import sys
from pathlib import Path

import duckdb
import polars as pl
import streamlit as st

project_root = str(Path(__file__).parent.parent)
if project_root not in sys.path:
    sys.path.append(project_root)

from utils.config_loader import settings

st.set_page_config(page_title="Strompreis & Netz Dashboard", layout="wide")

st.title("⚡ Strompreis, Netz & Wetter Dashboard")


@st.cache_data(ttl=300)
def load_data():
    try:
        con = duckdb.connect(settings.database.path)
        df = con.execute("SELECT * FROM combined ORDER BY timestamp DESC").pl()
        con.close()
        return df.fill_null(0)
    except Exception as e:
        st.error(f"Fehler beim Laden der Daten: {e}")
        return pl.DataFrame()


df = load_data()

if df.is_empty():
    st.warning("Keine Daten gefunden. Bitte Pipeline starten.")
else:
    latest = df.head(1).to_dicts()[0]
    m1, m2, m3, m4 = st.columns(4)
    m1.metric("Preis", f"{latest['price']:.2f} €/MWh")
    m2.metric("Netzlast", f"{latest['load_forecast'] / 1000:.1f} GW")
    m3.metric("Erneuerbare", f"{(latest['wind_total'] + latest['pv']) / 1000:.1f} GW")
    m4.metric("Außentemp.", f"{latest['temperature']:.1f} °C")

    tab1, tab2, tab3 = st.tabs(["Markt & Netz", "Wetter-Details", "Rohdaten"])

    with tab1:
        st.subheader("Strompreis vs. Netzlast")
        pdf = df.to_pandas()
        st.line_chart(pdf.set_index("timestamp")[["price", "load_forecast"]])

        st.subheader("Erzeugung Mix (Wind & Solar)")
        st.area_chart(pdf.set_index("timestamp")[["wind_total", "pv"]])

    with tab2:
        st.subheader("Detaillierte Wetterdaten")
        w_col1, w_col2 = st.columns(2)
        with w_col1:
            st.info("Temperaturverlauf")
            st.line_chart(pdf.set_index("timestamp")["temperature"])
        with w_col2:
            st.info("Windgeschwindigkeit")
            st.line_chart(pdf.set_index("timestamp")["wind_speed"])

        st.info("Weitere Wetterfaktoren")
        available_weather = [
            c
            for c in ["solar", "sunshine", "cloud_cover", "precipitation"]
            if c in df.columns
        ]
        if available_weather:
            st.line_chart(pdf.set_index("timestamp")[available_weather])

    with tab3:
        st.dataframe(df)