timing

src/run.py

@@ -10,6 +10,7 @@ import plotly.express as px
 import pandas as pd
 import psycopg
 import sqlalchemy
+import time
 
 try:
   redis_url = os.environ['REDIS_URL']
@@ -50,10 +51,15 @@ def index():
         dbh = psycopg.connect()
         engine = sqlalchemy.create_engine("postgresql+psycopg://", creator=lambda: dbh)
 
+        start_time = time.time()
         df = pd.read_sql("SELECT month, cast(year AS varchar), current_energy AS value FROM pv_energy_by_month", con=engine)
+        step1_time = time.time()
+        duration1 = step1_time - start_time
         fig_1 = px.bar(df, x='month', y='value', color='year', barmode='group')
+        step2_time = time.time()
+        duration2 = step2_time - step1_time
         fig_1.update_layout(
-            title="Jahreswerte Exportierte Energie",
+            title=f"Jahreswerte Exportierte Energie {duration1:.3f}, {duration2:.3f}",
             xaxis_title="",
             yaxis_title="",
             legend_title="Jahr",
@@ -66,22 +72,32 @@ def index():
         )
         graph_html_1 = fig_1.to_html(full_html=False, default_height='33%')
 
+        start_time = time.time()
         df = pd.read_sql("SELECT time_bucket('5 minutes', time) AS bucket, AVG(power) AS avg_power FROM pv_power_v WHERE time >= date_trunc('day', now()) - '1 day'::interval AND time < date_trunc('day', now()) GROUP BY bucket ORDER BY bucket", con=engine)
+        step1_time = time.time()
+        duration1 = step1_time - start_time
         fig_2 = px.line(df, x='bucket', y='avg_power')
+        step2_time = time.time()
+        duration2 = step2_time - step1_time
         fig_2.update_layout(
             xaxis_title="",
             yaxis_title="",
-            title="Export gestern",
+            title=f"Export gestern {duration1:.3f}, {duration2:.3f}",
             yaxis=dict(ticksuffix=" W")
         )
         graph_html_2 = fig_2.to_html(full_html=False, default_height='33%')
 
+        start_time = time.time()
         df = pd.read_sql("SELECT time_bucket('5 minutes', time) AS bucket, AVG(power) AS avg_power FROM pv_power_v WHERE time >= date_trunc('day', now()) AND time < date_trunc('day', now()) + '1 day'::interval GROUP BY bucket ORDER BY bucket", con=engine)
+        step1_time = time.time()
+        duration1 = step1_time - start_time
         fig_3 = px.line(df, x='bucket', y='avg_power')
+        step2_time = time.time()
+        duration2 = step2_time - step1_time
         fig_3.update_layout(
             xaxis_title="",
             yaxis_title="",
-            title="Export heute",
+            title=f"Export heute {duration1:.3f}, {duration2:.3f}",
             yaxis=dict(ticksuffix=" W")
         )
         graph_html_3 = fig_3.to_html(full_html=False, default_height='33%')