]
-
-
 async def tsp_by_tsp_id_dao(start, end, tsp_list):
     sql = f'SELECT tsp_id, ' \
           f'AVG(pm25_mean) pm25,AVG(pm10_mean) pm10,AVG(tsp_mean) tsp ' \
           f'FROM `tsp_day_record` where tsp_id in %s and ' \
           f'create_time BETWEEN "{start}" and "{end}" GROUP BY tsp_id '
     async with MysqlUtil() as conn:
-        datas = await conn.fetchall(sql, args=(tsp_list, ))
+        datas = await conn.fetchall(sql, args=(tsp_list,))
     return datas
 
 

unify_api/modules/tsp_water/service/drop_dust_service.py

@@ -2,7 +2,7 @@ from unify_api.constants import SLOTS_15MIN, DUST_STATE
 from unify_api.modules.common.dao.common_dao import storey_pl_by_cid, \
     storey_wp_by_cid
 from unify_api.modules.common.dao.common_dao import \
-     sql_point_15min_index_new15
+     load_point_pttl_mean
 from unify_api.modules.common.procedures.points import points_by_storeys
 from unify_api.modules.tsp_water.components.drop_dust_cps import DdwResp, \
     DdResp, IrmResp, IosResp, ItiResp, WsStatiResp
@@ -11,7 +11,7 @@ from unify_api.modules.tsp_water.dao.drop_dust_dao import \
     dust_water_run_state_by_time, sum_water_runts_group, sum_kwh_runts_group, \
     dust_water_run_day_sum_water, dust_fogcan_run_day_sum_kwh, sum_water_group
 from unify_api.modules.tsp_water.service.tsp_service import day_env_service,\
-    day_env_service_new15
+    day_env_service
 from unify_api.utils.common_utils import round_2
 from unify_api.utils.time_format import srv_time, last7_day_range, \
     start_end_date
@@ -108,7 +108,7 @@ async def post_drop_dust_wave_service(point_id, start, end):
     """降尘措施-雾炮-运行曲线"""
     # 1. 获取聚合信息
     slots_list = SLOTS_15MIN
-    sql_re = await sql_point_15min_index_new15(start, end, point_id)
+    sql_re = await load_point_pttl_mean(start, end, point_id)
     if not sql_re:
         return DdwResp(slots=[], value=[])
     es_re_dic = {str(i["create_time"])[-8:-3]: i for i in sql_re}
@@ -228,7 +228,7 @@ async def index_today_info_service(cid):
     """首页-今日数据-扬尘"""
     # 1. 环境信息
     # dr = await day_env_service(cid)
-    dr = await day_env_service_new15(cid)
+    dr = await day_env_service(cid)
     # 2. 今日用水, 用电
     today_start, today_end, m_start, m_end = start_end_date()
     start = today_start.split(" ")[0]

unify_api/modules/tsp_water/service/tsp_service.py

@@ -12,8 +12,7 @@ from unify_api.modules.common.dao.common_dao import tsp_by_cid, \
 from unify_api.modules.tsp_water.components.drop_dust_cps import DtResp, \
     ThResp, TisResp, DeResp, SaResp, TcdResp, TpdResp, AdResp
 from unify_api.modules.tsp_water.dao.tsp_dao import meterdata_tsp_current, \
-    tsp_histogram_tsp_id, tsp_index_statistics, tsp_aggs_tsp_id, \
-    tsp_by_tsp_id_dao
+    tsp_histogram_tsp_id, tsp_by_tsp_id_dao
 from unify_api.modules.tsp_water.dao.tsp_map_dao import \
     get_predict_data_day_dao, get_predict_data_month_dao, get_page_data, \
     get_contrast_data_day_dao, get_contrast_data_month_dao, get_cid_tsp_dao
@@ -24,8 +23,7 @@ from unify_api.modules.tsp_water.procedures.tsp_pds import per_hour_wave, \
     per_hour_wave_new15
 from unify_api.utils import time_format
 from unify_api.utils.common_utils import round_2, correlation, round_0
-from unify_api.utils.es_query_body import es_process
-from unify_api.utils.time_format import esstr_to_dthoutstr, start_end_date
+from unify_api.utils.time_format import start_end_date
 
 
 async def real_time_service(tsp_id):
@@ -49,7 +47,7 @@ async def tsp_history_service(tsp_id, start, end):
     interval, slots = time_format.time_pick_transf(start, end)
     # 实时数据
     pm25_list, pm10_list, tsp_list = await \
-        get_data_new15(tsp_id, start, end, slots, interval)
+        get_tsp_data(tsp_id, start, end, slots, interval)
     # 预测数据
     pm25_predict, pm10_predict, tsp_predict, _ = \
         await get_predict_data(tsp_id, start, end, slots)
@@ -69,44 +67,7 @@ async def tsp_history_service(tsp_id, start, end):
     )
 
 
-# tsp实时数据
-async def get_data(tsp_id, start, end, slots, interval):
-    """TSP信息-历史曲线"""
-    # 1. 查询es
-    if interval == 24 * 3600:
-        interval = "day"
-        fmt = "MM-DD"
-    elif interval == 15 * 60:
-        interval = "15m"
-        fmt = "HH:mm"
-    else:
-        raise BusinessException(message="time range not day or month")
-    es_res = await tsp_histogram_tsp_id(start, end, tsp_id, interval)
-    if not es_res:
-        return ThResp(pm2_5={"threshold": PM2_5, "value_slots": []},
-                      pm10={"threshold": PM10, "value_slots": []},
-                      tsp={"threshold": TSP, "value_slots": []},
-                      time_slots=[]
-                      )
-    es_dic = es_process(es_res, fmat=fmt)
-    # 2. 组装数据
-    pm25_list = []
-    pm10_list = []
-    tsp_list = []
-    for slot in slots:
-        if slot in es_dic:
-            pm25_value = round_0(es_dic[slot]["pm25"].get("avg"))
-            pm10_value = round_0(es_dic[slot]["pm10"].get("avg"))
-            tsp_value = round_0(es_dic[slot]["tsp"].get("avg"))
-        else:
-            pm25_value, pm10_value, tsp_value = "", "", ""
-        pm25_list.append(pm25_value)
-        pm10_list.append(pm10_value)
-        tsp_list.append(tsp_value)
-    return pm25_list, pm10_list, tsp_list
-
-
-async def get_data_new15(tsp_id, start, end, slots, interval):
+async def get_tsp_data(tsp_id, start, end, slots, interval):
     if interval == 24 * 3600:
         sql = f'SELECT DATE_FORMAT(create_time,"%m-%d") date_time, ' \
               f'AVG(pm25_max) pm25,AVG(pm25_max) pm10,AVG(tsp_max) tsp ' \
@@ -210,7 +171,7 @@ async def get_contrast_data(tsp_id, start, end, slots):
 async def tsp_predict_deviation_service(tsp_id, start, end):
     interval, slots = time_format.time_pick_transf(start, end)
     # 实时数据
-    pm25, pm10, tsp = await get_data_new15(tsp_id, start, end, slots, interval)
+    pm25, pm10, tsp = await get_tsp_data(tsp_id, start, end, slots, interval)
     # 预测数据
     pm25_predict, pm10_predict, tsp_predict, date_predict = \
         await get_predict_data(tsp_id, start, end, slots)
@@ -220,24 +181,25 @@ async def tsp_predict_deviation_service(tsp_id, start, end):
         if value and pm25[index]:
             pm25_time.append(date_predict[index])
             pm25_list.append(
-                round(math.fabs((pm25[index]-value)/pm25[index]), 3))
+                round(math.fabs((pm25[index] - value) / pm25[index]), 3))
     for index, value in enumerate(pm10_predict):
         if value and pm10[index]:
             pm10_time.append(date_predict[index])
             pm10_list.append(
-                round(math.fabs((pm10[index]-value)/pm10[index]), 3))
+                round(math.fabs((pm10[index] - value) / pm10[index]), 3))
     for index, value in enumerate(tsp_predict):
         if value and tsp[index]:
             tsp_time.append(date_predict[index])
-            tsp_list.append(round(math.fabs((tsp[index]-value)/tsp[index]), 3))
+            tsp_list.append(
+                round(math.fabs((tsp[index] - value) / tsp[index]), 3))
     pm25_max, pm25_min, pm25_avg = "", "", ""
     if pm25_list:
         pm25_max, pm25_min = max(pm25_list), min(pm25_list)
-        pm25_avg = round(sum(pm25_list)/len(pm25_list), 3)
+        pm25_avg = round(sum(pm25_list) / len(pm25_list), 3)
     pm10_max, pm10_min, pm10_avg = "", "", ""
     if pm10_list:
         pm10_max, pm10_min = max(pm10_list), min(pm10_list)
-        pm10_avg = round(sum(pm10_list)/len(pm10_list), 3)
+        pm10_avg = round(sum(pm10_list) / len(pm10_list), 3)
     tsp_max, tsp_min, tsp_avg = "", "", ""
     if tsp_list:
         tsp_max, tsp_min = max(tsp_list), min(tsp_list)
@@ -245,12 +207,16 @@ async def tsp_predict_deviation_service(tsp_id, start, end):
 
     return TpdResp(pm2_5={
         "max": pm25_max, "min": pm25_min, "avg": pm25_avg,
-        "max_time": pm25_time[pm25_list.index(pm25_max)] if pm25_max != "" else "",
-        "min_time": pm25_time[pm25_list.index(pm25_min)] if pm25_min != "" else ""
+        "max_time": pm25_time[
+            pm25_list.index(pm25_max)] if pm25_max != "" else "",
+        "min_time": pm25_time[
+            pm25_list.index(pm25_min)] if pm25_min != "" else ""
     }, pm10={
         "max": pm10_max, "min": pm10_min, "avg": pm10_avg,
-        "max_time": pm10_time[pm10_list.index(pm10_max)] if pm10_max != "" else "",
-        "min_time": pm10_time[pm10_list.index(pm10_min)] if pm10_min != "" else "",
+        "max_time": pm10_time[
+            pm10_list.index(pm10_max)] if pm10_max != "" else "",
+        "min_time": pm10_time[
+            pm10_list.index(pm10_min)] if pm10_min != "" else "",
     }, tsp={
         "max": tsp_max, "min": tsp_min, "avg": tsp_avg,
         "max_time": tsp_time[tsp_list.index(tsp_max)] if tsp_max != "" else "",
@@ -262,7 +228,7 @@ async def tsp_predict_deviation_service(tsp_id, start, end):
 async def tsp_contrast_deviation_service(tsp_id, start, end):
     interval, slots = time_format.time_pick_transf(start, end)
     # 实时数据
-    pm25, pm10, tsp = await get_data_new15(tsp_id, start, end, slots, interval)
+    pm25, pm10, tsp = await get_tsp_data(tsp_id, start, end, slots, interval)
     # 对比数据
     pm25_contrast, pm10_contrast, date_contrast = \
         await get_contrast_data(tsp_id, start, end, slots)
@@ -288,112 +254,20 @@ async def tsp_contrast_deviation_service(tsp_id, start, end):
         pm10_avg = round(sum(pm10_list) / len(pm10_list), 3)
     return TcdResp(pm2_5={
         "max": pm25_max, "min": pm25_min, "avg": pm25_avg,
-        "max_time": pm25_time[pm25_list.index(pm25_max)] if pm25_max != "" else "",
-        "min_time": pm25_time[pm25_list.index(pm25_min)] if pm25_min != "" else ""
+        "max_time": pm25_time[
+            pm25_list.index(pm25_max)] if pm25_max != "" else "",
+        "min_time": pm25_time[
+            pm25_list.index(pm25_min)] if pm25_min != "" else ""
     }, pm10={
         "max": pm10_max, "min": pm10_min, "avg": pm10_avg,
-        "max_time": pm10_time[pm10_list.index(pm10_max)] if pm10_max != "" else "",
-        "min_time": pm10_time[pm10_list.index(pm10_min)] if pm10_min != "" else "",
+        "max_time": pm10_time[
+            pm10_list.index(pm10_max)] if pm10_max != "" else "",
+        "min_time": pm10_time[
+            pm10_list.index(pm10_min)] if pm10_min != "" else "",
     })
 
 
 async def tsp_index_statistics_service(tsp_id, start, end):
-    """TSP信息-指标统计"""
-    # 1. 查询es
-    es_res = await tsp_index_statistics(start, end, tsp_id)
-    if not es_res:
-        return TisResp()
-    # 2.1 pm25
-    # max
-    pm25_max = ""
-    pm25_max_time = ""
-    pm_25_max_hits = es_res["pm25_max"]["hits"]["hits"]
-    if pm_25_max_hits:
-        pm25_max = round_2(pm_25_max_hits[0]["_source"].get("pm25_max"))
-        pm25_max_time = esstr_to_dthoutstr(
-            pm_25_max_hits[0]["_source"].get("pm25_max_time"),
-            format="%Y-%m-%d %H:%M:%S")
-    # min
-    pm25_min = ""
-    pm25_min_time = ""
-    pm_25_min_hits = es_res["pm25_min"]["hits"]["hits"]
-    if pm_25_min_hits:
-        pm25_min = round_2(pm_25_min_hits[0]["_source"].get("pm25_min"))
-        pm25_min_time = esstr_to_dthoutstr(
-            pm_25_min_hits[0]["_source"].get("pm25_min_time"),
-            format="%Y-%m-%d %H:%M:%S")
-    # avg
-    pm25_avg = ""
-    if es_res["pm25_avg"].get("value"):
-        pm25_avg = round(es_res["pm25_avg"].get("value"))
-
-    # 2.2 pm10
-    # max
-    pm10_max = ""
-    pm10_max_time = ""
-    pm_10_max_hits = es_res["pm10_max"]["hits"]["hits"]
-    if pm_10_max_hits:
-        pm10_max = round_2(pm_10_max_hits[0]["_source"].get("pm10_max"))
-        pm10_max_time = esstr_to_dthoutstr(
-            pm_10_max_hits[0]["_source"].get("pm10_max_time"),
-            format="%Y-%m-%d %H:%M:%S")
-    # min
-    pm10_min = ""
-    pm10_min_time = ""
-    pm_10_min_hits = es_res["pm10_min"]["hits"]["hits"]
-    if pm_10_min_hits:
-        pm10_min = round_2(pm_10_min_hits[0]["_source"].get("pm10_min"))
-        pm10_min_time = esstr_to_dthoutstr(
-            pm_10_min_hits[0]["_source"].get("pm10_min_time"),
-            format="%Y-%m-%d %H:%M:%S")
-    # avg
-    pm10_avg = ""
-    if es_res["pm10_avg"].get("value"):
-        pm10_avg = round(es_res["pm10_avg"].get("value"))
-
-    # 2.3 tsp
-    # max
-    tsp_max = ""
-    tsp_max_time = ""
-    tsp_max_hits = es_res["tsp_max"]["hits"]["hits"]
-    if tsp_max_hits:
-        tsp_max = round_2(tsp_max_hits[0]["_source"].get("tsp_max"))
-        tsp_max_time = esstr_to_dthoutstr(
-            tsp_max_hits[0]["_source"].get("tsp_max_time"),
-            format="%Y-%m-%d %H:%M:%S")
-    # min
-    tsp_min = ""
-    tsp_min_time = ""
-    tsp_min_hits = es_res["tsp_min"]["hits"]["hits"]
-    if tsp_min_hits:
-        tsp_min = round_2(tsp_min_hits[0]["_source"].get("tsp_min"))
-        tsp_min_time = esstr_to_dthoutstr(
-            tsp_min_hits[0]["_source"].get("tsp_min_time"),
-            format="%Y-%m-%d %H:%M:%S")
-    # avg
-    tsp_avg = ""
-    if es_res["tsp_avg"].get("value"):
-        tsp_avg = round(es_res["tsp_avg"].get("value"))
-
-    return TisResp(pm2_5={"max": pm25_max,
-                          "max_time": pm25_max_time,
-                          "min": pm25_min,
-                          "min_time": pm25_min_time,
-                          "avg": pm25_avg},
-                   pm10={"max": pm10_max,
-                         "max_time": pm10_max_time,
-                         "min": pm10_min,
-                         "min_time": pm10_min_time,
-                         "avg": pm10_avg},
-                   tsp={"max": tsp_max,
-                        "max_time": tsp_max_time,
-                        "min": tsp_min,
-                        "min_time": tsp_min_time,
-                        "avg": tsp_avg},
-                   )
-
-
-async def tsp_index_statistics_service_new15(tsp_id, start, end):
     now = str(datetime.datetime.now())
     if start[:10] == now[:10] and end[:10] == now[:10]:
         table_name = "tsp_15min_record"
@@ -405,7 +279,7 @@ async def tsp_index_statistics_service_new15(tsp_id, start, end):
           f" FROM {table_name} where tsp_id=%s and create_time " \
           f"BETWEEN '{start}' and '{end}' ORDER BY create_time"
     async with MysqlUtil() as conn:
-        datas = await conn.fetchall(sql, args=(tsp_id, ))
+        datas = await conn.fetchall(sql, args=(tsp_id,))
     if not datas:
         return TisResp()
     df = pd.DataFrame(list(datas))
@@ -457,48 +331,6 @@ def get_max_min_time(df, max_value, name):
 
 
 async def day_env_service(cid):
-    """当日环境"""
-    # 需求逻辑
-    # 求每个tsp装置pm2.5,pm10,tsp的平均值
-    # 取平均值高的pm2.5,pm10,tsp
-    today_start, today_end, m_start, m_end = start_end_date()
-    # 1. 根据cid取tsp_id_list
-    tsp_list = await tsp_by_cid(cid)
-    tsp_id_list = [i["tsp_id"] for i in tsp_list]
-    # 2. 取es数据
-    es_res = await tsp_aggs_tsp_id(today_start, today_end, tsp_id_list)
-    if not es_res:
-        return DeResp(pm2_5={"data": "", "grade": ""},
-                      pm10={"data": "", "grade": ""},
-                      tsp={"data": "", "grade": ""})
-    pm2_5_max = 0
-    pm10_max = 0
-    tsp_max = 0
-    for info in es_res:
-        pm2_5 = round(info["pm25"]["value"])
-        if pm2_5 > pm2_5_max:
-            pm2_5_max = pm2_5
-
-        pm10 = round(info["pm10"]["value"])
-        if pm10 > pm10_max:
-            pm10_max = pm10
-
-        tsp = round(info["tsp"]["value"])
-        if tsp > tsp_max:
-            tsp_max = tsp
-    # 调用函数,获取等级
-    pm2_5_grade = pm2_5_trans_grade(pm2_5_max)
-    pm10_grade = pm10_trans_grade(pm10_max)
-    tsp_grade = tsp_trans_grade(tsp_max)
-    # 3. 返回
-    return DeResp(
-        pm2_5={"data": pm2_5_max, "grade": pm2_5_grade},
-        pm10={"data": pm10_max, "grade": pm10_grade},
-        tsp={"data": tsp_max, "grade": tsp_grade}
-    )
-
-
-async def day_env_service_new15(cid):
     """当日环境"""
     # 需求逻辑
     # 求每个tsp装置pm2.5,pm10,tsp的平均值
@@ -589,7 +421,7 @@ async def analysis_describe_service(cid, start, end, page_num, page_size,
             "is_effective": page["is_valid"],
             "message": page["effect"]
         })
-    effective_rate = f"{round(data['effect']/data['measures'],2)*100}%" \
+    effective_rate = f"{round(data['effect'] / data['measures'], 2) * 100}%" \
         if data['measures'] else 0
     return AdResp(
         all_count=data["measures"] or 0,

unify_api/modules/tsp_water/views/tsp.py

@@ -5,8 +5,7 @@ from unify_api.modules.tsp_water.components.drop_dust_cps import DtReq, \
 from unify_api.modules.tsp_water.service.tsp_service import \
     real_time_service, tsp_history_service, tsp_index_statistics_service, \
     day_env_service, stat_analysis_service, tsp_predict_deviation_service, \
-    tsp_contrast_deviation_service, analysis_describe_service, \
-    day_env_service_new15, tsp_index_statistics_service_new15
+    tsp_contrast_deviation_service, analysis_describe_service
 
 
 @summary("TSP信息-实时参数")
@@ -62,14 +61,13 @@ async def post_tsp_index_statistics(req, body: TisReq) -> TisResp:
     start = body.start
     end = body.end
     # return await tsp_index_statistics_service(tsp_id, start, end)
-    # return await tsp_index_statistics_service_new15(tsp_id, start, end)
     return TisResp(pm2_5={}, pm10={}, tsp={})
 
 
 @summary("当日环境")
 async def post_day_env(req, body: DeReq) -> DeResp:
     cid = body.cid
-    return await day_env_service_new15(cid)
+    return await day_env_service(cid)
 
 
 @summary("统计分析-扬尘")