feat: wire Typesense search into backend, fix sync performance data bug

sync_typesense.py:
- Fix query string replacement: was matching 'ST_X(l.geom) as lng' but
  QUERY_BASE uses 'l.longitude as lng' — KS2/KS4 lateral joins were
  silently dropped on every sync run

backend:
- Add typesense_url/typesense_api_key settings to config.py
- Add search_schools_typesense() to data_loader.py — queries Typesense
  'schools' alias, returns URNs in relevance order with typo tolerance;
  falls back to empty list if Typesense is unavailable
- /api/schools: replace pandas str.contains with Typesense search;
  results are filtered from the DataFrame and returned in relevance order;
  graceful fallback to substring match if Typesense is down

requirements.txt: add typesense==0.21.0, numpy==1.26.4

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

backend/app.py

@@ -26,6 +26,7 @@ from .data_loader import (
     load_school_data,
     geocode_single_postcode,
     get_supplementary_data,
+    search_schools_typesense,
 )
 from .data_loader import get_data_info as get_db_info
 from .schemas import METRIC_DEFINITIONS, RANKING_COLUMNS, SCHOOL_COLUMNS
@@ -314,15 +315,19 @@ async def get_schools(
 
     # Apply filters
     if search:
-        search_lower = search.lower()
-        mask = (
-            schools_df["school_name"].str.lower().str.contains(search_lower, na=False)
-        )
-        if "address" in schools_df.columns:
-            mask = mask | schools_df["address"].str.lower().str.contains(
-                search_lower, na=False
-            )
-        schools_df = schools_df[mask]
+        ts_urns = search_schools_typesense(search)
+        if ts_urns:
+            urn_order = {urn: i for i, urn in enumerate(ts_urns)}
+            schools_df = schools_df[schools_df["urn"].isin(set(ts_urns))].copy()
+            schools_df["_ts_rank"] = schools_df["urn"].map(urn_order)
+            schools_df = schools_df.sort_values("_ts_rank").drop(columns=["_ts_rank"])
+        else:
+            # Fallback: Typesense unavailable, use substring match
+            search_lower = search.lower()
+            mask = schools_df["school_name"].str.lower().str.contains(search_lower, na=False)
+            if "address" in schools_df.columns:
+                mask = mask | schools_df["address"].str.lower().str.contains(search_lower, na=False)
+            schools_df = schools_df[mask]
 
     if local_authority:
         schools_df = schools_df[

backend/config.py

@@ -38,6 +38,10 @@ class Settings(BaseSettings):
     rate_limit_burst: int = 10  # Allow burst of requests
     max_request_size: int = 1024 * 1024  # 1MB max request size
 
+    # Typesense
+    typesense_url: str = "http://localhost:8108"
+    typesense_api_key: str = ""
+
     # Analytics
     ga_measurement_id: Optional[str] = "G-J0PCVT14NY"  # Google Analytics 4 Measurement ID
 

backend/data_loader.py

@@ -20,6 +20,47 @@ from .models import (
 from .schemas import SCHOOL_TYPE_MAP
 
 _postcode_cache: Dict[str, Tuple[float, float]] = {}
+_typesense_client = None
+
+
+def _get_typesense_client():
+    global _typesense_client
+    if _typesense_client is not None:
+        return _typesense_client
+    url = settings.typesense_url
+    key = settings.typesense_api_key
+    if not url or not key:
+        return None
+    try:
+        import typesense
+        host = url.split("//")[-1]
+        host_part, _, port_str = host.partition(":")
+        port = int(port_str) if port_str else 8108
+        _typesense_client = typesense.Client({
+            "nodes": [{"host": host_part, "port": str(port), "protocol": "http"}],
+            "api_key": key,
+            "connection_timeout_seconds": 2,
+        })
+        return _typesense_client
+    except Exception:
+        return None
+
+
+def search_schools_typesense(query: str, limit: int = 250) -> List[int]:
+    """Search Typesense. Returns URNs in relevance order, or [] if unavailable."""
+    client = _get_typesense_client()
+    if client is None:
+        return []
+    try:
+        result = client.collections["schools"].documents.search({
+            "q": query,
+            "query_by": "school_name,local_authority,postcode",
+            "per_page": min(limit, 250),
+            "typo_tokens_threshold": 1,
+        })
+        return [int(h["document"]["urn"]) for h in result.get("hits", [])]
+    except Exception:
+        return []
 
 
 def normalize_school_type(school_type: Optional[str]) -> Optional[str]:

pipeline/scripts/sync_typesense.py

@@ -158,7 +158,7 @@ def sync(typesense_url: str, api_key: str):
         query = QUERY_BASE
         if select_extra:
             # Insert extra select columns before FROM
-            query = query.replace("ST_X(l.geom) as lng", "ST_X(l.geom) as lng,\n        " + ",\n        ".join(select_extra))
+            query = query.replace("l.longitude as lng", "l.longitude as lng,\n        " + ",\n        ".join(select_extra))
         query += joins
 
         cur.execute(query)

requirements.txt

@@ -10,4 +10,6 @@ psycopg2-binary==2.9.9
 alembic==1.13.1
 slowapi==0.1.9
 secure==0.3.0
+typesense==0.21.0
+numpy==1.26.4