moving geocoding to a background task

backend/app.py

@@ -21,10 +21,9 @@ from starlette.middleware.base import BaseHTTPMiddleware
 from .config import settings
 from .data_loader import (
     clear_cache,
-    geocode_postcodes_bulk,
-    geocode_single_postcode,
     haversine_distance,
     load_school_data,
+    geocode_single_postcode,
 )
 from .data_loader import get_data_info as get_db_info
 from .database import init_db
@@ -256,7 +255,7 @@ async def get_schools(
     ]
     schools_df = df_latest[available_cols].drop_duplicates(subset=["urn"])
 
-    # Location-based search
+    # Location-based search (uses pre-geocoded data from database)
     search_coords = None
     if postcode:
         coords = geocode_single_postcode(postcode)
@@ -264,24 +263,7 @@ async def get_schools(
             search_coords = coords
             schools_df = schools_df.copy()
 
-            # Geocode school postcodes on-demand if not already cached
-            if "postcode" in schools_df.columns:
-                unique_postcodes = schools_df["postcode"].dropna().unique().tolist()
-                geocoded = geocode_postcodes_bulk(unique_postcodes)
-
-                # Add lat/long from geocoded data
-                schools_df["latitude"] = schools_df["postcode"].apply(
-                    lambda pc: geocoded.get(str(pc).strip().upper(), (None, None))[0]
-                    if pd.notna(pc)
-                    else None
-                )
-                schools_df["longitude"] = schools_df["postcode"].apply(
-                    lambda pc: geocoded.get(str(pc).strip().upper(), (None, None))[1]
-                    if pd.notna(pc)
-                    else None
-                )
-
-            # Filter by distance
+            # Filter by distance using pre-geocoded lat/long from database
             def calc_distance(row):
                 if pd.isna(row.get("latitude")) or pd.isna(row.get("longitude")):
                     return float("inf")