teljes backend_mentés

backend/app/api/v1/endpoints/search.py

@@ -1,24 +1,90 @@
 # /opt/docker/dev/service_finder/backend/app/api/v1/endpoints/search.py
 from fastapi import APIRouter, Depends
 from sqlalchemy.ext.asyncio import AsyncSession
-from sqlalchemy import text
+from sqlalchemy import select, func, or_
+from sqlalchemy.orm import selectinload
 from app.db.session import get_db
 from app.api.deps import get_current_user
-from app.models.marketplace.organization import Organization # JAVÍTVA
+from app.models.marketplace.organization import Organization, Branch
+from geoalchemy2 import WKTElement
+from typing import Optional
 
 router = APIRouter()
 
 @router.get("/match")
-async def match_service(lat: float, lng: float, radius: int = 20, db: AsyncSession = Depends(get_db), current_user = Depends(get_current_user)):
-    # PostGIS alapú keresés a fleet.branches táblában (a régi locations helyett)
-    query = text("""
-        SELECT o.id, o.name, b.city,
-        ST_Distance(b.location, ST_SetSRID(ST_MakePoint(:lng, :lat), 4326)::geography) / 1000 as distance
-        FROM fleet.organizations o
-        JOIN fleet.branches b ON o.id = b.organization_id
-        WHERE o.is_active = True AND b.is_active = True
-        AND ST_DWithin(b.location, ST_SetSRID(ST_MakePoint(:lng, :lat), 4326)::geography, :r * 1000)
-        ORDER BY distance ASC
-    """)
-    result = await db.execute(query, {"lat": lat, "lng": lng, "r": radius})
-    return {"results": [dict(row._mapping) for row in result.fetchall()]}
+async def match_service(
+    lat: Optional[float] = None,
+    lng: Optional[float] = None,
+    radius_km: float = 20.0,
+    sort_by: str = "distance",
+    db: AsyncSession = Depends(get_db),
+    current_user = Depends(get_current_user)
+):
+    """
+    Geofencing keresőmotor PostGIS segítségével.
+    Ha nincs megadva lat/lng, akkor nem alkalmazunk távolságszűrést.
+    """
+    # Alap lekérdezés: aktív szervezetek és telephelyek
+    query = select(
+        Organization.id,
+        Organization.name,
+        Branch.city,
+        Branch.branch_rating,
+        Branch.location
+    ).join(
+        Branch, Organization.id == Branch.organization_id
+    ).where(
+        Organization.is_active == True,
+        Branch.is_deleted == False
+    )
+    
+    # Távolság számítás és szűrés, ha van koordináta
+    if lat is not None and lng is not None:
+        # WKT pont létrehozása a felhasználó helyéhez
+        user_location = WKTElement(f'POINT({lng} {lat})', srid=4326)
+        
+        # Távolság kiszámítása méterben (ST_DistanceSphere)
+        distance_col = func.ST_DistanceSphere(Branch.location, user_location).label("distance_meters")
+        query = query.add_columns(distance_col)
+        
+        # Szűrés a sugárra (ST_DWithin) - a távolság méterben, radius_km * 1000
+        query = query.where(
+            func.ST_DWithin(Branch.location, user_location, radius_km * 1000)
+        )
+    else:
+        # Ha nincs koordináta, ne legyen distance oszlop
+        distance_col = None
+    
+    # Rendezés a sort_by paraméter alapján
+    if sort_by == "distance" and lat is not None and lng is not None:
+        query = query.order_by(distance_col.asc())
+    elif sort_by == "rating":
+        query = query.order_by(Branch.branch_rating.desc())
+    elif sort_by == "price":
+        # Jelenleg nincs ár információ, ezért rendezés alapértelmezettként (pl. név)
+        query = query.order_by(Organization.name.asc())
+    else:
+        # Alapértelmezett rendezés: távolság, ha van, különben név
+        if distance_col is not None:
+            query = query.order_by(distance_col.asc())
+        else:
+            query = query.order_by(Organization.name.asc())
+    
+    # Lekérdezés végrehajtása
+    result = await db.execute(query)
+    rows = result.fetchall()
+    
+    # Eredmények formázása
+    results = []
+    for row in rows:
+        row_dict = {
+            "id": row.id,
+            "name": row.name,
+            "city": row.city,
+            "rating": row.branch_rating,
+        }
+        if lat is not None and lng is not None:
+            row_dict["distance_km"] = round(row.distance_meters / 1000, 2) if row.distance_meters else None
+        results.append(row_dict)
+    
+    return {"results": results}