73641b7e5b
Introduce ENTSO-E data retrieval with layered caching, robust bidding-zone and missing-data handling, and persist model-ready features with detailed architecture/developer documentation. Made-with: Cursor
42 lines
1.4 KiB
Python
42 lines
1.4 KiB
Python
import argparse
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import os
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import pandas as pd
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from electricity_price_predictor.db import get_engine
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from electricity_price_predictor.pipeline import run_feature_pipeline
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def parse_args() -> argparse.Namespace:
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parser = argparse.ArgumentParser(description="Fetch ENTSO-E inputs and build feature store.")
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parser.add_argument("--country-code", required=True, help="ENTSO-E bidding zone code, e.g. DE_LU")
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parser.add_argument("--start", required=True, help="Inclusive start datetime, e.g. 2026-01-01T00:00:00Z")
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parser.add_argument("--end", required=True, help="Exclusive end datetime, e.g. 2026-02-01T00:00:00Z")
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parser.add_argument("--cache-ttl-hours", type=int, default=24, help="Decorator cache TTL in hours")
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return parser.parse_args()
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def main() -> None:
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args = parse_args()
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api_key = os.getenv("ENTSOE_API_KEY")
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if not api_key:
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raise RuntimeError("ENTSOE_API_KEY environment variable is required.")
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engine = get_engine()
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start = pd.Timestamp(args.start, tz="UTC")
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end = pd.Timestamp(args.end, tz="UTC")
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features = run_feature_pipeline(
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engine=engine,
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entsoe_api_key=api_key,
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country_code=args.country_code,
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start=start,
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end=end,
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cache_ttl_hours=args.cache_ttl_hours,
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)
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print(f"Persisted {len(features)} feature rows for {args.country_code}.")
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if __name__ == "__main__":
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main()
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