Compare commits
19 Commits
Author | SHA1 | Date | |
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8bef6d676c | |||
813265f8ee | |||
b47070cfc2 | |||
92ef3e6a85 | |||
a63776fb3f | |||
e24a29e94f | |||
b3c2c7794a | |||
7ff1b70098 | |||
aa4c307048 | |||
19672e6106 | |||
97e9d3e4e5 | |||
0914a91fa0 | |||
a972916704
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1774bb11aa
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d19ac55dea
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4db989022e
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af76406afa
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d85c32247e
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ba7b86e527
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@ -1,4 +1,4 @@
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FROM python:3.11-alpine3.21
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FROM python:3.12-alpine3.21
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||||||
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ENV REDIS_URL=""
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ENV REDIS_URL=""
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ENV SECRET_KEY=""
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ENV SECRET_KEY=""
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40
debug-build-run.sh
Executable file
40
debug-build-run.sh
Executable file
@ -0,0 +1,40 @@
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#!/bin/bash
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set -x
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IMAGE_NAME=numberimage
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docker build --progress=plain -t $IMAGE_NAME .
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SECRETS=`mktemp`
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gpg --decrypt --passphrase $GPG_PASSPHRASE --yes --batch --output $SECRETS ./deployment/secrets.asc
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. $SECRETS
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rm $SECRETS
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DB_NAMESPACE=database1
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DB_DEPLOYNAME=database
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REDIS_NAMESPACE=redis
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REDIS_SERVICE_NAME=redis
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PGHOST=`kubectl get services $DB_DEPLOYNAME -n $DB_NAMESPACE -o jsonpath="{.status.loadBalancer.ingress[0].ip}"`
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REDISHOST=`kubectl get services $REDIS_SERVICE_NAME -n $REDIS_NAMESPACE -o jsonpath="{.status.loadBalancer.ingress[0].ip}"`
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REDIS_URL=redis://$REDISHOST:6379/4
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docker run \
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-it \
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--rm \
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-e "REDIS_URL=$REDIS_URL" \
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-e "SECRET_KEY=$SECRET_KEY" \
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-e "OIDC_CLIENT_SECRETS=$OIDC_CLIENT_SECRETS" \
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-e "PGHOST=$PGHOST" \
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-e "PGDATABASE=$PGDATABASE" \
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-e "PGSSLMODE=$PGSSLMODE" \
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-e "PGUSER=$PGUSER" \
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-e "PGPASSWORD=$PGPASSWORD" \
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-p 8080:8080 \
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$IMAGE_NAME
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@ -1,27 +1,27 @@
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apiVersion: apps/v1
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apiVersion: apps/v1
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kind: Deployment
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kind: Deployment
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metadata:
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metadata:
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name: pv-stats
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name: numbers
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labels:
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labels:
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app: pv-stats
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app: numbers
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annotations:
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annotations:
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secret.reloader.stakater.com/reload: pv-stats
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secret.reloader.stakater.com/reload: numbers
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spec:
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spec:
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replicas: 1
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replicas: 1
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selector:
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selector:
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matchLabels:
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matchLabels:
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app: pv-stats
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app: numbers
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template:
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template:
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metadata:
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metadata:
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labels:
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labels:
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app: pv-stats
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app: numbers
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spec:
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spec:
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containers:
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containers:
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- name: pv-stats
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- name: numbers
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image: %IMAGE%
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image: %IMAGE%
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envFrom:
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envFrom:
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- secretRef:
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- secretRef:
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name: pv-stats
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name: numbers
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ports:
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ports:
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- containerPort: 8080
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- containerPort: 8080
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protocol: TCP
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protocol: TCP
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@ -29,11 +29,11 @@ spec:
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apiVersion: v1
|
apiVersion: v1
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kind: Service
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kind: Service
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metadata:
|
metadata:
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name: pv-stats
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name: numbers
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spec:
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spec:
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type: ClusterIP
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type: ClusterIP
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selector:
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selector:
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app: pv-stats
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app: numbers
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ports:
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ports:
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- name: http
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- name: http
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targetPort: 8080
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targetPort: 8080
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@ -42,23 +42,23 @@ spec:
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apiVersion: networking.k8s.io/v1
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apiVersion: networking.k8s.io/v1
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kind: Ingress
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kind: Ingress
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metadata:
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metadata:
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name: pv-stats
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name: numbers
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annotations:
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annotations:
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cert-manager.io/cluster-issuer: letsencrypt-production-http
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cert-manager.io/cluster-issuer: letsencrypt-production-http
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spec:
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spec:
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tls:
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tls:
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- hosts:
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- hosts:
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- pv-stats.hottis.de
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- numbers.hottis.de
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secretName: pv-stats-cert
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secretName: numbers-cert
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rules:
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rules:
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- host: pv-stats.hottis.de
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- host: numbers.hottis.de
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http:
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http:
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paths:
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paths:
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- path: /
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- path: /
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pathType: Prefix
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pathType: Prefix
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backend:
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backend:
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service:
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service:
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name: pv-stats
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name: numbers
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port:
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port:
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number: 80
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number: 80
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@ -9,7 +9,7 @@ if [ "$GPG_PASSPHRASE" == "" ]; then
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exit 1
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exit 1
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fi
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fi
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IMAGE_NAME=gitea.hottis.de/wn/pv-stats
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IMAGE_NAME=gitea.hottis.de/wn/numbers
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NAMESPACE=homea
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NAMESPACE=homea
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DEPLOYMENT_DIR=$PWD/deployment
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DEPLOYMENT_DIR=$PWD/deployment
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@ -25,7 +25,7 @@ kubectl create namespace $NAMESPACE \
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# rm $SECRETS_FILE
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# rm $SECRETS_FILE
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eval "`cat secrets.asc | /usr/local/bin/decrypt-secrets.sh`"
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eval "`cat secrets.asc | /usr/local/bin/decrypt-secrets.sh`"
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kubectl create secret generic pv-stats \
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kubectl create secret generic numbers \
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--dry-run=client \
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--dry-run=client \
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-o yaml \
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-o yaml \
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--save-config \
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--save-config \
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32
src/app.py
Normal file
32
src/app.py
Normal file
@ -0,0 +1,32 @@
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from flask import Flask, session, g, render_template_string
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from flask_session import Session
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from flask_oidc import OpenIDConnect
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from werkzeug.middleware.proxy_fix import ProxyFix
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from loguru import logger
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import redis
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import json
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import os
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|
try:
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redis_url = os.environ['REDIS_URL']
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oidc_client_secrets = os.environ['OIDC_CLIENT_SECRETS']
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secret_key = os.environ['SECRET_KEY']
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|
except KeyError as e:
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logger.error(f"Required environment variable not set ({e})")
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raise e
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app = Flask(__name__)
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app.config.update({
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'SECRET_KEY': secret_key,
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'SESSION_TYPE': 'redis',
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'SESSION_REDIS': redis.from_url(redis_url),
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'OIDC_CLIENT_SECRETS': json.loads(oidc_client_secrets),
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'OIDC_SCOPES': 'openid email',
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'OIDC_USER_INFO_ENABLED': True,
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'SESSION_USE_SIGNER': True,
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|
})
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|
Session(app)
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|
oidc = OpenIDConnect(app)
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|
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|
|
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|
|
16
src/debug_routes.py
Normal file
16
src/debug_routes.py
Normal file
@ -0,0 +1,16 @@
|
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|
from loguru import logger
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|
import json
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|
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|
from app import app
|
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from app import oidc
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|
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|
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|
@app.route('/token_debug', methods=['GET'])
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|
@oidc.require_login
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|
def token_debug():
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|
# Access Token vom Identity Provider abrufen
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|
access_token = oidc.get_access_token()
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|
return json.dumps({
|
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|
"access_token": access_token
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|
})
|
||||||
|
|
161
src/ntp_routes.py
Normal file
161
src/ntp_routes.py
Normal file
@ -0,0 +1,161 @@
|
|||||||
|
from flask import Flask, session, g, render_template_string
|
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|
from loguru import logger
|
||||||
|
import json
|
||||||
|
import plotly.express as px
|
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|
import plotly.graph_objects as po
|
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|
import matplotlib.pyplot as plt
|
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|
import pandas as pd
|
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|
import psycopg
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|
import sqlalchemy
|
||||||
|
import time
|
||||||
|
|
||||||
|
from app import app
|
||||||
|
from app import oidc
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
@app.route('/ntpserver')
|
||||||
|
def ntpserver():
|
||||||
|
try:
|
||||||
|
dbh = psycopg.connect()
|
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|
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,
|
||||||
|
max(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(
|
||||||
|
title='NTP Server Numbers',
|
||||||
|
|
||||||
|
# Linke Y-Achse
|
||||||
|
yaxis=dict(
|
||||||
|
title='Root Dispersion',
|
||||||
|
ticksuffix=' ms'
|
||||||
|
),
|
||||||
|
|
||||||
|
# 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
|
||||||
|
)
|
||||||
|
|
||||||
|
graph_html_1 = fig.to_html(full_html=False, default_height='30%')
|
||||||
|
|
||||||
|
query = """
|
||||||
|
select time_bucket('5 minutes', time) as bucket,
|
||||||
|
device,
|
||||||
|
avg(cast(values->'time-req-pkts'->>'value' as float)) as packets
|
||||||
|
from measurements
|
||||||
|
where time >= date_trunc('day', now()) AND time < date_trunc('day', now()) + '1 day'::interval and
|
||||||
|
application = 'SNMP' and attributes->>'Label' = 'david'
|
||||||
|
group by bucket, device
|
||||||
|
order by bucket, device
|
||||||
|
"""
|
||||||
|
df = pd.read_sql(query, con=engine)
|
||||||
|
fig_2 = px.line(df, x='bucket', y='packets')
|
||||||
|
fig_2.update_layout(
|
||||||
|
xaxis_title="",
|
||||||
|
yaxis_title="",
|
||||||
|
yaxis_ticksuffix="p/s",
|
||||||
|
title=f"Time Requests"
|
||||||
|
)
|
||||||
|
graph_html_2 = fig_2.to_html(full_html=False, default_height='30%')
|
||||||
|
|
||||||
|
query = """
|
||||||
|
select time_bucket('5 minutes', time) as bucket,
|
||||||
|
device,
|
||||||
|
avg(cast(values->'load1'->>'value' as float)) as loadaverage1min
|
||||||
|
from measurements
|
||||||
|
where time >= date_trunc('day', now()) AND time < date_trunc('day', now()) + '1 day'::interval and
|
||||||
|
application = 'SNMP' and attributes->>'Label' = 'david'
|
||||||
|
group by bucket, device
|
||||||
|
order by bucket, device
|
||||||
|
"""
|
||||||
|
df = pd.read_sql(query, con=engine)
|
||||||
|
fig_3 = px.line(df, x='bucket', y='loadaverage1min')
|
||||||
|
fig_3.update_layout(
|
||||||
|
xaxis_title="",
|
||||||
|
yaxis_title="",
|
||||||
|
title=f"CPU Load"
|
||||||
|
)
|
||||||
|
graph_html_3 = fig_3.to_html(full_html=False, default_height='30%')
|
||||||
|
|
||||||
|
return render_template_string(f"""
|
||||||
|
<html>
|
||||||
|
<head>
|
||||||
|
<title>NTP Server Numbers</title>
|
||||||
|
</head>
|
||||||
|
<body>
|
||||||
|
{graph_html_1}
|
||||||
|
{graph_html_2}
|
||||||
|
{graph_html_3}
|
||||||
|
</body>
|
||||||
|
</html>
|
||||||
|
""")
|
||||||
|
except Exception as e:
|
||||||
|
raise Exception(f"Error when querying NTP server values: {e}")
|
||||||
|
finally:
|
||||||
|
if dbh is not None:
|
||||||
|
dbh.close()
|
||||||
|
|
||||||
|
|
||||||
|
@app.route('/plot.png')
|
||||||
|
def plot_png():
|
||||||
|
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,
|
||||||
|
max(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, ax1 = plt.subplots()
|
||||||
|
|
||||||
|
ax1.plot(df['bucket'], df['rootdisp'], 'r-', label='Root Dispersion')
|
||||||
|
ax1.set_xlabel('Time')
|
||||||
|
ax1.set_ylabel('Root Dispersion (ms)', color='r')
|
||||||
|
ax1.tick_params(axis='y', labelcolor='r')
|
||||||
|
|
||||||
|
ax2 = ax1.twinx()
|
||||||
|
ax2.plot(df['bucket'], df['stratum'], 'b-', label='Stratum')
|
||||||
|
ax2.set_ylabel('Stratum', color='b')
|
||||||
|
ax2.tick_params(axis='y', labelcolor='b')
|
||||||
|
ax2.set_yticks(range(int(df['stratum'].min()), int(df['stratum'].max()) + 1))
|
||||||
|
|
||||||
|
fig.suptitle('NTP Server Numbers')
|
||||||
|
fig.tight_layout()
|
||||||
|
|
||||||
|
img_io = io.BytesIO()
|
||||||
|
plt.savefig(img_io, format='png')
|
||||||
|
img_io.seek(0)
|
||||||
|
plt.close(fig)
|
||||||
|
|
||||||
|
return Response(img_io, mimetype='image/png')
|
||||||
|
|
117
src/pv_routes.py
Normal file
117
src/pv_routes.py
Normal file
@ -0,0 +1,117 @@
|
|||||||
|
from flask import Flask, session, g, render_template_string
|
||||||
|
from loguru import logger
|
||||||
|
import json
|
||||||
|
import plotly.express as px
|
||||||
|
import plotly.graph_objects as po
|
||||||
|
import pandas as pd
|
||||||
|
import psycopg
|
||||||
|
import sqlalchemy
|
||||||
|
import time
|
||||||
|
|
||||||
|
from app import app
|
||||||
|
from app import oidc
|
||||||
|
|
||||||
|
|
||||||
|
@app.route('/pvstats')
|
||||||
|
@oidc.require_login
|
||||||
|
def pvstats():
|
||||||
|
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)
|
||||||
|
step1_time = time.time()
|
||||||
|
duration1 = step1_time - step0_time
|
||||||
|
logger.info(f"{duration1=}")
|
||||||
|
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(
|
||||||
|
tickmode="array",
|
||||||
|
tickvals=list(range(1, 13)), # Monate 1–12
|
||||||
|
ticktext=["Jan", "Feb", "Mär", "Apr", "Mai", "Jun", "Jul", "Aug", "Sep", "Okt", "Nov", "Dez"]
|
||||||
|
),
|
||||||
|
yaxis=dict(ticksuffix=" kWh")
|
||||||
|
)
|
||||||
|
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>
|
||||||
|
<head>
|
||||||
|
<title>Jahreswerte PV-Energie</title>
|
||||||
|
</head>
|
||||||
|
<body>
|
||||||
|
{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>
|
||||||
|
""")
|
||||||
|
except Exception as e:
|
||||||
|
raise Exception(f"Error when querying energy export values: {e}")
|
||||||
|
finally:
|
||||||
|
if dbh is not None:
|
||||||
|
dbh.close()
|
||||||
|
|
@ -38,3 +38,6 @@ tzdata==2025.1
|
|||||||
urllib3==2.3.0
|
urllib3==2.3.0
|
||||||
Werkzeug==3.1.3
|
Werkzeug==3.1.3
|
||||||
zipp==3.21.0
|
zipp==3.21.0
|
||||||
|
pillow==11.1.0
|
||||||
|
matplotlib==3.10.1
|
||||||
|
|
||||||
|
24
src/routes.py
Normal file
24
src/routes.py
Normal file
@ -0,0 +1,24 @@
|
|||||||
|
from flask import abort, Response
|
||||||
|
from PIL import Image, ImageDraw
|
||||||
|
import io
|
||||||
|
from app import app
|
||||||
|
from app import oidc
|
||||||
|
|
||||||
|
|
||||||
|
@app.route('/')
|
||||||
|
def index():
|
||||||
|
abort(404)
|
||||||
|
|
||||||
|
@app.route('/generate_image')
|
||||||
|
def generate_image():
|
||||||
|
img = Image.new('RGB', (200, 100), color=(255, 255, 255))
|
||||||
|
|
||||||
|
draw = ImageDraw.Draw(img)
|
||||||
|
draw.text((50, 40), "Hello, Flask!", fill=(0, 0, 0)) # Schwarzer Text
|
||||||
|
|
||||||
|
img_io = io.BytesIO()
|
||||||
|
img.save(img_io, 'PNG')
|
||||||
|
img_io.seek(0) # Zeiger zurücksetzen
|
||||||
|
|
||||||
|
return Response(img_io, mimetype='image/png')
|
||||||
|
|
267
src/run.py
267
src/run.py
@ -1,269 +1,12 @@
|
|||||||
from flask import Flask, session, g, render_template_string
|
|
||||||
from flask_session import Session
|
|
||||||
from flask_oidc import OpenIDConnect
|
|
||||||
from werkzeug.middleware.proxy_fix import ProxyFix
|
from werkzeug.middleware.proxy_fix import ProxyFix
|
||||||
from loguru import logger
|
from loguru import logger
|
||||||
import redis
|
|
||||||
import json
|
|
||||||
import os
|
|
||||||
import plotly.express as px
|
|
||||||
import plotly.graph_objects as po
|
|
||||||
import pandas as pd
|
|
||||||
import psycopg
|
|
||||||
import sqlalchemy
|
|
||||||
import time
|
|
||||||
|
|
||||||
try:
|
|
||||||
redis_url = os.environ['REDIS_URL']
|
|
||||||
oidc_client_secrets = os.environ['OIDC_CLIENT_SECRETS']
|
|
||||||
secret_key = os.environ['SECRET_KEY']
|
|
||||||
except KeyError as e:
|
|
||||||
logger.error(f"Required environment variable not set ({e})")
|
|
||||||
raise e
|
|
||||||
|
|
||||||
|
|
||||||
app = Flask(__name__)
|
|
||||||
|
|
||||||
app.config.update({
|
|
||||||
'SECRET_KEY': secret_key,
|
|
||||||
'SESSION_TYPE': 'redis',
|
|
||||||
'SESSION_REDIS': redis.from_url(redis_url),
|
|
||||||
'OIDC_CLIENT_SECRETS': json.loads(oidc_client_secrets),
|
|
||||||
'OIDC_SCOPES': 'openid email',
|
|
||||||
'OIDC_USER_INFO_ENABLED': True,
|
|
||||||
'SESSION_USE_SIGNER': True,
|
|
||||||
})
|
|
||||||
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():
|
|
||||||
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)
|
|
||||||
step1_time = time.time()
|
|
||||||
duration1 = step1_time - step0_time
|
|
||||||
logger.info(f"{duration1=}")
|
|
||||||
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(
|
|
||||||
tickmode="array",
|
|
||||||
tickvals=list(range(1, 13)), # Monate 1–12
|
|
||||||
ticktext=["Jan", "Feb", "Mär", "Apr", "Mai", "Jun", "Jul", "Aug", "Sep", "Okt", "Nov", "Dez"]
|
|
||||||
),
|
|
||||||
yaxis=dict(ticksuffix=" kWh")
|
|
||||||
)
|
|
||||||
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>
|
|
||||||
<head>
|
|
||||||
<title>Jahreswerte PV-Energie</title>
|
|
||||||
</head>
|
|
||||||
<body>
|
|
||||||
{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>
|
|
||||||
""")
|
|
||||||
except Exception as e:
|
|
||||||
raise Exception(f"Error when querying energy export values: {e}")
|
|
||||||
finally:
|
|
||||||
if dbh is not None:
|
|
||||||
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,
|
|
||||||
max(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(
|
|
||||||
title='NTP Server Numbers',
|
|
||||||
|
|
||||||
# Linke Y-Achse
|
|
||||||
yaxis=dict(
|
|
||||||
title='Root Dispersion',
|
|
||||||
ticksuffix=' ms'
|
|
||||||
),
|
|
||||||
|
|
||||||
# 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
|
|
||||||
)
|
|
||||||
|
|
||||||
graph_html_1 = fig.to_html(full_html=False, default_height='30%')
|
|
||||||
|
|
||||||
query = """
|
|
||||||
select time_bucket('5 minutes', time) as bucket,
|
|
||||||
device,
|
|
||||||
avg(cast(values->'lan-out'->>'value' as int)) as outOctetsPerSeconds,
|
|
||||||
avg(cast(values->'lan-in'->>'value' as int)) as inOctetsPerSeconds
|
|
||||||
from measurements
|
|
||||||
where time >= date_trunc('day', now()) AND time < date_trunc('day', now()) + '1 day'::interval and
|
|
||||||
application = 'SNMP' and attributes->>'Label' = 'david'
|
|
||||||
group by bucket, device
|
|
||||||
order by bucket, device
|
|
||||||
"""
|
|
||||||
df = pd.read_sql(query, con=engine)
|
|
||||||
fig_2 = po.Figure()
|
|
||||||
fig_2.add_trace(po.Scatter(x=df['bucket'], y=df['outOctetsPerSeconds'], mode='lines', name='Outbound Traffic', line=dict(color='green')))
|
|
||||||
fig_2.add_trace(po.Scatter(x=df['bucket'], y=df['inOctetsPerSeconds'], mode='lines', name='Inbound Traffic', line=dict(color='blue')))
|
|
||||||
|
|
||||||
fig_2.update_layout(
|
|
||||||
title='Network Load',
|
|
||||||
|
|
||||||
# Linke Y-Achse
|
|
||||||
yaxis=dict(
|
|
||||||
ticksuffix=' KiB/s'
|
|
||||||
),
|
|
||||||
|
|
||||||
legend=dict(x=0.05, y=1) # Position der Legende
|
|
||||||
)
|
|
||||||
graph_html_2 = fig_2.to_html(full_html=False, default_height='30%')
|
|
||||||
|
|
||||||
query = """
|
|
||||||
select time_bucket('5 minutes', time) as bucket,
|
|
||||||
device,
|
|
||||||
avg(cast(values->'local'->>'value' as float)) as loadAverage1Min
|
|
||||||
from measurements
|
|
||||||
where time >= date_trunc('day', now()) AND time < date_trunc('day', now()) + '1 day'::interval and
|
|
||||||
application = 'SNMP' and attributes->>'Label' = 'david'
|
|
||||||
group by bucket, device
|
|
||||||
order by bucket, device
|
|
||||||
"""
|
|
||||||
df = pd.read_sql(query, con=engine)
|
|
||||||
fig_3 = px.line(df, x='bucket', y='loadAverage1Min')
|
|
||||||
fig_3.update_layout(
|
|
||||||
xaxis_title="",
|
|
||||||
yaxis_title="",
|
|
||||||
title=f"CPU Load"
|
|
||||||
)
|
|
||||||
graph_html_3 = fig_3.to_html(full_html=False, default_height='30%')
|
|
||||||
|
|
||||||
return render_template_string(f"""
|
|
||||||
<html>
|
|
||||||
<head>
|
|
||||||
<title>NTP Server Numbers</title>
|
|
||||||
</head>
|
|
||||||
<body>
|
|
||||||
{graph_html_1}
|
|
||||||
{graph_html_2}
|
|
||||||
{graph_html_3}
|
|
||||||
</body>
|
|
||||||
</html>
|
|
||||||
""")
|
|
||||||
except Exception as e:
|
|
||||||
raise Exception(f"Error when querying NTP server values: {e}")
|
|
||||||
finally:
|
|
||||||
if dbh is not None:
|
|
||||||
dbh.close()
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
from app import app
|
||||||
|
|
||||||
|
import routes
|
||||||
|
import debug_routes
|
||||||
|
import pv_routes
|
||||||
|
import ntp_routes
|
||||||
|
|
||||||
|
|
||||||
if __name__ == '__main__':
|
if __name__ == '__main__':
|
||||||
|
Reference in New Issue
Block a user