id,page,ref,title,content,breadcrumbs,references spatialite:importing-geojson-polygons-using-shapely,spatialite,importing-geojson-polygons-using-shapely,Importing GeoJSON polygons using Shapely,"Another common form of polygon data is the GeoJSON format. This can be imported into SpatiaLite directly, or by using the Shapely Python library. Who's On First is an excellent source of openly licensed GeoJSON polygons. Let's import the geographical polygon for Wales. First, we can use the Who's On First Spelunker tool to find the record for Wales: spelunker.whosonfirst.org/id/404227475 That page includes a link to the GeoJSON record, which can be accessed here: data.whosonfirst.org/404/227/475/404227475.geojson Here's Python code to create a SQLite database, enable SpatiaLite, create a places table and then add a record for Wales: import sqlite3 conn = sqlite3.connect(""places.db"") # Enable SpatialLite extension conn.enable_load_extension(True) conn.load_extension(""/usr/local/lib/mod_spatialite.dylib"") # Create the masic countries table conn.execute(""select InitSpatialMetadata(1)"") conn.execute( ""create table places (id integer primary key, name text);"" ) # Add a MULTIPOLYGON Geometry column conn.execute( ""SELECT AddGeometryColumn('places', 'geom', 4326, 'MULTIPOLYGON', 2);"" ) # Add a spatial index against the new column conn.execute(""SELECT CreateSpatialIndex('places', 'geom');"") # Now populate the table from shapely.geometry.multipolygon import MultiPolygon from shapely.geometry import shape import requests geojson = requests.get( ""https://data.whosonfirst.org/404/227/475/404227475.geojson"" ).json() # Convert to ""Well Known Text"" format wkt = shape(geojson[""geometry""]).wkt # Insert and commit the record conn.execute( ""INSERT INTO places (id, name, geom) VALUES(null, ?, GeomFromText(?, 4326))"", (""Wales"", wkt), ) conn.commit()","[""SpatiaLite""]","[{""href"": ""https://pypi.org/project/Shapely/"", ""label"": ""Shapely""}, {""href"": ""https://whosonfirst.org/"", ""label"": ""Who's On First""}, {""href"": ""https://spelunker.whosonfirst.org/id/404227475/"", ""label"": ""spelunker.whosonfirst.org/id/404227475""}, {""href"": ""https://data.whosonfirst.org/404/227/475/404227475.geojson"", ""label"": ""data.whosonfirst.org/404/227/475/404227475.geojson""}]" spatialite:making-use-of-a-spatial-index,spatialite,making-use-of-a-spatial-index,Making use of a spatial index,"SpatiaLite spatial indexes are R*Trees. They allow you to run efficient bounding box queries using a sub-select, with a similar pattern to that used for Searches using custom SQL . In the above example, the resulting index will be called idx_museums_point_geom . This takes the form of a SQLite virtual table. You can inspect its contents using the following query: select * from idx_museums_point_geom limit 10; Here's a live example: timezones-api.datasette.io/timezones/idx_timezones_Geometry pkid xmin xmax ymin ymax 1 -8.601725578308105 -2.4930307865142822 4.162120819091797 10.74019718170166 2 -3.2607860565185547 1.27329421043396 4.539252281188965 11.174856185913086 3 32.997581481933594 47.98238754272461 3.3974475860595703 14.894054412841797 4 -8.66890811920166 11.997337341308594 18.9681453704834 37.296207427978516 5 36.43336486816406 43.300174713134766 12.354820251464844 18.070993423461914 You can now construct efficient bounding box queries that will make use of the index like this: select * from museums where museums.rowid in ( SELECT pkid FROM idx_museums_point_geom -- left-hand-edge of point > left-hand-edge of bbox (minx) where xmin > :bbox_minx -- right-hand-edge of point < right-hand-edge of bbox (maxx) and xmax < :bbox_maxx -- bottom-edge of point > bottom-edge of bbox (miny) and ymin > :bbox_miny -- top-edge of point < top-edge of bbox (maxy) and ymax < :bbox_maxy ); Spatial indexes can be created against polygon columns as well as point columns, in which case they will represent the minimum bounding rectangle of that polygon. This is useful for accelerating within queries, as seen in the Timezones API example.","[""SpatiaLite""]","[{""href"": ""https://timezones-api.datasette.io/timezones/idx_timezones_Geometry"", ""label"": ""timezones-api.datasette.io/timezones/idx_timezones_Geometry""}]" spatialite:spatialite-warning,spatialite,spatialite-warning,Warning,"The SpatiaLite extension adds a large number of additional SQL functions , some of which are not be safe for untrusted users to execute: they may cause the Datasette server to crash. You should not expose a SpatiaLite-enabled Datasette instance to the public internet without taking extra measures to secure it against potentially harmful SQL queries. The following steps are recommended: Disable arbitrary SQL queries by untrusted users. See Controlling the ability to execute arbitrary SQL for ways to do this. The easiest is to start Datasette with the datasette --setting default_allow_sql off option. Define Canned queries with the SQL queries that use SpatiaLite functions that you want people to be able to execute. The Datasette SpatiaLite tutorial includes detailed instructions for running SpatiaLite safely using these techniques","[""SpatiaLite""]","[{""href"": ""https://www.gaia-gis.it/gaia-sins/spatialite-sql-5.0.1.html"", ""label"": ""a large number of additional SQL functions""}, {""href"": ""https://datasette.io/tutorials/spatialite"", ""label"": ""Datasette SpatiaLite tutorial""}]"