Add hexagon backend

pipeline/run.py

@@ -0,0 +1,36 @@
+"""Pipeline CLI to process property data with H3 spatial indexing."""
+
+from pathlib import Path
+import polars as pl
+from tqdm import tqdm
+
+from pipeline.sources.postcodes import save_postcodes, DATA_DIR
+from pipeline.sources.property_prices import PropertyPricesSource
+from pipeline.processors.h3_aggregator import save_aggregates
+
+
+def run_pipeline():
+    """Run the full data processing pipeline."""
+    print("=" * 60)
+    print("Property Map Data Pipeline")
+    print("=" * 60)
+
+    # Step 1: Process postcodes with H3 indices
+    print("\n[1/3] Processing postcodes with H3 indices...")
+    postcodes_path = save_postcodes()
+    print(f"      Saved: {postcodes_path}")
+
+    print("\n[2/3] Processing property prices...")
+    postcodes = pl.scan_parquet(postcodes_path)
+    property_source = PropertyPricesSource()
+    properties = property_source.process(postcodes)
+    print("      Joined property prices with postcodes")
+
+    print("\n[3/3] Aggregating at H3 resolutions...")
+    saved_paths = save_aggregates(properties)
+    for path in saved_paths:
+        size_mb = path.stat().st_size / (1024 * 1024)
+        print(f"      Saved: {path.name} ({size_mb:.1f} MB)")
+
+if __name__ == "__main__":
+    run_pipeline()