Add proper buy listing support with type-aware UI filters and display

crawler/ui_exporter.py

@@ -1,13 +1,122 @@
 import json
 import logging
 import pathlib
+from typing import Any
 
-from models.listing import QueryParameters
+from models.listing import QueryParameters, RentListing, BuyListing
 from repositories.listing_repository import ListingRepository
 
 logger = logging.getLogger("uvicorn.error")
 
 
+def convert_row_to_geojson(row: dict[str, Any], listing_type: str = "RENT") -> dict[str, Any]:
+    """Convert a projected row dict to GeoJSON Feature format.
+
+    This function handles dict rows from stream_listings_optimized(),
+    which uses column projection and returns dicts instead of model instances.
+
+    Args:
+        row: A dict with keys matching STREAMING_COLUMNS
+
+    Returns:
+        A GeoJSON Feature dict with properties and geometry
+    """
+    # Parse price history from JSON string
+    price_history = []
+    if row.get('price_history_json'):
+        parsed = json.loads(row['price_history_json'])
+        price_history = [
+            {
+                "first_seen": p["first_seen"],
+                "last_seen": p["last_seen"],
+                "price": p["price"]
+            }
+            for p in parsed
+        ]
+
+    sqm = row.get('square_meters')
+    price = row['price']
+
+    # Handle available_from which may be a datetime or None
+    available_from_val = row.get('available_from')
+    available_from_str = None
+    if available_from_val is not None:
+        if hasattr(available_from_val, 'isoformat'):
+            available_from_str = available_from_val.isoformat()
+        else:
+            available_from_str = str(available_from_val)
+
+    # Handle last_seen which should be a datetime
+    last_seen_val = row['last_seen']
+    if hasattr(last_seen_val, 'isoformat'):
+        last_seen_str = last_seen_val.isoformat()
+    else:
+        last_seen_str = str(last_seen_val)
+
+    return {
+        "type": "Feature",
+        "properties": {
+            "listing_type": listing_type,
+            "city": "London",
+            "country": "United Kingdom",
+            "qm": sqm,
+            "qmprice": round(price / sqm, 2) if sqm else None,
+            "rooms": row['number_of_bedrooms'],
+            "total_price": price,
+            "url": f"https://www.rightmove.co.uk/properties/{row['id']}",
+            "photo_thumbnail": row.get('photo_thumbnail'),
+            "last_seen": last_seen_str,
+            "price_history": price_history,
+            "agency": row.get('agency'),
+            "available_from": available_from_str,
+        },
+        "geometry": {
+            "coordinates": [row['longitude'], row['latitude']],
+            "type": "Point",
+        },
+    }
+
+
+def convert_to_geojson_feature(listing: RentListing | BuyListing) -> dict[str, Any]:
+    """Convert a single listing to GeoJSON Feature format.
+
+    Args:
+        listing: A RentListing or BuyListing model instance
+
+    Returns:
+        A GeoJSON Feature dict with properties and geometry
+    """
+    # Safely access nested additional_info
+    property_info = listing.additional_info.get("property", {}) if listing.additional_info else {}
+    listing_type = "RENT" if isinstance(listing, RentListing) else "BUY"
+
+    return {
+        "type": "Feature",
+        "properties": {
+            "listing_type": listing_type,
+            "city": "London",  # change me
+            "country": "United Kingdom",
+            "qm": listing.square_meters,
+            "qmprice": listing.price_per_square_meter,
+            "rooms": listing.number_of_bedrooms,
+            "total_price": listing.price,
+            "url": listing.url,
+            "photo_thumbnail": listing.photo_thumbnail,
+            "last_seen": listing.last_seen.isoformat(),
+            "price_history": [item.to_dict() for item in listing.price_history],
+            "agency": listing.agency,
+            "available_from": property_info.get("letDateAvailable", None),
+        },
+        "geometry": {
+            "coordinates": [
+                listing.longitude,
+                listing.latitude,
+            ],
+            "type": "Point",
+        },
+    }
+
+
 async def export_immoweb(
     repository: ListingRepository,
     output_file: str | None = None,
@@ -20,39 +129,8 @@ async def export_immoweb(
     )
     logger.info(f"Fetched {len(listings)} listings")
 
-    # Convert listings to immoweb format
-    immoweb_listings = []
-    for listing in listings:
-        immoweb_listing = {
-            "type": "Feature",
-            "properties": {
-                "city": "London",  # change me
-                "country": "United Kingdom",
-                "qm": listing.square_meters,
-                "qmprice": listing.price_per_square_meter,
-                "rooms": listing.number_of_bedrooms,
-                "total_price": listing.price,
-                "url": listing.url,
-                "photo_thumbnail": listing.photo_thumbnail,
-                "last_seen": listing.last_seen.isoformat(),
-                "price_history": [item.to_dict() for item in listing.price_history],
-                "agency": listing.agency,
-                "available_from": listing.additional_info["property"].get(
-                    "letDateAvailable", None
-                ),
-                # All other crap can be found in additional_info
-                # Prefer pulling out fields here instead of exporting the entire additional_info
-                # "info": listing.additional_info,
-            },
-            "geometry": {
-                "coordinates": [
-                    listing.longitude,
-                    listing.latitude,
-                ],
-                "type": "Point",
-            },
-        }
-        immoweb_listings.append(immoweb_listing)
+    # Convert listings to GeoJSON features using the helper function
+    immoweb_listings = [convert_to_geojson_feature(listing) for listing in listings]
 
     prefix = "var data = "
     serialized_data = {"type": "FeatureCollection", "features": immoweb_listings}