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fd7e10c193
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0330203a58 | ||
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7efa753092 |
122
geo_app/cluster_index.py
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122
geo_app/cluster_index.py
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@@ -0,0 +1,122 @@
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"""
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Server-side map clustering using Uber H3 hexagonal grid.
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Maps zoom levels to h3 resolutions and groups nodes by cell.
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"""
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import logging
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import threading
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import h3
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logger = logging.getLogger(__name__)
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# Global cache for nodes
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_nodes_cache = {}
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_cache_lock = threading.Lock()
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# Map zoom level to h3 resolution
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# Higher zoom = higher resolution = smaller cells
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ZOOM_TO_RES = {
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0: 0, 1: 0, 2: 1, 3: 1, 4: 2, 5: 2,
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6: 3, 7: 3, 8: 4, 9: 4, 10: 5, 11: 5,
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12: 6, 13: 7, 14: 8, 15: 9, 16: 10
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}
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def _fetch_nodes(db, transport_type=None):
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"""Fetch nodes from database with caching."""
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cache_key = f"nodes:{transport_type or 'all'}"
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with _cache_lock:
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if cache_key not in _nodes_cache:
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aql = """
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FOR node IN nodes
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FILTER node.node_type == 'logistics' OR node.node_type == null
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FILTER node.latitude != null AND node.longitude != null
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RETURN node
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"""
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cursor = db.aql.execute(aql)
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all_nodes = list(cursor)
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# Filter by transport type if specified
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if transport_type:
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all_nodes = [
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n for n in all_nodes
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if transport_type in (n.get('transport_types') or [])
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]
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_nodes_cache[cache_key] = all_nodes
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logger.info("Cached %d nodes for %s", len(all_nodes), cache_key)
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return _nodes_cache[cache_key]
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def get_clustered_nodes(db, west, south, east, north, zoom, transport_type=None):
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"""
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Get clustered nodes for given bounding box and zoom level.
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Uses H3 hexagonal grid to group nearby nodes.
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"""
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resolution = ZOOM_TO_RES.get(int(zoom), 5)
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nodes = _fetch_nodes(db, transport_type)
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if not nodes:
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return []
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# Group nodes by h3 cell
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cells = {}
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for node in nodes:
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lat = node.get('latitude')
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lng = node.get('longitude')
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# Skip nodes outside bounding box (rough filter)
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if lat < south or lat > north or lng < west or lng > east:
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continue
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cell = h3.latlng_to_cell(lat, lng, resolution)
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if cell not in cells:
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cells[cell] = []
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cells[cell].append(node)
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# Build results
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results = []
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for cell, nodes_in_cell in cells.items():
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count = len(nodes_in_cell)
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if count == 1:
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# Single point — return actual node data
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node = nodes_in_cell[0]
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results.append({
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'id': node.get('_key'),
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'latitude': node.get('latitude'),
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'longitude': node.get('longitude'),
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'count': 1,
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'expansion_zoom': None,
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'name': node.get('name'),
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})
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else:
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# Cluster — return cell centroid
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lat, lng = h3.cell_to_latlng(cell)
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results.append({
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'id': f"cluster-{cell}",
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'latitude': lat,
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'longitude': lng,
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'count': count,
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'expansion_zoom': min(zoom + 2, 16),
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'name': None,
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})
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logger.info("Returning %d clusters/points for zoom=%d res=%d", len(results), zoom, resolution)
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return results
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def invalidate_cache(transport_type=None):
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"""Invalidate node cache after data changes."""
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with _cache_lock:
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if transport_type:
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cache_key = f"nodes:{transport_type}"
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if cache_key in _nodes_cache:
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del _nodes_cache[cache_key]
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else:
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_nodes_cache.clear()
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logger.info("Cluster cache invalidated")
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@@ -6,6 +6,7 @@ import requests
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import graphene
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from django.conf import settings
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from .arango_client import get_db, ensure_graph
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from .cluster_index import get_clustered_nodes, invalidate_cache
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logger = logging.getLogger(__name__)
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@@ -80,6 +81,16 @@ class ProductRouteOptionType(graphene.ObjectType):
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routes = graphene.List(RoutePathType)
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class ClusterPointType(graphene.ObjectType):
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"""Cluster or individual point for map display."""
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id = graphene.String(description="UUID for points, 'cluster-N' for clusters")
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latitude = graphene.Float()
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longitude = graphene.Float()
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count = graphene.Int(description="1 for single point, >1 for cluster")
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expansion_zoom = graphene.Int(description="Zoom level to expand cluster")
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name = graphene.String(description="Node name (only for single points)")
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class Query(graphene.ObjectType):
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"""Root query."""
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MAX_EXPANSIONS = 20000
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@@ -161,6 +172,17 @@ class Query(graphene.ObjectType):
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description="Find routes from product offer nodes to destination",
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)
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clustered_nodes = graphene.List(
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ClusterPointType,
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west=graphene.Float(required=True, description="Bounding box west longitude"),
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south=graphene.Float(required=True, description="Bounding box south latitude"),
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east=graphene.Float(required=True, description="Bounding box east longitude"),
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north=graphene.Float(required=True, description="Bounding box north latitude"),
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zoom=graphene.Int(required=True, description="Map zoom level (0-16)"),
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transport_type=graphene.String(description="Filter by transport type"),
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description="Get clustered nodes for map display (server-side clustering)",
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)
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@staticmethod
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def _build_routes(db, from_uuid, to_uuid, limit):
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"""Shared helper to compute K shortest routes between two nodes."""
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@@ -740,6 +762,12 @@ class Query(graphene.ObjectType):
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return found_routes
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def resolve_clustered_nodes(self, info, west, south, east, north, zoom, transport_type=None):
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"""Get clustered nodes for map display using server-side SuperCluster."""
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db = get_db()
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clusters = get_clustered_nodes(db, west, south, east, north, zoom, transport_type)
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return [ClusterPointType(**c) for c in clusters]
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schema = graphene.Schema(query=Query)
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@@ -767,6 +795,11 @@ def _build_route_from_edges(path_edges, node_docs):
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if not path_edges:
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return None
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# Фильтруем offer edges - это не транспортные этапы, а связь оффера с локацией
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path_edges = [(f, t, e) for f, t, e in path_edges if e.get('transport_type') != 'offer']
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if not path_edges:
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return None
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stages = []
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current_edges = []
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current_type = None
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@@ -15,7 +15,8 @@ dependencies = [
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"infisicalsdk (>=1.0.12,<2.0.0)",
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"gunicorn (>=23.0.0,<24.0.0)",
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"whitenoise (>=6.7.0,<7.0.0)",
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"sentry-sdk (>=2.47.0,<3.0.0)"
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"sentry-sdk (>=2.47.0,<3.0.0)",
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"h3 (>=4.0.0,<5.0.0)"
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]
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[tool.poetry]
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