SpatiaLite Tutorial

GeoAlchemy 2’s main target is PostGIS. But GeoAlchemy 2 also supports SpatiaLite, the spatial extension to SQLite. This tutorial describes how to use GeoAlchemy 2 with SpatiaLite. It’s based on the ORM Tutorial, which you may want to read first.

Connect to the DB

Just like when using PostGIS connecting to a SpatiaLite database requires an Engine. This is how you create one for SpatiaLite:

>>> from geoalchemy2 import load_spatialite
>>> from sqlalchemy import create_engine
>>> from sqlalchemy.event import listen
>>> engine = create_engine("sqlite:///gis.db", echo=True)
>>> listen(engine, "connect", load_spatialite)

The call to create_engine creates an engine bound to the database file gis.db. After that a connect listener is registered on the engine. The listener is responsible for loading the SpatiaLite extension, which is a necessary operation for using SpatiaLite through SQL. The path to the mod_spatialite file should be stored in the SPATIALITE_LIBRARY_PATH environment variable before using the load_spatialite function.

At this point you can test that you are able to connect to the database:

>> conn = engine.connect()

Note that this call will internally call the load_spatialite function, which can take some time to execute on a new database because it actually calls the InitSpatialMetaData function from SpatiaLite (it is possible to reduce this time by loading only the required SRIDs, see geoalchemy2.admin.dialects.sqlite.load_spatialite()). Then you can also check that the gis.db SQLite database file was created on the file system.

Note that when InitSpatialMetaData is executed again it will report an error:

InitSpatiaMetaData() error:"table spatial_ref_sys already exists"

You can safely ignore that error.

Before going further we can close the current connection:

>>> conn.close()

Declare a Mapping

Now that we have a working connection we can go ahead and create a mapping between a Python class and a database table:

>>> from sqlalchemy.orm import declarative_base
>>> from sqlalchemy import Column, Integer, String
>>> from geoalchemy2 import Geometry
>>> Base = declarative_base()
>>> class Lake(Base):
...     __tablename__ = "lake"
...     id = Column(Integer, primary_key=True)
...     name = Column(String)
...     geom = Column(Geometry(geometry_type="POLYGON"))

From the user point of view this works in the same way as with PostGIS. The difference is that internally the RecoverGeometryColumn and DiscardGeometryColumn management functions will be used for the creation and removal of the geometry column.

Create the Table in the Database

We can now create the lake table in the gis.db database:

>>> Lake.__table__.create(engine)

If we wanted to drop the table we’d use:

>>> Lake.__table__.drop(engine)

There’s nothing specific to SpatiaLite here.

Create a Session

When using the SQLAlchemy ORM the ORM interacts with the database through a Session.

>>> from sqlalchemy.orm import sessionmaker
>>> Session = sessionmaker(bind=engine)
>>> session = Session()

The session is associated with our SpatiaLite Engine. Again, there’s nothing specific to SpatiaLite here.

Add New Objects

We can now create and insert new Lake objects into the database, the same way we’d do it using GeoAlchemy 2 with PostGIS.

>>> lake = Lake(name="Majeur", geom="POLYGON((0 0,1 0,1 1,0 1,0 0))")
>>> session.add(lake)
>>> session.commit()

We can now query the database for Majeur:

>>> our_lake = session.query(Lake).filter_by(name="Majeur").first()
>>> our_lake.geom
<WKBElement at 0x9af594c; "0103000000010000000500000000000000000000000000000000000000000000000000f03f0000000000000000000000000000f03f000000000000f03f0000000000000000000000000000f03f00000000000000000000000000000000">

Let’s add more lakes:

>>> session.add_all([
...     Lake(name="Garde", geom="POLYGON((1 0,3 0,3 2,1 2,1 0))"),
...     Lake(name="Orta", geom="POLYGON((3 0,6 0,6 3,3 3,3 0))")
... ])
>>> session.commit()


Let’s make a simple, non-spatial, query:

>>> query = session.query(Lake).order_by(
>>> for lake in query:
...     print(

Now a spatial query:

>>> from geolachemy2 import WKTElement
>>> query = session.query(Lake).filter(
...             func.ST_Contains(Lake.geom, WKTElement("POINT(4 1)")))
>>> for lake in query:
...     print(

Here’s another spatial query, using ST_Intersects this time:

>>> query = session.query(Lake).filter(
...             Lake.geom.ST_Intersects(WKTElement("LINESTRING(2 1,4 1)")))
>>> for lake in query:
...     print(

We can also apply relationship functions to geoalchemy2.elements.WKBElement. For example:

>>> lake = session.query(Lake).filter_by(name="Garde").one()
>>> print(session.scalar(lake.geom.ST_Intersects(WKTElement("LINESTRING(2 1,4 1)"))))

session.scalar allows executing a clause and returning a scalar value (an integer value in this case).

The value 1 indicates that the lake “Garde” does intersects the LINESTRING(2 1,4 1) geometry. See the SpatiaLite SQL functions reference list for more information.

Function mapping

Several functions have different names in SpatiaLite than in PostGIS. The GeoAlchemy 2 package is based on the PostGIS syntax but it is possible to automatically translate the queries into SpatiaLite ones. For example, the function ST_GeomFromEWKT is automatically translated into GeomFromEWKT. Unfortunately, only a few functions are automatically mapped (mainly the ones internally used by GeoAlchemy 2). Nevertheless, it is possible to define new mappings in order to translate the queries automatically. Here is an example to register a mapping for the ST_Buffer function:

>>> geoalchemy2.functions.register_sqlite_mapping(
...     {"ST_Buffer": "Buffer"}
... )

After this command, all ST_Buffer calls in the queries will be translated to Buffer calls when the query is executed on a SQLite DB.

A more complex example is provided for when the PostGIS function should be mapped depending on the given parameters. For example, the ST_Buffer function can actually be translate into either the Buffer function or the SingleSidedBuffer function (only when side=right or side=left is passed). See the Function translation for specific dialect example in the gallery.

GeoPackage format

Starting from the version 4.2 of Spatialite, it is possible to use GeoPackage files as DB containers. GeoAlchemy 2 is able to handle most of the GeoPackage features automatically if the GeoPackage dialect is used (i.e. the DB URL starts with gpkg:///) and the SpatiaLite extension is loaded. Usually, this extension should be loaded using the load_spatialite_gpkg listener:

>>> from geoalchemy2 import load_spatialite_gpkg
>>> from sqlalchemy import create_engine
>>> from sqlalchemy.event import listen
>>> engine = create_engine("gpkg:///gis.gpkg", echo=True)
>>> listen(engine, "connect", load_spatialite_gpkg)

When using the load_spatialite_gpkg listener on a DB recognized as a GeoPackage, specific processes are activated:

  • the base tables are created if they are missing,

  • the Amphibious mode is enabled using the EnableGpkgAmphibiousMode function,

  • the VirtualGPKG wrapper is activated using the AutoGpkgStart function.

After that it should be possible to use a GeoPackage the same way as a standard SpatiaLite database. GeoAlchemy 2 should be able to handle the following features in a transparent way for the user:

  • create/drop spatial tables,

  • automatically create/drop spatial indexes if required,

  • reflect spatial tables,

  • use spatial functions on inserted geometries.


If you want to use the ST_Transform function you should call the geoalchemy2.admin.dialects.geopackage.create_spatial_ref_sys_view() first.

Further Reference