import kaleido, 2

.woodpecker.yml

@@ -13,14 +13,8 @@ steps:
       dockerfile: Dockerfile
     when:
       - event: [push, tag]
-  scan_image:
-    image: aquasec/trivy
-    commands:
-      - trivy image $FORGE_NAME/$CI_REPO:$CI_COMMIT_SHA --quiet --exit-code 1
-    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

@@ -1,17 +1,64 @@
-apiVersion: batch/v1
+apiVersion: apps/v1
-kind: CronJob
+kind: Deployment
 metadata:
-  name: pv-energy-calculator
+  name: pv-stats
-spec:
+  labels:
-  schedule: "15 * * * *"
+    app: pv-stats
-  jobTemplate:
+  annotations:
+    secret.reloader.stakater.com/reload: pv-stats
 spec:
+  replicas: 1
+  selector:
+    matchLabels:
+      app: pv-stats
   template:
+    metadata:
+      labels:
+        app: pv-stats
     spec:
-          restartPolicy: OnFailure
       containers:
-            - name: pv-energy-calculator
+        - name: pv-stats
           image: %IMAGE%
           envFrom:
             - secretRef: 
-                    name: pv-energy-calculator
+                name: pv-stats
+          ports:
+            - containerPort: 8080
+              protocol: TCP
+---
+apiVersion: v1
+kind: Service
+metadata:
+  name: pv-stats
+spec:
+  type: ClusterIP
+  selector:
+    app: pv-stats
+  ports:
+    - name: http
+      targetPort: 8080
+      port: 80
+---
+apiVersion: networking.k8s.io/v1
+kind: Ingress
+metadata:
+  name: pv-stats
+  annotations:
+    cert-manager.io/cluster-issuer: letsencrypt-production-http
+spec:
+  tls:
+    - hosts:
+        - pv-stats.hottis.de
+      secretName: pv-stats-cert
+  rules:
+    - host: pv-stats.hottis.de
+      http:
+        paths:
+          - path: /
+            pathType: Prefix
+            backend:
+              service:
+                name: pv-stats
+                port:
+                  number: 80
+

deployment/deploy.sh

@@ -9,7 +9,7 @@ if [ "$GPG_PASSPHRASE" == "" ]; then
   exit 1
 fi
 
-IMAGE_NAME=gitea.hottis.de/wn/mini_flask
+IMAGE_NAME=gitea.hottis.de/wn/pv-stats
 NAMESPACE=homea
 DEPLOYMENT_DIR=$PWD/deployment
 
@@ -19,20 +19,29 @@ kubectl create namespace $NAMESPACE \
   -o yaml | \
   kubectl -f - apply
 
-SECRETS_FILE=`mktemp`
+# SECRETS_FILE=`mktemp`
-gpg --decrypt --passphrase $GPG_PASSPHRASE --yes --batch --homedir /tmp/.gnupg --output $SECRETS_FILE secrets.asc
+# 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 mini_flask \
+kubectl create secret generic pv-stats \
   --dry-run=client \
   -o yaml \
   --save-config \
-  --from-env-file=<(sed 's/^export //g' $SECRETS_FILE) | \
+  --from-literal=REDIS_URL="$REDIS_URL" \
+  --from-literal=SECRET_KEY="$SECRET_KEY" \
+  --from-literal=PGPASSWORD="$PGPASSWORD" \
+  --from-literal=PGUSER="$PGUSER" \
+  --from-literal=PGHOST="$PGHOST" \
+  --from-literal=PGSSLMODE="$PGSSLMODE" \
+  --from-literal=PGDATABASE="$PGDATABASE" \
+  --from-literal=OIDC_CLIENT_SECRETS="$OIDC_CLIENT_SECRETS" | \
   kubectl apply -f - -n $NAMESPACE
-rm $SECRETS_FILE
 
-# cat $DEPLOYMENT_DIR/deploy-yml.tmpl | \
+cat $DEPLOYMENT_DIR/deploy-yml.tmpl | \
-#   sed -e 's,%IMAGE%,'$IMAGE_NAME':'$IMAGE_TAG','g | \
+  sed -e 's,%IMAGE%,'$IMAGE_NAME':'$IMAGE_TAG','g | \
-#   kubectl apply -f - -n $NAMESPACE
+  kubectl apply -f - -n $NAMESPACE
 
 popd > /dev/null
 

deployment/secrets.asc

@@ -1,15 +1,15 @@
 -----BEGIN PGP MESSAGE-----
 
-jA0ECQMCGiCDDKK8KgP/0sExAeQ99bvndkYa/C1rLsDj14oKDgqea1ylRMTSm3if
+jA0ECQMC4tvOFCp2PT7/0sE+AcZmiGwroHYdWW/vJA1sCoMrM2oW8xUc1KndDGto
-jUdbOyaNR0p0R32AS1wVlR9qxE1g/e/dCNmGjYQ0lqpyRwX6uqJFZ8KubZp0rRCV
+dFev2KcoZ4FRL9liCrJ7on773bZFCTDu2xiBNMeKF1p8drub1Ej5l61Oq15mLTYf
-40VpAfuu4eKE6NsxW8U4wlY5aDR21YUndoaHCwNQDgFV2exCDVeOsF1hyGgurWBG
+XjXknFiWWq4PTzhhy53zvDyIV5yIcGfjotpGC83/qH5CBWIcCw9PZHI5+uHRVRKL
-QeAtlCN+HV6t9Gg6KUXRlr89C/wdZkkYScVGXxqemqetGntGhS96u37EFzyjnDaD
+OpdTpekJ8ljPAGQ4F3vbOeBbG1PMoclx8r5SpKxLwQco2iaXd71dXHtPkEnLujd4
-P09d6LKOIuHnKHZgBcKUZSqkYYwlNk05Wum9FqoWQc8KgCMvMv0WQNaaQxkrRah5
+ZRCthVNVfxrIIRcTJfgxewz2oJWYF9008nmtxpKzqfBtNpFIdBtnTTVvv2lfcVuS
-DRgyXkNYrDg3WGt7357H3LO+IP1gTVAyjEsZl0OpazXLKGfrsWis+191t9omXk+x
+S4eav9ljPPd/exZaT7fOGD/kuCdiiu6e0yGLzo2ykf0uBy7hG7ZJg8TH5e+LMBm9
-Y9g/dx1aSqgeIQ3SiTpjdHHItSYcJ+ZYvJy+4u6FeKFrk/5Z9nBA0LxEmo5ObGmg
+Q1OFD+5LWeEsOEdSTlT5UbV5EaVEiawKWQn7rMZOyvBNiPwLaOlquHirWoll5eIm
-SrMCnzU1/JDCsAEp8mvAMQWFjJUrgUMUHM00uFm32Nq6SOAT50rW4/XIxak2w6/x
+OHgBVN0FiY/righpIoei/KP705FIg+hrpMUvc29PahiL8dgsxJycnKIo4t+2/nac
-Zi7j3kxD6dfEXAeGRqCbDeTPQHNWPlvq0Rez2uaYA8w8S1hNoS8iSOSUbBoMCdFK
+H144hP/rqBeaobG05TkZIr+Cpt4rpwwfNWOHgmNFHVpxdmPfoeAmpT4nz760hTEN
-k61VApVRty0g35IsemcEuocIBw3YLWLLngHk7/xpKKWjbFO9H5AmxZT6FKcq7BwK
+2ol4Qh8xL7n4GFiCpNg8tNZiZkPPa/aRUAFxgdq5beossvKukxCexQmlCFvxITSG
-Q4DPHAmHDSCniiMzdcbcH7Y8GvO8q9jFPfQWE5MDETVlQ7Q=
+x9RwssFMnT+wqTuzBN8neBeEF1d9AtAFQKPtg3wkMUyJAlYkxiGS/2NJuYDVpmEQ
-=gOlN
+=Wr4f
 -----END PGP MESSAGE-----

src/requirements.txt

@@ -10,10 +10,13 @@ cryptography==44.0.0
 Flask==3.1.0
 flask-oidc==2.2.2
 Flask-Session==0.8.0
+greenlet==3.1.1
+gunicorn==23.0.0
 idna==3.10
 importlib_metadata==8.6.1
 itsdangerous==2.2.0
 Jinja2==3.1.5
+kaleido==1.0.0rc0
 loguru==0.7.3
 MarkupSafe==3.0.2
 msgspec==0.19.0

src/run.py

@@ -1,15 +1,20 @@
-from flask import Flask, session, g, render_template_string
+from flask import Flask, session, g, render_template_string, Response
 from flask_session import Session
 from flask_oidc import OpenIDConnect
+import kaleido
 from werkzeug.middleware.proxy_fix import ProxyFix
 from loguru import logger
 import redis
 import json
 import os
 import plotly.express as px
+import plotly.graph_objects as po
+import plotly.io as pio
+import io
 import pandas as pd
 import psycopg
 import sqlalchemy
+import time
 
 try:
   redis_url = os.environ['REDIS_URL']
@@ -34,25 +39,35 @@ app.config.update({
 Session(app)
 oidc = OpenIDConnect(app)
 
+@app.route('/token_debug', methods=['GET'])
+@oidc.require_login
+def token_debug():
+    # Access Token vom Identity Provider abrufen
+    access_token = oidc.get_access_token()
+    return json.dumps({
+        "access_token": access_token
+    })
+
 @app.route('/')
 @oidc.require_login
 def index():
-    counter = int(session.get('counter', '0'))
-    counter += 1
-    session['counter'] = f"{counter}"
-    return f"Hello, Flask! Called for the {counter}. time."
-
-@app.route('/plot')
-@oidc.require_login
-def plot():
     try:
+        stepX_time = time.time()
         dbh = psycopg.connect()
         engine = sqlalchemy.create_engine("postgresql+psycopg://", creator=lambda: dbh)
+
+        step0_time = time.time()
         df = pd.read_sql("SELECT month, cast(year AS varchar), current_energy AS value FROM pv_energy_by_month", con=engine)
-        fig = px.bar(df, x='month', y='value', color='year', barmode='group')
+        step1_time = time.time()
-        fig.update_layout(
+        duration1 = step1_time - step0_time
-            title="Jahreswerte Exportierte Energie",
+        logger.info(f"{duration1=}")
-            xaxis_title="Monat",
+        fig_1 = px.bar(df, x='month', y='value', color='year', barmode='group')
+        step2_time = time.time()
+        duration2 = step2_time - step1_time
+        logger.info(f"{duration2=}")
+        fig_1.update_layout(
+            title=f"Jahreswerte Exportierte Energie {duration1:.3f}, {duration2:.3f}",
+            xaxis_title="",
             yaxis_title="",
             legend_title="Jahr",
             xaxis=dict(
@@ -62,7 +77,44 @@ def plot():
             ),
             yaxis=dict(ticksuffix=" kWh")
         )
-        graph_html = fig.to_html(full_html=False)
+        graph_html_1 = fig_1.to_html(full_html=False, default_height='30%')
+
+        step3_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)
+        step4_time = time.time()
+        duration3 = step4_time - step3_time
+        logger.info(f"{duration3=}")
+        fig_2 = px.line(df, x='bucket', y='avg_power')
+        step5_time = time.time()
+        duration4 = step5_time - step4_time
+        logger.info(f"{duration4=}")
+        fig_2.update_layout(
+            xaxis_title="",
+            yaxis_title="",
+            title=f"Export gestern {duration3:.3f}, {duration4:.3f}",
+            yaxis=dict(ticksuffix=" W")
+        )
+        graph_html_2 = fig_2.to_html(full_html=False, default_height='30%')
+
+        step6_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)
+        step7_time = time.time()
+        duration5 = step7_time - step6_time
+        logger.info(f"{duration5=}")
+        fig_3 = px.line(df, x='bucket', y='avg_power')
+        step8_time = time.time()
+        duration6 = step8_time - step7_time
+        logger.info(f"{duration6=}")
+        fig_3.update_layout(
+            xaxis_title="",
+            yaxis_title="",
+            title=f"Export heute {duration5:.3f}, {duration6:.3f}",
+            yaxis=dict(ticksuffix=" W")
+        )
+        graph_html_3 = fig_3.to_html(full_html=False, default_height='30%')
+        stepZ_time = time.time()
+        duration7 = stepZ_time - stepX_time
+        logger.info(f"{duration7=}")
 
         return render_template_string(f"""
             <html>
@@ -70,7 +122,26 @@ def plot():
                     <title>Jahreswerte PV-Energie</title>
                 </head>
                 <body>
-                    {graph_html}
+                    {graph_html_1}
+                    {graph_html_2}
+                    {graph_html_3}
+                    <div style="height:9vh; background-color:lightgrey; font-family: Courier, Consolas, monospace;">
+                      <table style="border-collapse: collapse;">
+                        <style>
+                          td.smallsep {{ padding-right: 10px }}
+                          td.largesep {{ padding-right: 30px }}
+                        </style> 
+                        <tr>
+                          <td class="smallsep">Query 1:</td><td class="largesep"> {duration1:.3f} s</td><td class="smallsep">Graph 1:</td><td> {duration2:.3f} s</td>
+                        </tr><tr>
+                          <td class="smallsep">Query 2:</td><td class="largesep"> {duration3:.3f} s</td><td class="smallsep">Graph 2:</td><td> {duration4:.3f} s</td>
+                        </tr><tr>
+                          <td class="smallsep">Query 3:</td><td class="largesep"> {duration5:.3f} s</td><td class="smallsep">Graph 3:</td><td> {duration6:.3f} s</td>
+                        </tr><tr>
+                          <td class="smallsep">Total:</td><td> {duration7:.3f} s</td><td></td><td></td>
+                        </tr>
+                      </table>   
+                    </div>
                 </body>
             </html>
         """)
@@ -81,6 +152,60 @@ def plot():
             dbh.close()
 
 
+@app.route('/ntpserver')
+def ntpserver():
+    try:
+        dbh = psycopg.connect()
+        engine = sqlalchemy.create_engine("postgresql+psycopg://", creator=lambda: dbh)
+
+        query = """
+          select   time_bucket('5 minutes', time) as bucket,
+            device,
+            avg(cast(values->'rootdisp'->>'value'  as float)) as rootdisp,
+            avg(cast(values->'stratum'->>'value'  as int)) as stratum
+          from measurements
+          where time >= date_trunc('day', now()) AND time < date_trunc('day', now()) + '1 day'::interval and 
+            application = 'TSM' and attributes->>'Label' = 'david'
+          group by bucket, device
+          order by bucket, device
+        """      
+
+        df = pd.read_sql(query, con=engine)
+
+        fig = po.Figure()
+        fig.add_trace(po.Scatter(x=df['bucket'], y=df['rootdisp'], mode='lines', name='Root Dispersion', yaxis='y1', line=dict(color='red')))
+        fig.add_trace(po.Scatter(x=df['bucket'], y=df['stratum'], mode='lines', name='Stratum', yaxis='y2', line=dict(color='blue')))
+
+        fig.update_layout(
+            # Linke Y-Achse
+            yaxis=dict(
+                title='Root Dispersion'
+            ),
+            
+            # Rechte Y-Achse
+            yaxis2=dict(
+                title='Stratum',
+                overlaying='y',  # Legt die zweite Y-Achse über die erste
+                side='right',  # Setzt sie auf die rechte Seite
+                tickmode='linear',  # Stellt sicher, dass die Ticks in festen Intervallen sind
+                dtick=1,  # Zeigt nur ganzzahlige Ticks
+            ),
+            
+            legend=dict(x=0.05, y=1)  # Position der Legende
+        )
+
+        img = fig.to_image(format='png')
+        return Response(img, mimetype='image/png')
+
+    except Exception as e:
+        raise Exception(f"Error when querying NTP server values: {e}")
+    finally:
+        if dbh is not None:
+            dbh.close()
+
+
+
+
 
 
 if __name__ == '__main__':