apache-sedona

import sedona.db from shapely.geometry import Point # 1. Connect to SedonaDB (single-node engine for local quickstart) sd = sedona.db.connect() # 2. Create a DataFrame with spatial data data = [ {"id": 1, "name": "Central Park", "geometry": Point(40.7812, -73.9665).wkt}, {"id": 2, "name": "Empire State Building", "geometry": Point(40.7484, -73.9857).wkt}, {"id": 3, "name": "Times Square", "geometry": Point(40.7580, -73.9855).wkt}, ] # Convert WKT strings to SedonaDB geometry objects df = sd.create_dataframe(data).with_column("geometry", sd.st_geomfromwkt(sd.column("geometry"))) print("Original DataFrame:") df.print_schema() df.show() # 3. Perform a spatial SQL query sd.create_view("nyc_landmarks", df) # Expose DataFrame as a temporary view # Find landmarks within a certain distance of a reference point reference_point = Point(40.75, -73.98).wkt # A point near Midtown result = sd.sql( f"""SELECT name, ST_Distance(geometry, ST_GeomFromWKT('{reference_point}')) as distance_to_ref FROM nyc_landmarks WHERE ST_DWithin(geometry, ST_GeomFromWKT('{reference_point}'), 0.05) -- 0.05 degrees approx. 5.5km ORDER BY distance_to_ref """ ) print("\nLandmarks within 0.05 degrees of the reference point:") result.show()