timing

.woodpecker.yml

@@ -20,7 +20,7 @@ steps:
     when:
       - event: [push, tag]
   deploy:
-    image: quay.io/wollud1969/k8s-admin-helper:0.1.3
+    image: quay.io/wollud1969/k8s-admin-helper:0.2.1
     environment:
       KUBE_CONFIG_CONTENT:
         from_secret: kube_config

deployment/deploy-yml.tmpl

@@ -4,6 +4,8 @@ metadata:
   name: pv-stats
   labels:
     app: pv-stats
+  annotations:
+    secret.reloader.stakater.com/reload: pv-stats
 spec:
   replicas: 1
   selector:

deployment/deploy.sh

@@ -19,10 +19,11 @@ kubectl create namespace $NAMESPACE \
   -o yaml | \
   kubectl -f - apply
 
-SECRETS_FILE=`mktemp`
-gpg --decrypt --passphrase $GPG_PASSPHRASE --yes --batch --homedir /tmp/.gnupg --output $SECRETS_FILE secrets.asc
-. $SECRETS_FILE
-rm $SECRETS_FILE
+# SECRETS_FILE=`mktemp`
+# gpg --decrypt --passphrase $GPG_PASSPHRASE --yes --batch --homedir /tmp/.gnupg --output $SECRETS_FILE secrets.asc
+# . $SECRETS_FILE
+# rm $SECRETS_FILE
+eval "`cat secrets.asc | /usr/local/bin/decrypt-secrets.sh`"
 
 kubectl create secret generic pv-stats \
   --dry-run=client \

deployment/secrets.asc

@@ -1,15 +1,15 @@
 -----BEGIN PGP MESSAGE-----
 
-jA0ECQMCjSYtdE7M+rT/0sEmAbK6tjOB7cduweJyS3sULIl017BrOM1HGV1v4QkN
-NWtceKHpJEFmk1ZFh1EmyS724bDxtVLm8qJN4VzV+cLPa8/IiTzOHJEg4PDRcc0U
-LRCZOb5PtfKWBcQdRshT3JhIxxOKG53ZKOHJ2VodZ/iqmpSbjZ39GtzLJoXlXwCJ
-jHAHgADdvq5J7joSaozjxVCXQI2nOmlEcZosZVd6LZDvemWtmci4ARJtOEqad4Wi
-mbleupBF18pA7b63hfmHocO89b9pTpUZWw10b0SHrUiKZG6kHeQXE8GGu+4HiRcG
-xJN/yYe2Ly4tHwT54gQ7ytLrxOnJUQKelSpq370t/lrGTf8L4b2eq+tED8/7z5Ho
-E12VDreYLFaS2IeJCFBefiGGbKgttPcHZvDCPCUpCpfSShlqtTaidwsTq2lPFGyo
-0Lz9NHsqp4/U+4nabCWNVWhnZhwqIPYOt/kKsYvjq40U29q7RORnxz8l/Ym4vB1P
-kLeouElJvAz6vt/1+nFQJb65YykTqKQpbKgbziFiUFwb37QzBqRO7tuv3/MUzJ1Q
-KB7+IOQ43vFbAK6DZAhJZtAspVYiZ95niVxepaghzf33/FquhtZ+XpFEBDv525z7
-pML7BxFxuwF5q7HBTPtc4IeJBgGi16wm
-=K6Qq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Wr4f
 -----END PGP MESSAGE-----

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']
@@ -39,10 +40,8 @@ oidc = OpenIDConnect(app)
 def token_debug():
     # Access Token vom Identity Provider abrufen
     access_token = oidc.get_access_token()
-    id_token = oidc.credentials_store.get(oidc.user_loggedin)
     return json.dumps({
-        "access_token": access_token,
-        "id_token": id_token
+        "access_token": access_token
     })
 
 @app.route('/')
@@ -52,10 +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 - start_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",
@@ -68,22 +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 - start_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 - start_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%')