stuff

app.py

@@ -5,6 +5,7 @@ import tempfile
 import hopsworks
 from xgboost import XGBRegressor
 from datetime import datetime, timedelta
+import numpy as np
 
 from airquality.util import plot_air_quality_forecast
 
@@ -49,13 +50,16 @@ def load_resources_v2():
 
     return model, fv, weather_fg, project
 
+resources_v1 = load_resources_v1()
+resources_v2 = load_resources_v2()
+
 
 
 # -------------------------
 # FORECAST LOGIC (NEXT 7 DAYS)
 # -------------------------
 def generate_forecast_v1(days):
-    model, fv, weather_fg, project = load_resources_v1()
+    model, fv, weather_fg, project = resources_v1
 
     today = datetime.utcnow().date()
     df_future = weather_fg.read()
@@ -81,9 +85,11 @@ def generate_forecast_v1(days):
     tmp_path = tempfile.NamedTemporaryFile(suffix=".png", delete=False).name
     plot_air_quality_forecast("linkoping", "hamngatan-10", df_preds, tmp_path)
 
+    return tmp_path
+
 
 def generate_forecast_v2(days):
-    model, fv, weather_fg, project = load_resources_v2()
+    model, fv, weather_fg, project = resources_v2
 
     today = datetime.utcnow().date()
     df_future = weather_fg.read().sort_values("date")
@@ -134,7 +140,7 @@ def generate_forecast_v2(days):
 # HINDCAST LOGIC (LAST 7 DAYS)
 # -------------------------
 def generate_hindcast_v1(days):
-    model, fv, weather_fg, project = load_resources_v1()
+    model, fv, weather_fg, project = resources_v1
 
     features_df, labels_df = fv.training_data(
         start_time=datetime.utcnow().date() - timedelta(days=days),
@@ -156,7 +162,7 @@ def generate_hindcast_v1(days):
 
 
 def generate_hindcast_v2(days):
-    model, fv, weather_fg, project = load_resources_v2()
+    model, fv, weather_fg, project = resources_v2
 
     features_df, labels_df = fv.training_data(
         start_time=datetime.utcnow().date() - timedelta(days=days),