From d87d0cce11d94738c350eee2739da90eb396c01c Mon Sep 17 00:00:00 2001 From: Patryk Hegenberg Date: Wed, 11 Feb 2026 15:24:26 +0100 Subject: [PATCH 1/2] refactor: modernize project and improve error handling and documentation --- Dockerfile | 17 + README.md | 64 ++ api/main.py | 51 ++ collectors/pricing.py | 29 - collectors/smard.py | 58 ++ collectors/weather.py | 55 +- config/config.yaml | 12 + dashboard/app.py | 73 ++ docker-compose.yaml | 36 + main.py | 133 +++- pyproject.toml | 28 + scripts/scheduler.sh | 8 + transformators/transformator.py | 104 +-- utils/config_loader.py | 54 ++ utils/database.py | 77 ++- utils/request_utils.py | 40 +- uv.lock | 1142 +++++++++++++++++++++++++++++++ 17 files changed, 1793 insertions(+), 188 deletions(-) create mode 100644 Dockerfile create mode 100644 README.md create mode 100644 api/main.py delete mode 100644 collectors/pricing.py create mode 100644 collectors/smard.py create mode 100644 docker-compose.yaml create mode 100644 scripts/scheduler.sh diff --git a/Dockerfile b/Dockerfile new file mode 100644 index 0000000..e21bca8 --- /dev/null +++ b/Dockerfile @@ -0,0 +1,17 @@ +FROM python:3.11-slim-bookworm +COPY --from=ghcr.io/astral-sh/uv:latest /uv /uvbin/uv + +WORKDIR /app + +COPY pyproject.toml uv.lock ./ +RUN /uvbin/uv pip install --system --requirement pyproject.toml + +COPY . . + +RUN mkdir -p output config .cache && chmod -R 777 output config .cache + +ENV PYTHONPATH=. +ENV INTERVAL=3600 +ENV UV_CACHE_DIR=/app/.cache + +CMD ["/uvbin/uv", "run", "python", "main.py", "run"] diff --git a/README.md b/README.md new file mode 100644 index 0000000..7ba96ef --- /dev/null +++ b/README.md @@ -0,0 +1,64 @@ +# Strompreis & Netz Pipeline + +Automatisierte End-to-End Daten-Pipeline zur Erfassung, Analyse und Visualisierung von Strommarkt- und Wetterdaten. + +## 🏗 Architektur (Medallion Prinzip) + +Das Projekt folgt einer sauberen Data-Engineering-Struktur unter Verwendung von DuckDB und Polars: + +1. **Bronze Layer (Raw):** Unveränderte API-Antworten von SMARD und Bright Sky werden als historische Fakten gespeichert. +2. **Gold Layer (Combined):** Transformierte, bereinigte und über Zeitstempel zusammengeführte Daten (Inner Join), die direkt für Analysen und das Dashboard bereitstehen. + +## 🚀 Features + +- **Datensammlung:** Automatisiertes Abrufen von: + - Strompreisen, Netzlast, Gesamterzeugung, Wind- & Solar-Erzeugung (SMARD API). + - Umfassenden Wetterdaten (Temperatur, Wind, Solarstrahlung, etc. via Bright Sky API). +- **Dashboard:** Interaktive Visualisierung mit Streamlit (Preise, Energiemix, Wetter-Details). +- **REST-API:** FastAPI-Schnittstelle für den programmatischen Zugriff auf aktuelle Daten. +- **Orchestrierung:** Vollständige Docker-Integration inklusive eines automatisierten Schedulers. + +## 🛠 Installation & Betrieb + +### Mit Docker (Empfohlen) + +Das gesamte System (Pipeline, API, Dashboard) wird mit einem Befehl gestartet: + +```bash +docker-compose up --build +``` +- **Dashboard:** `http://localhost:8501` +- **API:** `http://localhost:8000/docs` + +### Lokal (Entwicklung) + +1. **Abhängigkeiten installieren:** + ```bash + uv sync + ``` + +2. **Pipeline manuell ausführen:** + ```bash + uv run python main.py run + ``` + +3. **Dashboard starten:** + ```bash + uv run streamlit run dashboard/app.py + ``` + +## ⚙️ Konfiguration + +Die Konfiguration erfolgt über `config/config.yaml` oder Umgebungsvariablen mit dem Präfix `STROM_`: +- `STROM_SMARD__REGION`: Region-Code (Standard: DE-LU) +- `STROM_DATABASE__PATH`: Pfad zur DuckDB Datei +- `INTERVAL`: Ausführungsintervall des Schedulers im Docker-Container (in Sekunden). + +## 🧪 Tests + +```bash +uv run pytest +``` + +## Lizenz +MIT diff --git a/api/main.py b/api/main.py new file mode 100644 index 0000000..95103f0 --- /dev/null +++ b/api/main.py @@ -0,0 +1,51 @@ +""" +REST API for accessing processed electricity price and network data. +""" + +import sys +from pathlib import Path +from fastapi import FastAPI, HTTPException + +# Add project root to sys.path +project_root = str(Path(__file__).parent.parent) +if project_root not in sys.path: + sys.path.append(project_root) + +from utils import database as db +from utils.config_loader import settings + +app = FastAPI( + title="Strompreis API", + description="Provides access to cleaned and joined electricity price, network, and weather data." +) + +@app.get("/current-price") +async def get_current_price(): + """ + Returns the most recent price record from the Gold (combined) layer. + """ + try: + with db.get_connection() as con: + res = con.execute( + "SELECT timestamp, price FROM combined ORDER BY timestamp DESC LIMIT 1" + ).fetchone() + + if not res: + raise HTTPException(status_code=404, detail="No data available") + + return { + "timestamp": res[0], + "price_eur_mwh": res[1], + "price_ct_kwh": round(res[1] / 10, 2) + } + except Exception as e: + raise HTTPException(status_code=500, detail=f"Database error: {str(e)}") + +@app.get("/status") +async def get_status(): + """Returns basic system configuration and status.""" + return { + "region": settings.smard.region, + "database": settings.database.path, + "status": "operational" + } diff --git a/collectors/pricing.py b/collectors/pricing.py deleted file mode 100644 index cb11698..0000000 --- a/collectors/pricing.py +++ /dev/null @@ -1,29 +0,0 @@ -from datetime import datetime -import time -import polars as pl -from utils import request_utils - - -def fetch_prices(region: str = "DE-LU", filter_id: int = 4169) -> pl.DataFrame: - current_time = 0 - closest = 0 - now_ms = int(time.time()) * 1000 - index_url = ( - f"https://www.smard.de/app/chart_data/{filter_id}/{region}/index_hour.json" - ) - timestamps = request_utils.make_requests(index_url, timeout=20) - closest = min(timestamps.get("timestamps", []), key=lambda x: abs(x - now_ms)) - - current_time = closest - url = f"https://www.smard.de/app/chart_data/{filter_id}/{region}/{filter_id}_{region}_hour_{current_time}.json" - data = request_utils.make_requests(url, timeout=20) - series = data.get("series", []) - clean_series = [row for row in series if row[1] is not None] - - df = pl.DataFrame( - { - "timestamp": [row[0] for row in clean_series], - "price": [row[1] for row in clean_series], - } - ) - return df diff --git a/collectors/smard.py b/collectors/smard.py new file mode 100644 index 0000000..d095c8c --- /dev/null +++ b/collectors/smard.py @@ -0,0 +1,58 @@ +""" +Collector for SMARD (Electricity Market Data) API. +""" + +import time +import logging +import polars as pl +from utils import request_utils +from utils.config_loader import settings + +logger = logging.getLogger(__name__) + +def fetch_smard_data(filter_id: int, region: str = None) -> pl.DataFrame: + """ + Fetches time-series data from the SMARD API for a specific filter. + + Args: + filter_id: The SMARD data identifier (e.g., 4169 for price). + region: The region code (defaults to config value). + + Returns: + A Polars DataFrame with 'timestamp' (ms) and 'value'. + """ + region = region or settings.smard.region + base_url = settings.smard.base_url + + now_ms = int(time.time()) * 1000 + index_url = f"{base_url}/{filter_id}/{region}/index_hour.json" + + try: + index_data = request_utils.make_requests(index_url) + if not index_data or "timestamps" not in index_data: + logger.warning(f"No index data for filter {filter_id}") + return pl.DataFrame() + + closest_ts = min(index_data["timestamps"], key=lambda x: abs(x - now_ms)) + + data_url = ( + f"{base_url}/{filter_id}/{region}/" + f"{filter_id}_{region}_hour_{closest_ts}.json" + ) + payload = request_utils.make_requests(data_url) + series = payload.get("series", []) + + clean_series = [row for row in series if row[1] is not None] + if not clean_series: + return pl.DataFrame() + + return pl.DataFrame( + { + "timestamp": [row[0] for row in clean_series], + "value": [row[1] for row in clean_series], + }, + schema={"timestamp": pl.Int64, "value": pl.Float64} + ) + except Exception as e: + logger.error(f"Failed to fetch SMARD filter {filter_id}: {e}") + return pl.DataFrame() diff --git a/collectors/weather.py b/collectors/weather.py index 2da9480..7f65bbd 100644 --- a/collectors/weather.py +++ b/collectors/weather.py @@ -1,11 +1,30 @@ +""" +Collector for Bright Sky (Weather) API. +""" + +import logging from datetime import datetime, timedelta, timezone -from utils import request_utils + import polars as pl +from utils import request_utils +from utils.config_loader import settings + +logger = logging.getLogger(__name__) + + +def fetch_weather(lat: float = None, lon: float = None) -> pl.DataFrame: + """ + Fetches historical weather data from Bright Sky API. + Filters for the specific columns defined in the Bronze schema. + + Returns: + A Polars DataFrame containing filtered raw weather parameters. + """ + lat = lat or settings.brightsky.lat + lon = lon or settings.brightsky.lon + url = settings.brightsky.base_url -def fetch_weather(lat: float = 52.52, lon: float = 13.41) -> pl.DataFrame: - url = "https://api.brightsky.dev/weather" - headers = {"Accept": "application/json"} current_utc = datetime.now(timezone.utc) payload = { "date": (current_utc - timedelta(hours=72)).isoformat(), @@ -15,8 +34,9 @@ def fetch_weather(lat: float = 52.52, lon: float = 13.41) -> pl.DataFrame: "units": "dwd", "tz": "Etc/UTC", } - data = request_utils.make_requests(url, headers, payload, 20) - relevant_fields = [ + + schema_cols = [ + "timestamp", "temperature", "wind_speed", "solar", @@ -24,13 +44,20 @@ def fetch_weather(lat: float = 52.52, lon: float = 13.41) -> pl.DataFrame: "cloud_cover", "precipitation", ] - critical_fields = ["temperature", "wind_speed"] - weather_data = [ - {k: v for k, v in entry.items() if k in relevant_fields or k in ["timestamp"]} - for entry in data["weather"] - if all(entry.get(field) is not None for field in critical_fields) - ] + try: + data = request_utils.make_requests(url, params=payload) + weather_list = data.get("weather", []) - df_weather = pl.DataFrame(weather_data) - return df_weather + if not weather_list: + logger.warning("No weather data returned from API.") + return pl.DataFrame() + + df = pl.DataFrame(weather_list) + + available_cols = [c for c in schema_cols if c in df.columns] + return df.select(available_cols) + + except Exception as e: + logger.error(f"Failed to fetch weather data: {e}") + return pl.DataFrame() diff --git a/config/config.yaml b/config/config.yaml index e69de29..ed6cdf4 100644 --- a/config/config.yaml +++ b/config/config.yaml @@ -0,0 +1,12 @@ +smard: + region: "DE-LU" + filter_id: 4169 + base_url: "https://www.smard.de/app/chart_data" + +brightsky: + lat: 52.52 + lon: 13.41 + base_url: "https://api.brightsky.dev/weather" + +database: + path: "output/pipeline.duckdb" diff --git a/dashboard/app.py b/dashboard/app.py index e69de29..cea3ecf 100644 --- a/dashboard/app.py +++ b/dashboard/app.py @@ -0,0 +1,73 @@ +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) diff --git a/docker-compose.yaml b/docker-compose.yaml new file mode 100644 index 0000000..3a4a364 --- /dev/null +++ b/docker-compose.yaml @@ -0,0 +1,36 @@ +services: + pipeline: + build: . + user: "1000:1000" + volumes: + - ./output:/app/output:z + - ./config:/app/config:z + command: ["/bin/bash", "scripts/scheduler.sh"] + environment: + - INTERVAL=3600 + restart: unless-stopped + + api: + build: . + user: "1000:1000" + ports: + - "8000:8000" + volumes: + - ./output:/app/output:z + - ./config:/app/config:z + command: ["python", "-m", "uvicorn", "api.main:app", "--host", "0.0.0.0", "--port", "8000"] + restart: unless-stopped + + dashboard: + build: . + user: "1000:1000" + ports: + - "8501:8501" + volumes: + - ./output:/app/output:z + - ./config:/app/config:z + environment: + - STREAMLIT_BROWSER_GATHER_USAGE_STATS=false + - STREAMLIT_USAGE_STATS_ENABLED=false + command: ["streamlit", "run", "dashboard/app.py", "--server.port", "8501", "--server.address", "0.0.0.0"] + restart: unless-stopped diff --git a/main.py b/main.py index 086ce76..7471c4a 100644 --- a/main.py +++ b/main.py @@ -1,10 +1,18 @@ +""" +Main entry point for the Strompreis Pipeline CLI. +Coordinates data collection, transformation, and storage. +""" + import sys -from collectors import pricing, weather +import logging +import click +import polars as pl +from collectors import smard, weather from transformators import transformator from utils import database as db -import logging - +from utils.config_loader import settings +# Structured logging configuration logging.basicConfig( level=logging.INFO, format="%(asctime)s - %(name)s - %(levelname)s - %(message)s", @@ -12,39 +20,100 @@ logging.basicConfig( logger = logging.getLogger(__name__) -def main(): - logger.info("Starte Strompreis-Pipeline") +@click.group() +def cli(): + """Strompreis Pipeline CLI Tools.""" + pass - logger.info("Hole Preisdaten...") - df_prices_raw = pricing.fetch_prices() - logger.info(f"Preise: {len(df_prices_raw)} Zeilen") - logger.info("Hole Wetterdaten...") - df_weather_raw = weather.fetch_weather() - logger.info(f"Wetter: {len(df_weather_raw)} Zeilen") +@cli.command() +@click.option("--region", help="SMARD region code (e.g., DE-LU).") +@click.option("--lat", type=float, help="Latitude for weather data.") +@click.option("--lon", type=float, help="Longitude for weather data.") +def run(region, lat, lon): + """ + Executes the full ETL pipeline: + 1. Bronze Layer: Fetch and store raw data. + 2. Gold Layer: Transform and join data into a clean business view. + """ + logger.info("Initializing Pipeline...") - logger.info("Transformiere Daten...") - df_prices_clean = transformator.transform_prices(df_prices_raw) - df_weather_clean = transformator.transform_weather(df_weather_raw) - df_joined = transformator.join_dataframes(df_prices_clean, df_weather_clean) - logger.info(f"Joined: {len(df_joined)} Zeilen") + try: + logger.info("Step 1/4: Fetching raw data from APIs...") + smard_queries = { + "prices_raw": settings.smard.price_filter, + "load_forecast_raw": settings.smard.load_forecast_filter, + "gen_total_raw": settings.smard.generation_total_filter, + "wind_onshore_raw": settings.smard.wind_onshore_filter, + "wind_offshore_raw": settings.smard.wind_offshore_filter, + "pv_raw": settings.smard.pv_filter, + } - logger.info("Speichere in DuckDB...") - with db.get_connection() as con: - db.init_tables(con) - db.upsert_prices(con, df_prices_raw) - db.upsert_prices_clean(con, df_prices_clean) - db.upsert_weather(con, df_weather_raw) - db.upsert_combined(con, df_joined) - logger.info("Erfolgreich zur Datenbank hinzugefügt.") + smard_dfs = { + tbl: smard.fetch_smard_data(fid, region) + for tbl, fid in smard_queries.items() + } + df_weather_raw = weather.fetch_weather(lat, lon) + + logger.info("Step 2/4: Persisting Bronze Layer...") + with db.get_connection() as con: + db.init_tables(con) + for table, df in smard_dfs.items(): + db.upsert_raw(con, table, df) + db.upsert_raw(con, "weather_raw", df_weather_raw) + + logger.info("Step 3/4: Transforming and joining data (Gold Layer)...") + + def to_gold_smard(df, name): + """Internal helper to convert raw SMARD df to gold format.""" + if df.is_empty(): + return pl.DataFrame( + schema={"timestamp": pl.Datetime("ms", "UTC"), name: pl.Float64} + ) + return df.with_columns( + pl.col("timestamp").cast(pl.Datetime("ms")).dt.replace_time_zone("UTC") + ).rename({"value": name}) + + df_p = to_gold_smard(smard_dfs["prices_raw"], "price") + df_l = to_gold_smard(smard_dfs["load_forecast_raw"], "load_forecast") + df_g = to_gold_smard(smard_dfs["gen_total_raw"], "generation_total") + df_w_on = to_gold_smard(smard_dfs["wind_onshore_raw"], "wind_on") + df_w_off = to_gold_smard(smard_dfs["wind_offshore_raw"], "wind_off") + df_pv = to_gold_smard(smard_dfs["pv_raw"], "pv") + + df_wind = df_w_on.join( + df_w_off, on="timestamp", how="full", coalesce=True + ).fill_null(0) + df_wind = df_wind.with_columns( + (pl.col("wind_on") + pl.col("wind_off")).alias("wind_total") + ) + + df_weather_gold = transformator.transform_weather(df_weather_raw) + + df_smard_all = ( + df_p.join(df_l, on="timestamp", how="full", coalesce=True) + .join(df_g, on="timestamp", how="full", coalesce=True) + .join( + df_wind[["timestamp", "wind_total"]], + on="timestamp", + how="full", + coalesce=True, + ) + .join(df_pv, on="timestamp", how="full", coalesce=True) + ) + + df_gold = df_smard_all.join(df_weather_gold, on="timestamp", how="inner") + + logger.info("Step 4/4: Persisting Gold Layer...") + with db.get_connection() as con: + db.upsert_combined(con, df_gold) + + logger.info("Pipeline completed successfully.") + + except Exception as e: + logger.error(f"Pipeline execution failed: {e}", exc_info=True) + sys.exit(1) if __name__ == "__main__": - try: - main() - except KeyboardInterrupt: - logger.info("Pipeline durch Benutzer gestoppt") - sys.exit(0) - except Exception as e: - logger.error(f"Pipeline fehlgeschlagen: {e}", exc_info=True) - sys.exit(1) + cli() diff --git a/pyproject.toml b/pyproject.toml index c7cd9ec..29331c4 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -5,8 +5,36 @@ description = "Add your description here" readme = "README.md" requires-python = ">=3.11" dependencies = [ + "click>=8.3.1", "duckdb>=1.4.4", + "fastapi>=0.128.7", "polars>=1.38.1", "pyarrow>=23.0.0", + "pydantic>=2.12.5", + "pydantic-settings>=2.12.0", + "pyyaml>=6.0.3", "requests>=2.32.5", + "streamlit>=1.54.0", + "tenacity>=9.1.4", + "uvicorn>=0.40.0", +] + +[tool.ruff] +line-length = 88 +target-version = "py311" + +[tool.ruff.lint] +select = ["E", "F", "I", "W", "C90", "B"] +ignore = [] + +[tool.pytest.ini_options] +pythonpath = ["."] +testpaths = ["tests"] + +[dependency-groups] +dev = [ + "pytest>=9.0.2", + "pytest-mock>=3.15.1", + "requests-mock>=1.12.1", + "ruff>=0.15.0", ] diff --git a/scripts/scheduler.sh b/scripts/scheduler.sh new file mode 100644 index 0000000..7ca0848 --- /dev/null +++ b/scripts/scheduler.sh @@ -0,0 +1,8 @@ +#!/bin/bash +echo "Starte Pipeline Scheduler (Intervall: $INTERVAL Sekunden)" +while true; do + echo "Führe Pipeline aus: $(date)" + python main.py run + echo "Pipeline beendet. Warte $INTERVAL Sekunden..." + sleep ${INTERVAL:-3600} +done diff --git a/transformators/transformator.py b/transformators/transformator.py index dd03270..a1383d9 100644 --- a/transformators/transformator.py +++ b/transformators/transformator.py @@ -1,76 +1,40 @@ +""" +Data transformation logic for price and weather data. +""" + from datetime import timedelta import polars as pl +def transform_weather(df: pl.DataFrame) -> pl.DataFrame: + """ + Cleans and standardizes raw weather data. + """ + if df.is_empty(): + return pl.DataFrame() + + relevant_cols = [ + "timestamp", "temperature", "wind_speed", "solar", + "sunshine", "cloud_cover", "precipitation" + ] + + # Filter for existing relevant columns + cols_to_keep = [c for c in relevant_cols if c in df.columns] + + return df.select(cols_to_keep).with_columns( + pl.col("timestamp") + .str.to_datetime(format="%Y-%m-%dT%H:%M:%S%z", time_zone="UTC") + .cast(pl.Datetime("ms", time_zone="UTC")) + ).sort("timestamp") def transform_prices(df: pl.DataFrame) -> pl.DataFrame: + """ + Transforms raw SMARD timestamps to UTC Datetime. + """ + if df.is_empty(): + return pl.DataFrame() + return df.with_columns( - [ - pl.col("timestamp") - .cast(pl.Datetime("ms")) - .dt.replace_time_zone("UTC") - .alias("timestamp") - ] - ) - - -def transform_weather(df: pl.DataFrame) -> pl.DataFrame: - return df.with_columns( - [ - pl.col("timestamp") - .str.to_datetime( - format="%Y-%m-%dT%H:%M:%S%z", - time_zone="UTC", - ) - .cast(pl.Datetime("ms", time_zone="UTC")) - .alias("timestamp") - ] - ) - - -def join_dataframes(df_prices: pl.DataFrame, df_weather: pl.DataFrame) -> pl.DataFrame: - return df_prices.join(df_weather, on="timestamp", how="inner").select( - [ - pl.col("timestamp"), - pl.col("price"), - pl.col( - [ - "temperature", - "wind_speed", - "solar", - "sunshine", - "cloud_cover", - "precipitation", - ] - ), - ] - ) - - -# -# -# def join_dataframes(df_prices: pl.DataFrame, df_weather: pl.DataFrame) -> pl.DataFrame: -# return ( -# df_prices.sort("timestamp") # ← Pflicht! -# .join_asof( -# df_weather.sort("timestamp"), # ← Pflicht! -# on="timestamp", -# strategy="nearest", # ← nearest statt backward! -# tolerance=timedelta(hours=1), -# ) -# .select( -# [ -# pl.col("timestamp"), -# pl.col("price"), -# pl.col( -# [ -# "temperature", -# "wind_speed", -# "solar", -# "sunshine", -# "cloud_cover", -# "precipitation", -# ] -# ), -# ] -# ) -# ) + pl.col("timestamp") + .cast(pl.Datetime("ms")) + .dt.replace_time_zone("UTC") + ).sort("timestamp") diff --git a/utils/config_loader.py b/utils/config_loader.py index e69de29..9b13a80 100644 --- a/utils/config_loader.py +++ b/utils/config_loader.py @@ -0,0 +1,54 @@ +from pathlib import Path + +import yaml +from pydantic import BaseModel +from pydantic_settings import BaseSettings, SettingsConfigDict + + +class SmardConfig(BaseModel): + region: str = "DE-LU" + price_filter: int = 4169 + load_forecast_filter: int = 4382 + generation_total_filter: int = 122 + wind_onshore_filter: int = 4069 + wind_offshore_filter: int = 4068 + pv_filter: int = 4070 + base_url: str = "https://www.smard.de/app/chart_data" + + +class BrightSkyConfig(BaseModel): + lat: float = 52.52 + lon: float = 13.41 + base_url: str = "https://api.brightsky.dev/weather" + + +class DatabaseConfig(BaseModel): + path: str = "output/pipeline.duckdb" + + +class Settings(BaseSettings): + model_config = SettingsConfigDict( + env_file=".env", + env_nested_delimiter="__", + env_prefix="STROM_", + extra="ignore" + ) + + smard: SmardConfig = SmardConfig() + brightsky: BrightSkyConfig = BrightSkyConfig() + database: DatabaseConfig = DatabaseConfig() + + +def load_config(config_path: str = "config/config.yaml") -> Settings: + path = Path(config_path) + if not path.exists(): + return Settings() + + with open(path, "r") as f: + config_data = yaml.safe_load(f) or {} + + return Settings(**config_data) + + +# Global settings instance +settings = load_config() diff --git a/utils/database.py b/utils/database.py index 9750826..bf76a88 100644 --- a/utils/database.py +++ b/utils/database.py @@ -1,10 +1,17 @@ +""" +DuckDB database interface for Bronze (Raw) and Gold (Combined) layers. +""" + import duckdb import polars as pl from contextlib import contextmanager +from utils.config_loader import settings @contextmanager -def get_connection(db_path: str = "output/pipeline.duckdb"): +def get_connection(db_path: str = None): + """Context manager for DuckDB connections.""" + db_path = db_path or settings.database.path con = duckdb.connect(db_path) try: yield con @@ -13,23 +20,26 @@ def get_connection(db_path: str = "output/pipeline.duckdb"): def init_tables(con: duckdb.DuckDBPyConnection): - con.execute(""" - CREATE TABLE IF NOT EXISTS prices_raw ( - timestamp BIGINT NOT NULL UNIQUE, - price DOUBLE NOT NULL - ) - """) - - con.execute(""" - CREATE TABLE IF NOT EXISTS prices_clean ( - timestamp TIMESTAMP NOT NULL UNIQUE, - price DOUBLE NOT NULL - ) - """) + """ + Initializes the database schema following the Medallion architecture. + """ + # BRONZE LAYER (Raw API responses) + smard_tables = [ + "prices_raw", + "load_forecast_raw", + "gen_total_raw", + "wind_onshore_raw", + "wind_offshore_raw", + "pv_raw", + ] + for table in smard_tables: + con.execute( + f"CREATE TABLE IF NOT EXISTS {table} (timestamp BIGINT PRIMARY KEY, value DOUBLE)" + ) con.execute(""" CREATE TABLE IF NOT EXISTS weather_raw ( - timestamp TIMESTAMP NOT NULL UNIQUE, + timestamp VARCHAR PRIMARY KEY, temperature DOUBLE, wind_speed DOUBLE, solar DOUBLE, @@ -39,10 +49,15 @@ def init_tables(con: duckdb.DuckDBPyConnection): ) """) + # GOLD LAYER (Transformed and Joined Business Data) con.execute(""" CREATE TABLE IF NOT EXISTS combined ( - timestamp TIMESTAMP NOT NULL UNIQUE, - price DOUBLE NOT NULL, + timestamp TIMESTAMP PRIMARY KEY, + price DOUBLE, + load_forecast DOUBLE, + generation_total DOUBLE, + wind_total DOUBLE, + pv DOUBLE, temperature DOUBLE, wind_speed DOUBLE, solar DOUBLE, @@ -53,25 +68,23 @@ def init_tables(con: duckdb.DuckDBPyConnection): """) -def upsert_prices(con: duckdb.DuckDBPyConnection, df: pl.DataFrame): +def upsert_raw(con: duckdb.DuckDBPyConnection, table_name: str, df: pl.DataFrame): + """Inserts raw data using explicit columns to match the target table schema.""" + if df.is_empty(): + return + + cols = con.execute(f"DESCRIBE {table_name}").pl()["column_name"].to_list() + df_to_insert = df.select([c for c in cols if c in df.columns]) + con.execute( - """INSERT INTO prices_raw SELECT * FROM df ON CONFLICT (timestamp) DO NOTHING;""" - ) - - -def upsert_prices_clean(con: duckdb.DuckDBPyConnection, df: pl.DataFrame): - con.execute( - """INSERT INTO prices_clean SELECT * FROM df ON CONFLICT (timestamp) DO NOTHING;""" - ) - - -def upsert_weather(con: duckdb.DuckDBPyConnection, df: pl.DataFrame): - con.execute( - """INSERT INTO weather_raw SELECT * FROM df ON CONFLICT (timestamp) DO NOTHING;""" + f"INSERT INTO {table_name} SELECT * FROM df_to_insert ON CONFLICT (timestamp) DO NOTHING;" ) def upsert_combined(con: duckdb.DuckDBPyConnection, df: pl.DataFrame): + """Inserts business-ready data into the Gold layer.""" + if df.is_empty(): + return con.execute( - """INSERT INTO combined SELECT * FROM df ON CONFLICT (timestamp) DO NOTHING;""" + "INSERT INTO combined SELECT * FROM df ON CONFLICT (timestamp) DO NOTHING;" ) diff --git a/utils/request_utils.py b/utils/request_utils.py index 18a2b76..c68896a 100644 --- a/utils/request_utils.py +++ b/utils/request_utils.py @@ -1,23 +1,41 @@ +import logging + import requests +from tenacity import ( + retry, + retry_if_exception_type, + stop_after_attempt, + wait_exponential, +) + +logger = logging.getLogger(__name__) +@retry( + stop=stop_after_attempt(3), + wait=wait_exponential(multiplier=1, min=2, max=10), + retry=retry_if_exception_type((requests.exceptions.RequestException,)), + reraise=True, +) def make_requests( - url: str, headers: dict = {}, payload: dict = {}, timeout: int = 20 + url: str, headers: 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++++++++++++++++++++++++++++ tests/test_weather.py | 27 +++++++++++++++++++++++++++ uv.lock | 30 ++++++++++++++++++++++++++++++ 8 files changed, 128 insertions(+) create mode 100644 tests/test_api.py delete mode 100644 tests/test_pricing.py create mode 100644 tests/test_smard.py diff --git a/api/main.py b/api/main.py index 95103f0..53cc9a9 100644 --- a/api/main.py +++ b/api/main.py @@ -38,6 +38,8 @@ async def get_current_price(): "price_eur_mwh": res[1], "price_ct_kwh": round(res[1] / 10, 2) } + except HTTPException: + raise except Exception as e: raise HTTPException(status_code=500, detail=f"Database error: {str(e)}") diff --git a/pyproject.toml b/pyproject.toml index 29331c4..4286830 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -33,6 +33,7 @@ testpaths = ["tests"] [dependency-groups] dev = [ + "httpx>=0.28.1", "pytest>=9.0.2", "pytest-mock>=3.15.1", "requests-mock>=1.12.1", diff --git a/tests/test_api.py b/tests/test_api.py new file mode 100644 index 0000000..3fe97c9 --- /dev/null +++ b/tests/test_api.py @@ -0,0 +1,20 @@ +from fastapi.testclient import TestClient +from api.main import app +import pytest + +client = TestClient(app) + +def test_get_status(): + response = client.get("/status") + assert response.status_code == 200 + assert response.json()["status"] == "operational" + +def test_get_current_price_no_data(mocker): + # Mock database connection to return no data + mock_db = mocker.patch("utils.database.get_connection") + mock_con = mock_db.return_value.__enter__.return_value + mock_con.execute.return_value.fetchone.return_value = None + + response = client.get("/current-price") + assert response.status_code == 404 + assert response.json()["detail"] == "No data available" diff --git a/tests/test_pricing.py b/tests/test_pricing.py deleted file mode 100644 index e69de29..0000000 diff --git a/tests/test_smard.py b/tests/test_smard.py new file mode 100644 index 0000000..1afce15 --- /dev/null +++ b/tests/test_smard.py @@ -0,0 +1,20 @@ +import polars as pl +import requests_mock +from collectors.smard import fetch_smard_data + +def test_fetch_smard_data(): + with requests_mock.Mocker() as m: + # Mock index call + m.get("https://www.smard.de/app/chart_data/4169/DE-LU/index_hour.json", + json={"timestamps": [1700000000000]}) + # Mock data call + m.get("https://www.smard.de/app/chart_data/4169/DE-LU/4169_DE-LU_hour_1700000000000.json", + json={ + "series": [[1700000000000, 50.0], [1700003600000, 60.0]] + }) + + df = fetch_smard_data(filter_id=4169) + assert isinstance(df, pl.DataFrame) + assert df.shape == (2, 2) + assert "value" in df.columns + assert df["value"][0] == 50.0 diff --git a/tests/test_transformator.py b/tests/test_transformator.py index e69de29..4c18088 100644 --- a/tests/test_transformator.py +++ b/tests/test_transformator.py @@ -0,0 +1,28 @@ +import polars as pl +from transformators.transformator import ( + transform_prices, + transform_weather, +) + +def test_transform_prices(): + df = pl.DataFrame({ + "timestamp": [1700000000000], + "value": [50.0] + }) + transformed = transform_prices(df) + assert transformed.shape == (1, 2) + assert transformed["timestamp"].dtype == pl.Datetime("ms", time_zone="UTC") + +def test_transform_weather(): + df = pl.DataFrame({ + "timestamp": ["2023-11-14T22:13:20+00:00"], + "temperature": [10.5], + "wind_speed": [5.0], + "solar": [0.0], + "sunshine": [0.0], + "cloud_cover": [0.0], + "precipitation": [0.0] + }) + transformed = transform_weather(df) + assert transformed.shape == (1, 7) + assert transformed["timestamp"].dtype == pl.Datetime("ms", time_zone="UTC") diff --git a/tests/test_weather.py b/tests/test_weather.py index e69de29..02e41fc 100644 --- a/tests/test_weather.py +++ b/tests/test_weather.py @@ -0,0 +1,27 @@ +import polars as pl +import requests_mock +from collectors.weather import fetch_weather + +def test_fetch_weather(): + with requests_mock.Mocker() as m: + m.get("https://api.brightsky.dev/weather", json={ + "weather": [ + { + "timestamp": "2023-11-14T22:13:20+00:00", + "temperature": 10.5, + "wind_speed": 5.0, + "solar": 0.0, + "sunshine": 0.0, + "cloud_cover": 0.0, + "precipitation": 0.0, + "extra_field": "should_be_filtered" + } + ] + }) + + df = fetch_weather() + assert isinstance(df, pl.DataFrame) + # Check that it filtered to the schema columns (7 columns) + assert df.shape == (1, 7) + assert "temperature" in df.columns + assert "extra_field" not in df.columns diff --git a/uv.lock b/uv.lock index 2bf2be1..5192140 100644 --- a/uv.lock +++ b/uv.lock @@ -268,6 +268,34 @@ wheels = [ { url = "https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl", hash = "sha256:63cf8bbe7522de3bf65932fda1d9c2772064ffb3dae62d55932da54b31cb6c86", size = 37515, upload-time = "2025-04-24T03:35:24.344Z" }, ] +[[package]] +name = "httpcore" +version = "1.0.9" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "certifi" }, + { name = "h11" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/06/94/82699a10bca87a5556c9c59b5963f2d039dbd239f25bc2a63907a05a14cb/httpcore-1.0.9.tar.gz", hash = "sha256:6e34463af53fd2ab5d807f399a9b45ea31c3dfa2276f15a2c3f00afff6e176e8", size = 85484, upload-time = "2025-04-24T22:06:22.219Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/7e/f5/f66802a942d491edb555dd61e3a9961140fd64c90bce1eafd741609d334d/httpcore-1.0.9-py3-none-any.whl", hash = "sha256:2d400746a40668fc9dec9810239072b40b4484b640a8c38fd654a024c7a1bf55", size = 78784, upload-time = "2025-04-24T22:06:20.566Z" }, +] + +[[package]] +name = "httpx" +version = "0.28.1" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "anyio" }, + { name = "certifi" }, + { name = "httpcore" }, + { name = "idna" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/b1/df/48c586a5fe32a0f01324ee087459e112ebb7224f646c0b5023f5e79e9956/httpx-0.28.1.tar.gz", hash = "sha256:75e98c5f16b0f35b567856f597f06ff2270a374470a5c2392242528e3e3e42fc", size = 141406, upload-time = "2024-12-06T15:37:23.222Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/2a/39/e50c7c3a983047577ee07d2a9e53faf5a69493943ec3f6a384bdc792deb2/httpx-0.28.1-py3-none-any.whl", hash = "sha256:d909fcccc110f8c7faf814ca82a9a4d816bc5a6dbfea25d6591d6985b8ba59ad", size = 73517, upload-time = "2024-12-06T15:37:21.509Z" }, +] + [[package]] name = "idna" version = "3.11" @@ -1255,6 +1283,7 @@ dependencies = [ [package.dev-dependencies] dev = [ + { name = "httpx" }, { name = "pytest" }, { name = "pytest-mock" }, { name = "requests-mock" }, @@ -1279,6 +1308,7 @@ requires-dist = [ [package.metadata.requires-dev] dev = [ + { name = "httpx", specifier = ">=0.28.1" }, { name = "pytest", specifier = ">=9.0.2" }, { name = "pytest-mock", specifier = ">=3.15.1" }, { name = "requests-mock", specifier = ">=1.12.1" },