Add Overture Maps POI enrichment layer for place details

Ingests 20.9M North America places from Overture Maps Foundation
(release 2026-04-15.0) into PostgreSQL. Enriches /api/place responses
with phone, website, and brand data via spatial + fuzzy name matching
when OSM extratags are sparse.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
Matt 2026-04-21 16:51:25 +00:00
commit 65693d15aa
6 changed files with 597 additions and 0 deletions

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@ -39,6 +39,7 @@ features:
has_traffic_overlay: true
has_landclass: false
has_address_book_write: false
has_overture_enrichment: true
defaults:
center: [42.5736, -114.6066]

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@ -34,6 +34,7 @@ features:
has_traffic_overlay: false
has_landclass: false
has_address_book_write: true
has_overture_enrichment: false
defaults:
center: [44.0, -114.0]

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@ -39,6 +39,7 @@ features:
has_traffic_overlay: true
has_landclass: true
has_address_book_write: true
has_overture_enrichment: false
defaults:
center: [44.0, -114.0]

170
lib/overture.py Normal file
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@ -0,0 +1,170 @@
"""
Overture Maps enrichment layer.
Provides lookup functions against the local PostgreSQL Overture Places database.
Two strategies:
1. find_by_osm_id exact match via OSM cross-reference index
2. find_by_coords_and_name spatial + fuzzy name fallback
Connection pool is lazy-initialized on first call. If PostgreSQL is unreachable,
functions return None gracefully (feature degrades, doesn't crash).
"""
import json
import os
import psycopg2
import psycopg2.pool
from .utils import setup_logging
logger = setup_logging('recon.overture')
_pool = None
_pool_failed = False
# Map full OSM type names to single-letter codes used in Overture sources
OSM_TYPE_MAP = {
'N': 'n', 'W': 'w', 'R': 'r',
'node': 'n', 'way': 'w', 'relation': 'r',
'n': 'n', 'w': 'w', 'r': 'r',
}
def _get_pool():
"""Lazy-init the connection pool. Returns None if Postgres is unreachable."""
global _pool, _pool_failed
if _pool is not None:
return _pool
if _pool_failed:
return None
try:
_pool = psycopg2.pool.SimpleConnectionPool(
minconn=1,
maxconn=3,
host=os.environ.get('OVERTURE_DB_HOST', 'localhost'),
port=int(os.environ.get('OVERTURE_DB_PORT', '5432')),
dbname=os.environ.get('OVERTURE_DB_NAME', 'overture'),
user=os.environ.get('OVERTURE_DB_USER', 'overture'),
password=os.environ.get('OVERTURE_DB_PASSWORD', ''),
connect_timeout=5,
)
logger.info("Overture PostgreSQL connection pool initialized")
return _pool
except Exception as e:
_pool_failed = True
logger.warning(f"Overture PostgreSQL unavailable, enrichment disabled: {e}")
return None
def _query(sql, params):
"""Execute a query and return the first row as a dict, or None."""
pool = _get_pool()
if pool is None:
return None
conn = None
try:
conn = pool.getconn()
with conn.cursor() as cur:
cur.execute(sql, params)
row = cur.fetchone()
if row is None:
return None
cols = [desc[0] for desc in cur.description]
return dict(zip(cols, row))
except Exception as e:
logger.warning(f"Overture query error: {e}")
if conn:
try:
conn.rollback()
except Exception:
pass
return None
finally:
if conn:
try:
pool.putconn(conn)
except Exception:
pass
def _format_result(row, match_method):
"""Convert a database row dict to the enrichment result shape."""
if not row:
return None
socials = row.get('socials')
if isinstance(socials, str):
try:
socials = json.loads(socials)
except (json.JSONDecodeError, TypeError):
socials = None
return {
'phone': row.get('phone'),
'website': row.get('website'),
'socials': socials,
'brand_name': row.get('brand_name'),
'brand_wikidata': row.get('brand_wikidata'),
'basic_category': row.get('basic_category'),
'confidence': row.get('confidence'),
'gers_id': row.get('id'),
'match_method': match_method,
}
def find_by_osm_id(osm_type, osm_id):
"""
Look up an Overture place by its OSM cross-reference.
Args:
osm_type: OSM type 'N', 'W', 'R', 'node', 'way', 'relation', or single letter
osm_id: OSM numeric ID
Returns:
Enrichment dict or None
"""
type_letter = OSM_TYPE_MAP.get(osm_type)
if not type_letter:
return None
row = _query(
"""SELECT id, name, basic_category, confidence,
phone, website, socials, brand_name, brand_wikidata
FROM places
WHERE osm_type = %s AND osm_id = %s
LIMIT 1""",
(type_letter, int(osm_id))
)
return _format_result(row, 'osm_xref')
def find_by_coords_and_name(lat, lon, name, radius_m=100):
"""
Look up an Overture place by spatial proximity + fuzzy name match.
Args:
lat: Latitude
lon: Longitude
name: Place name to fuzzy-match
radius_m: Search radius in meters (default 100)
Returns:
Enrichment dict or None
"""
if not name or not lat or not lon:
return None
row = _query(
"""SELECT id, name, basic_category, confidence,
phone, website, socials, brand_name, brand_wikidata,
similarity(name, %s) AS sim
FROM places
WHERE ST_DWithin(geometry::geography, ST_MakePoint(%s, %s)::geography, %s)
AND similarity(name, %s) > 0.4
ORDER BY sim DESC, ST_Distance(geometry::geography, ST_MakePoint(%s, %s)::geography) ASC
LIMIT 1""",
(name, lon, lat, radius_m, name, lon, lat)
)
return _format_result(row, 'coord_name_fuzzy')

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@ -1,5 +1,6 @@
"""
Place detail proxy local Nominatim first, Overpass API fallback, SQLite cache.
Overture Maps enrichment layer fills sparse extratags (phone, website, brand).
Provides get_place_detail(osm_type, osm_id) which returns a cleaned dict
matching the response shape for /api/place/<osm_type>/<osm_id>.
@ -82,6 +83,77 @@ def cache_put(osm_type, osm_id, data, source):
db.commit()
# ── Overture enrichment ─────────────────────────────────────────────────
def _enrich_with_overture(result, osm_type, osm_id):
"""
Attempt to enrich a place result with Overture Maps data.
Fills sparse extratags (phone, website, brand) without overwriting existing values.
Returns the (possibly enriched) result dict.
"""
try:
from .deployment_config import get_deployment_config
deploy_config = get_deployment_config()
features = deploy_config.get('features', {})
if not features.get('has_overture_enrichment', False):
return result
except Exception:
return result
try:
from .overture import find_by_osm_id, find_by_coords_and_name
except ImportError:
logger.debug("Overture module not available")
return result
enrichment = None
match_method = None
# Strategy 1: OSM cross-reference (exact)
enrichment = find_by_osm_id(osm_type, osm_id)
if enrichment:
match_method = 'osm_xref'
# Strategy 2: Coordinate + name fuzzy (fallback)
if not enrichment and result.get('centroid') and result.get('name'):
centroid = result['centroid']
if centroid.get('lat') and centroid.get('lon'):
enrichment = find_by_coords_and_name(
centroid['lat'], centroid['lon'], result['name']
)
if enrichment:
match_method = 'coord_name_fuzzy'
if not enrichment:
return result
# Fill sparse extratags (never overwrite existing non-null values)
extratags = result.get('extratags', {})
fill_map = [
('phone', 'phone'),
('website', 'website'),
('brand', 'brand_name'),
('brand:wikidata', 'brand_wikidata'),
]
for osm_key, overture_key in fill_map:
if not extratags.get(osm_key) and enrichment.get(overture_key):
extratags[osm_key] = enrichment[overture_key]
result['extratags'] = extratags
# Add source metadata
result['sources'] = {
'primary': result.get('source', 'unknown'),
'enrichment': 'overture',
'overture_match_method': match_method,
'overture_gers_id': enrichment.get('gers_id'),
'overture_confidence': enrichment.get('confidence'),
'overture_basic_category': enrichment.get('basic_category'),
}
logger.debug(f"Overture enrichment for {osm_type}/{osm_id}: {match_method}")
return result
# ── Nominatim parsing ───────────────────────────────────────────────────
# Nominatim address array uses rank_address to indicate what each entry is.
@ -368,6 +440,7 @@ def get_place_detail(osm_type, osm_id):
logger.warning(f"Nominatim error for {osm_type}/{osm_id}: {e}")
if nominatim_result:
nominatim_result = _enrich_with_overture(nominatim_result, osm_type, osm_id)
cache_put(osm_type, osm_id, nominatim_result, 'nominatim_local')
return nominatim_result, 200
@ -398,6 +471,7 @@ def get_place_detail(osm_type, osm_id):
logger.warning(f"Overpass error for {osm_type}/{osm_id}: {e}")
if overpass_result:
overpass_result = _enrich_with_overture(overpass_result, osm_type, osm_id)
cache_put(osm_type, osm_id, overpass_result, 'overpass')
return overpass_result, 200

350
scripts/overture_import.py Normal file
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@ -0,0 +1,350 @@
#!/usr/bin/env python3
"""Overture Maps Places → PostgreSQL import script (v2).
Downloads Overture Places Parquet from S3 via DuckDB (public bucket, no credentials),
filters to North America bounding box, and inserts into local PostgreSQL with PostGIS.
Usage:
cd /opt/recon && venv/bin/python scripts/overture_import.py
Re-runnable (idempotent via UPSERT).
"""
import json
import logging
import os
import re
import sys
import time
import duckdb
import psycopg2
import psycopg2.extras
logging.basicConfig(
level=logging.INFO,
format='%(asctime)s %(levelname)s %(message)s',
datefmt='%H:%M:%S'
)
log = logging.getLogger('overture_import')
# --- Config ---
OVERTURE_RELEASE = '2026-04-15.0'
S3_PATH = f's3://overturemaps-us-west-2/release/{OVERTURE_RELEASE}/theme=places/type=place/*'
# North America bounding box (generous — includes Hawaii, Puerto Rico, Canada)
BBOX = {
'xmin': -170.0,
'xmax': -50.0,
'ymin': 15.0,
'ymax': 85.0,
}
BATCH_SIZE = 50_000
OSM_RECORD_RE = re.compile(r'^([nwr])(\d+)@\d+$')
DB_CONFIG = {
'host': os.environ.get('OVERTURE_DB_HOST', 'localhost'),
'port': int(os.environ.get('OVERTURE_DB_PORT', '5432')),
'dbname': os.environ.get('OVERTURE_DB_NAME', 'overture'),
'user': os.environ.get('OVERTURE_DB_USER', 'overture'),
'password': os.environ.get('OVERTURE_DB_PASSWORD', ''),
}
def create_table(conn):
"""Create places table and indexes if they don't exist."""
with conn.cursor() as cur:
cur.execute("""
CREATE TABLE IF NOT EXISTS places (
id TEXT PRIMARY KEY,
geometry GEOMETRY(Point, 4326),
name TEXT,
basic_category TEXT,
confidence REAL,
phone TEXT,
website TEXT,
socials JSONB,
brand_name TEXT,
brand_wikidata TEXT,
osm_type CHAR(1),
osm_id BIGINT,
source_record_id TEXT,
raw_sources JSONB
);
""")
cur.execute("""
CREATE INDEX IF NOT EXISTS idx_places_osm
ON places(osm_type, osm_id) WHERE osm_type IS NOT NULL;
""")
cur.execute("""
CREATE INDEX IF NOT EXISTS idx_places_geom
ON places USING GIST(geometry);
""")
cur.execute("""
CREATE INDEX IF NOT EXISTS idx_places_name_trgm
ON places USING GIN(name gin_trgm_ops);
""")
conn.commit()
log.info('Table and indexes ready')
def parse_osm_ref(sources):
"""Extract OSM type letter and ID from Overture sources array."""
if not sources:
return None, None, None
for src in sources:
record_id = None
if isinstance(src, dict):
record_id = src.get('record_id', '')
elif hasattr(src, '__getitem__'):
# DuckDB struct — try attribute access
try:
record_id = src['record_id']
except (KeyError, TypeError, IndexError):
pass
if not record_id:
continue
m = OSM_RECORD_RE.match(str(record_id))
if m:
return m.group(1), int(m.group(2)), str(record_id)
return None, None, None
def run_import():
"""Main import: DuckDB reads S3 Parquet → PostgreSQL via chunked OFFSET/LIMIT."""
log.info(f'Overture release: {OVERTURE_RELEASE}')
log.info(f'S3 path: {S3_PATH}')
log.info(f'Bounding box: {BBOX}')
# Connect to PostgreSQL
conn = psycopg2.connect(**DB_CONFIG)
conn.autocommit = False
create_table(conn)
# Set up DuckDB with httpfs and spatial for S3 access
duck = duckdb.connect()
duck.execute("INSTALL httpfs; LOAD httpfs;")
duck.execute("INSTALL spatial; LOAD spatial;")
duck.execute("SET s3_region='us-west-2';")
# Use a materialized approach: DuckDB query → Arrow → iterate in Python
query = f"""
SELECT
id,
ST_X(geometry) AS lon,
ST_Y(geometry) AS lat,
names.primary AS name,
basic_category,
confidence,
phones,
websites,
socials,
brand,
sources
FROM read_parquet('{S3_PATH}', hive_partitioning=true)
WHERE bbox.xmin >= {BBOX['xmin']}
AND bbox.xmax <= {BBOX['xmax']}
AND bbox.ymin >= {BBOX['ymin']}
AND bbox.ymax <= {BBOX['ymax']}
"""
log.info('Starting DuckDB query against S3 (this will take several minutes)...')
t_start = time.time()
# Execute and fetch all as Arrow for efficient iteration
result_rel = duck.sql(query)
upsert_sql = """
INSERT INTO places (id, geometry, name, basic_category, confidence,
phone, website, socials, brand_name, brand_wikidata,
osm_type, osm_id, source_record_id, raw_sources)
VALUES %s
ON CONFLICT (id) DO UPDATE SET
geometry = EXCLUDED.geometry,
name = EXCLUDED.name,
basic_category = EXCLUDED.basic_category,
confidence = EXCLUDED.confidence,
phone = EXCLUDED.phone,
website = EXCLUDED.website,
socials = EXCLUDED.socials,
brand_name = EXCLUDED.brand_name,
brand_wikidata = EXCLUDED.brand_wikidata,
osm_type = EXCLUDED.osm_type,
osm_id = EXCLUDED.osm_id,
source_record_id = EXCLUDED.source_record_id,
raw_sources = EXCLUDED.raw_sources
"""
template = """(
%(id)s,
ST_SetSRID(ST_MakePoint(%(lon)s, %(lat)s), 4326),
%(name)s,
%(basic_category)s,
%(confidence)s,
%(phone)s,
%(website)s,
%(socials)s::jsonb,
%(brand_name)s,
%(brand_wikidata)s,
%(osm_type)s,
%(osm_id)s,
%(source_record_id)s,
%(raw_sources)s::jsonb
)"""
total = 0
osm_refs = 0
batch = []
log.info('DuckDB query executing, fetching results in chunks...')
# Fetch in chunks using fetchmany on the relation
chunk_size = BATCH_SIZE
while True:
chunk = result_rel.fetchmany(chunk_size)
if not chunk:
break
for row in chunk:
row_id = row[0]
lon = row[1]
lat = row[2]
name = row[3]
basic_cat = row[4]
conf = row[5]
phones = row[6]
websites = row[7]
socials_raw = row[8]
brand_raw = row[9]
sources_raw = row[10]
if lon is None or lat is None:
continue
# Phone: first element of VARCHAR[]
phone = None
if phones and len(phones) > 0:
phone = str(phones[0]) if phones[0] else None
# Website: first element of VARCHAR[]
website = None
if websites and len(websites) > 0:
website = str(websites[0]) if websites[0] else None
# Socials: VARCHAR[] → JSON array of strings
socials_json = None
if socials_raw and len(socials_raw) > 0:
socials_json = json.dumps([str(s) for s in socials_raw if s])
# Brand: struct with wikidata and names.primary
brand_name = None
brand_wikidata = None
if brand_raw:
try:
if isinstance(brand_raw, dict):
brand_wikidata = brand_raw.get('wikidata')
names_struct = brand_raw.get('names')
if names_struct and isinstance(names_struct, dict):
brand_name = names_struct.get('primary')
else:
# DuckDB struct — access by key
brand_wikidata = brand_raw['wikidata'] if 'wikidata' in dir(brand_raw) else None
try:
brand_wikidata = brand_raw[0] # wikidata is first field
names_struct = brand_raw[1] # names is second field
if names_struct:
brand_name = names_struct[0] # primary is first field
except (IndexError, TypeError):
pass
except Exception:
pass
# Sources: parse OSM cross-reference
sources_list = None
if sources_raw:
if isinstance(sources_raw, (list, tuple)):
sources_list = []
for s in sources_raw:
if isinstance(s, dict):
sources_list.append(s)
else:
# DuckDB struct tuple — convert
try:
sources_list.append({
'dataset': s[1] if len(s) > 1 else None,
'record_id': s[3] if len(s) > 3 else None,
})
except (TypeError, IndexError):
pass
osm_type_letter, osm_id_val, source_record_id = parse_osm_ref(sources_list)
if osm_type_letter:
osm_refs += 1
raw_sources_json = json.dumps(sources_list) if sources_list else None
batch.append({
'id': row_id,
'lon': float(lon),
'lat': float(lat),
'name': name,
'basic_category': basic_cat,
'confidence': float(conf) if conf is not None else None,
'phone': phone,
'website': website,
'socials': socials_json,
'brand_name': brand_name,
'brand_wikidata': brand_wikidata,
'osm_type': osm_type_letter,
'osm_id': osm_id_val,
'source_record_id': source_record_id,
'raw_sources': raw_sources_json,
})
if len(batch) >= BATCH_SIZE:
with conn.cursor() as cur:
psycopg2.extras.execute_values(
cur, upsert_sql, batch,
template=template,
page_size=BATCH_SIZE
)
conn.commit()
total += len(batch)
elapsed = time.time() - t_start
rate = total / elapsed if elapsed > 0 else 0
log.info(f'Inserted {total:,} rows ({osm_refs:,} OSM xrefs) '
f'[{rate:.0f} rows/sec, {elapsed:.0f}s elapsed]')
batch = []
# Flush remaining
if batch:
with conn.cursor() as cur:
psycopg2.extras.execute_values(
cur, upsert_sql, batch,
template=template,
page_size=BATCH_SIZE
)
conn.commit()
total += len(batch)
duck.close()
# Final stats
elapsed = time.time() - t_start
log.info(f'Import complete: {total:,} rows, {osm_refs:,} OSM cross-refs, '
f'{elapsed:.0f}s total ({total/elapsed:.0f} rows/sec)')
# Verify
with conn.cursor() as cur:
cur.execute("SELECT count(*) FROM places")
count = cur.fetchone()[0]
cur.execute("SELECT count(*) FROM places WHERE osm_type IS NOT NULL")
osm_count = cur.fetchone()[0]
log.info(f'Final table: {count:,} total rows, {osm_count:,} with OSM cross-references')
conn.close()
if __name__ == '__main__':
run_import()