Update tasks.py

service/tasks.py

@@ -4,6 +4,7 @@ import catboost
 import geopandas as gpd
 import numpy as np
 import pandas as pd
+import shap
 import psycopg2
 import sqlalchemy
 from celery import shared_task
@@ -189,11 +190,20 @@ def raschet(table_name='service_placementpoint', need_time=True):
             status.status = 'Обучение inference 100%'
             current_pred = sum(y_infers) / 5
 
+            # расчет шапов
+            explainer = shap.TreeExplainer(model)
+            shap_values = explainer(X_inf.drop(columns=['id']))
+            shap_fields = pd.DataFrame(shap_values.values)
+            shap_fields.columns = X_inf.drop(columns=['id']).columns + '_shap'
+            shap_fields = shap_fields.drop(columns = ['age_day_shap'])
+            shap_fields['sum'] = abs(shap_fields).sum(axis=1)
+            shap_fields = round(shap_fields.iloc[:,:32].div(shap_fields['sum'], axis=0)*100, 2)
+
             # Обновление полей по результатам работы модели
             update_fields = pts_inf[
                 [
                     'id', 'age_day_init', 'status', 'fact', 'delta_current', 'delta_first', 'plan_current', 'plan_first',
-                    'prediction_first',
+                    'prediction_first', 'target_post_cnt', 'target_dist'
                 ]
             ]
             update_fields = update_fields.join(
@@ -252,8 +262,52 @@ def raschet(table_name='service_placementpoint', need_time=True):
             conn2 = None
             log_to_telegram('Не удалось подключиться к базе данных')
 
-        # prediction_current
         if conn2 is not None:
+            # апдейт шапов
+            update_fields_shap = pd.concat([shap_fields, update_fields[['id']]], axis=1)
+            update_records0 = []
+            for i in range(0, len(update_fields_shap)):
+                update_records1 = []
+                for n in list(update_fields_shap):
+                    update_records1.append(int(update_fields_shap[n][i]))
+                update_records0.append(tuple(update_records1))
+            shap_fields_name = str(list(shap_fields))[1:-1].replace("'", "").replace(',', '=%s,')
+            sql_update_query = f"""Update {table_name} set {shap_fields_name} = %s where id = %s"""
+            try:
+                psycopg2.extras.execute_batch(cursor, sql_update_query, update_records0)
+                conn2.commit()
+            except:
+                cursor.execute("ROLLBACK")
+                psycopg2.extras.execute_batch(cursor, sql_update_query, update_records0)
+                conn2.commit()
+
+            # target_post_cnt
+            update_records1 = []
+            for i in range(0, len(update_fields)):
+                update_records1.append((int(update_fields.target_post_cnt[i]), int(update_fields.id[i])))
+            sql_update_query = f"""Update {table_name} set target_post_cnt = %s where id = %s"""
+            try:
+                psycopg2.extras.execute_batch(cursor, sql_update_query, update_records1)
+                conn2.commit()
+            except:
+                cursor.execute("ROLLBACK")
+                psycopg2.extras.execute_batch(cursor, sql_update_query, update_records1)
+                conn2.commit()
+
+            # target_dist
+            update_records1 = []
+            for i in range(0, len(update_fields)):
+                update_records1.append((int(update_fields.target_dist[i]), int(update_fields.id[i])))
+            sql_update_query = f"""Update {table_name} set target_dist = %s where id = %s"""
+            try:
+                psycopg2.extras.execute_batch(cursor, sql_update_query, update_records1)
+                conn2.commit()
+            except:
+                cursor.execute("ROLLBACK")
+                psycopg2.extras.execute_batch(cursor, sql_update_query, update_records1)
+                conn2.commit()
+
+            # prediction_current
             update_records1 = []
             for i in range(0, len(update_fields)):
                 update_records1.append((int(update_fields.prediction_current[i]), int(update_fields.id[i])))