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('/') @oidc.require_login def pvstats(): try: dbh = psycopg.connect() engine = sqlalchemy.create_engine("postgresql+psycopg://", creator=lambda: dbh) df = pd.read_sql("SELECT month, cast(year AS varchar), current_energy AS value FROM pv_energy_by_month ORDER BY year, month", con=engine) fig_1 = px.bar(df, x='month', y='value', color='year', barmode='group') fig_1.update_layout( title=f"Jahreswerte Exportierte Energie PV-Anlage", 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%') df = pd.read_sql("SELECT month, cast(year AS varchar), current_energy AS value FROM car_energy_by_month ORDER BY year, month", con=engine) fig_2 = px.bar(df, x='month', y='value', color='year', barmode='group') fig_2.update_layout( title=f"Jahreswerte Verbrauch Elektroauto", 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_2 = fig_2.to_html(full_html=False, default_height='30%') return render_template_string(f""" Jahreswerte PV und Auto {graph_html_1} {graph_html_2} """) except Exception as e: raise Exception(f"Error when querying energy values: {e}") finally: if dbh is not None: dbh.close()