shapefile-to-sqlite 0.4.2

Load shapefiles into a SQLite (optionally SpatiaLite) database

shapefile-to-sqlite

Load shapefiles into a SQLite (optionally SpatiaLite) database.

Project background: Things I learned about shapefiles building shapefile-to-sqlite

How to install

$ pip install shapefile-to-sqlite

How to use

You can run this tool against a shapefile file like so:

$ shapefile-to-sqlite my.db features.shp

This will load the geometries as GeoJSON in a text column.

Using with SpatiaLite

If you have SpatiaLite available you can load them as SpatiaLite geometries like this:

$ shapefile-to-sqlite my.db features.shp --spatialite

The data will be loaded into a table called features - based on the name of the shapefile. You can specify an alternative table name using --table:

$ shapefile-to-sqlite my.db features.shp --table=places --spatialite

The tool will search for the SpatiaLite module in the following locations:

• /usr/lib/x86_64-linux-gnu/mod_spatialite.so
• /usr/local/lib/mod_spatialite.dylib

If you have installed the module in another location, you can use the --spatialite_mod=xxx option to specify where:

$ shapefile-to-sqlite my.db features.shp \
    --spatialite_mod=/usr/lib/mod_spatialite.dylib

You can use the --spatial-index option to create a spatial index on the geometry column:

$ shapefile-to-sqlite my.db features.shp --spatial-index

You can omit --spatialite if you use either --spatialite-mod or --spatial-index.

Projections

By default, this tool will attempt to convert geometries in the shapefile to the WGS 84 projection, for best conformance with the GeoJSON specification.

If you want it to leave the data in whatever projection was used by the shapefile, use the --crs=keep option.

You can convert the data to another output projection by passing it to the --crs option. For example, to convert to EPSG:2227 (California zone 3) use --crs=espg:2227.

The full list of formats accepted by the --crs option is documented here.

Extracting columns

If your data contains columns with a small number of heavily duplicated values - the names of specific agencies responsible for parcels of land for example - you can extract those columns into separate lookup tables referenced by foreign keys using the -c option:

$ shapefile-to-sqlite my.db features.shp -c agency

This will create a agency table with id and name columns, and will create the agency column in your main table as an integer foreign key reference to that table.

The -c option can be used multiple times.

CPAD_2020a_Units is an example of a table created using the -c option.