fix20230223

apps/view_map/view.py

@@ -68,13 +68,14 @@ def attract_map():
             provinces = [i[0] for i in provinces if i[0]]  # 拿到省份的无重复值
             for pro in provinces:
                 num = enterprise.filter_by(province=pro).count()
-                province_data = Enterprise.query.filter_by(province=pro).first()
+                # province_data = Enterprise.query.filter_by(province=pro).first()
                 df.append({"name": pro,
                            "value": num,
                            "color": jishu(num),
                            # "jwd": {"lng": province_data.p_lng, "lat": province_data.p_lat}})
                            })
-
+            # redis缓存
+            redis_store.setex(name_query, 30 * 24 * 3600, json.dumps(df))
             return jsonify(code=RET.OK, msg="获取成功", data=df)
         if province and not city:  # 省-》市数据
             cities = Enterprise.query.filter_by(province=province).with_entities(Enterprise.city).distinct().all()
@@ -87,7 +88,8 @@ def attract_map():
                            "color": jishu(num),
                            # "jwd": {"lng": city_data.c_lng, "lat": city_data.c_lat}})
                            })
-
+            # redis缓存
+            redis_store.setex(name_query, 30 * 24 * 3600, json.dumps(df))
             return jsonify(code=RET.OK, msg="获取成功", data=df)
         if province and city and not district:  # 市-》区数据
             districts = Enterprise.query.filter_by(province=province, city=city).with_entities(
@@ -101,7 +103,8 @@ def attract_map():
                            "color": jishu(num),
                            # "jwd": {"lng": district_data.d_lng, "lat": district_data.d_lat}})
                            })
-
+            # redis缓存
+            redis_store.setex(name_query, 30 * 24 * 3600, json.dumps(df))
             return jsonify(code=RET.OK, msg="获取成功", data=df)
         if province and city and district:  # 区数据
             num = enterprise.filter_by(province=province, city=city, district=district).count()