Improve map

pipeline/config.py

@@ -9,7 +9,7 @@ AGGREGATES_DIR = PROCESSED_DIR / "aggregates"
 
 # H3 resolutions to generate and serve
 # https://h3geo.org/docs/core-library/restable/#average-area-in-m2
-H3_RESOLUTIONS = [6, 7, 8, 9, 10, 11, 12]
+H3_RESOLUTIONS = [6, 7, 8, 9, 10, 11]
 DEFAULT_H3_RESOLUTION = 8
 
 # Year filters
@@ -20,4 +20,4 @@ DEFAULT_MAX_YEAR = 2024
 
 # Price filters
 DEFAULT_MIN_PRICE = 0
-DEFAULT_MAX_PRICE = 2_000_000
+DEFAULT_MAX_PRICE = 100_000_000

pipeline/run.py

@@ -1,10 +1,8 @@
 """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.postcodes import save_postcodes
 from pipeline.sources.property_prices import PropertyPricesSource
 from pipeline.processors.h3_aggregator import save_aggregates
 

pipeline/sources/postcodes.py

@@ -28,7 +28,8 @@ def process_postcodes() -> pl.LazyFrame:
         df = df.with_columns(
             pl.struct(["lat", "long"])
             .map_elements(
-                lambda x: lat_long_to_h3(x["lat"], x["long"], res),
+                # Capture res by value using default argument to avoid closure bug
+                lambda x, res=res: lat_long_to_h3(x["lat"], x["long"], res),
                 return_dtype=pl.Utf8,
             )
             .alias(col_name)