refactor: seperate system into single Dockerfiles

apps/dashboard/dashboard/app.py

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+import duckdb
+import polars as pl
+import streamlit as st
+
+from common.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)

apps/dashboard/pyproject.toml

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+[project]
+name = "dashboard"
+version = "0.1.0"
+description = "Streamlit dashboard for electricity price data"
+dependencies = [
+    "streamlit>=1.54.0",
+    "common",
+]
+
+[tool.uv.sources]
+common = { workspace = true }
+
+[build-system]
+requires = ["hatchling"]
+build-backend = "hatchling.build"