Python gRPC Geometry Client

Why wrap shapely? We wanted three different abilities. Protobuf support, a required spatial reference and spatial reference aware geometry operations.

Install

Linux or Max

pip install epl.geometry

Windows

• Find out your whether you are using Windows 32-bit or 64-bit. Go to Settings => System => About => System Type .
• Find out your python version. Open Command prompt, enter python --version and remember the first two numbers. For example my version is Python 3.7.3 so I should remember the number 37:

pip install wheel

• Go here and download the wheel corresponding to items 1–2. For example, I have 64-bit OS and Python 3.7.3 so I need to download file Shapely-1.6.4.post2-cp37-cp37m-win_amd64.whl .

pip install <path-to-Downloads>\<filename_from_item_4> .

For example:

pip install C:\Users\Dalya\Downloads\Shapely-1.6.4.post2-cp37-cp37m-win_amd64.whl .

Protobuf

We wanted to import, export and operate on protobuf geometries and envelopes. Our microservices communicate using protobufs, so it made sense for us to have a helper library that allowed us to work with the geometries on our client and quickly construct protobufs for messaging.

Spatial Reference / ProjectionData

We never want a geometry separate from it's spatial reference details. We could have solved this by working exclusively with the geojson idea of always Wgs84, but we've found time and again that projected geometries exist and must be worked with. So instead of letting geometries float around without their coordinate system information we decided to tie it to the geometry, much like ESRI does with ArcObjects.

Geometry Service and SpatialReference

We wanted easy projections and operators that returned results according to their spatial reference tolerance (geodetic buffer, area, and topo relationships). Most of the old shapely operators behave the same as they did before (with exception of project and generalize), but now they use a remote geometry service that requires spatial reference information (defined in the ProjectionData object). We've kept the native shapely topo operators and changed their names to use the s_ prefix.

Changed Behavior

Many things default to a "geodetic" method if possible, you can override that with a boolean in the method calls. There are a few differences between how shapely behaves and how this wrapper functions.

• project now means to project a geometry from one spatial reference to another
• simplify fixes a broken geometry. To remove vertices from a geometry use s_simplify or generalize
• area is no longer a property. it's a method and it defaults to geodetic (internally it uses geodetic_area). the default result unit is meters squared. to force non-geodetic use geodetic=False
• carto_bounds property is used for the bounds order cartopy prefers
• carto_geom returns a shapely geometry (as does shapely_dump). Cartopy doesn't want wrapped shapely geometries, it wants the real thing.
• buffer defaults to geodetic (like area). The distance you specify is in meters. You can override with geodetic=False
• proj field on geometry returns a ProjectionData protobuf object
• initializing geometry requires a spatial reference, proj, epsg or proj4 definition

Requirements

This requires the gRPC geometry service. You can run this example from docker.

docker run -it -p 8980:8980 geogrpc/geometry-chain:latest

The GEOMETRY_SERVICE_HOST must also be set to a service. It defaults to localhost:8980.

Install Python gRPC Geometry Client

install using pip (depends on shapely, epl.protobuf and grpc)

pip install epl.geometry

install for development

pip install -r requirements.txt
pip install -r requirements-test.txt

run tests

docker run -d -p 8980:8980 geogrpc/geometry-chain:latest
pytest ./test