Kuksa Quickstart
The quickest possible way to get Kuksa up and running
Note: The examples in this document do not use TLS or access control. They use the latest released version and use default settings as far as possible. More details on how you can configure the components is available in the GitHub Repositories!
Starting broker
First we want to run latest released version of Kuksa Databroker
docker run -it --rm --net=host ghcr.io/eclipse-kuksa/kuksa-databroker:latest --insecure
Reading and Writing VSS data via CLI
You can interact with the VSS datapoints using the cli clients. The first option is databroker-cli.
This is, how you start it:
docker run -it --rm --net=host ghcr.io/eclipse-kuksa/kuksa-databroker-cli:latest
Here is how you can use it:
kuksa.val.v1 > get Vehicle.Speed
[get] OK
Vehicle.Speed: NotAvailable
kuksa.val.v1 > publish Vehicle.Speed 200
[publish] OK
kuksa.val.v1 > get Vehicle.Speed
[get] OK
Vehicle.Speed: 200.00 km/h
kuksa.val.v1 > quit
Bye bye!
An alternative is the kuksa-client CLI (based on our Python client library).
Here is how you start it:
docker run -it --rm --net=host ghcr.io/eclipse-kuksa/kuksa-python-sdk/kuksa-client:latest
Here is how you can use it:
Test Client> getValue Vehicle.Speed
{
"path": "Vehicle.Speed"
}
Test Client> setValue Vehicle.Speed 200
OK
Test Client> getValue Vehicle.Speed
{
"path": "Vehicle.Speed",
"value": {
"value": 200.0,
"timestamp": "2024-11-13T14:29:37.156154+00:00"
}
}
Test Client> quit
2024-11-13 14:29:50,087 INFO kuksa_client.cli_backend.grpc: gRPC channel disconnected.
It is also possible to install the kuksa-client using PyPI
Reading and Writing VSS data with code
To realize your ideas with Kuksa you need to write programs that interact with its API. The easiest way to achieve this is using our Python library.
Generating data
Create a file speed_provider.py
with the following content
from kuksa_client.grpc import VSSClient
from kuksa_client.grpc import Datapoint
import time
with VSSClient('127.0.0.1', 55555) as client:
for speed in range(0,100):
client.set_current_values({
'Vehicle.Speed': Datapoint(speed),
})
print(f"Feeding Vehicle.Speed to {speed}")
time.sleep(1)
print("Finished.")
Do a pip install kuksa-client
and start with
python ./speed_provider.py
Subscribing data:
Create a file speed_subscriber.py
with the following content
from kuksa_client.grpc import VSSClient
with VSSClient('127.0.0.1', 55555) as client:
for updates in client.subscribe_current_values([
'Vehicle.Speed',
]):
speed = updates['Vehicle.Speed'].value
print(f"Received updated speed: {speed}")
Do a pip install kuksa-client
and start with
python ./speed_subscriber.py
If you now run speed_provider.py
and speed_subscriber.py
in parallel you should get updated speed values in the subscriber.
Received updated speed: 0.0
Received updated speed: 1.0
Received updated speed: 2.0
Received updated speed: 3.0
Received updated speed: 4.0
Received updated speed: 5.0
...
FAQ & Notes
Frequently anticipated questions and tips.
This is not working on OS X
Unfortunately OS X has a bug that does not allow you to use the Databroker default port 55555. To change when starting the server:
docker run -it --rm --net=host ghcr.io/eclipse-kuksa/kuksa-databroker:latest --port 55556 --insecure
Using the databroker-cli
docker run -it --rm --net=host -e KUKSA_DATA_BROKER_PORT=55556 ghcr.io/eclipse-kuksa/kuksa-databroker-cli:latest
Using kuksa-client CLI
docker run -it --rm --net=host ghcr.io/eclipse-kuksa/kuksa-python-sdk/kuksa-client:latest grpc://127.0.0.1:55556
Docker desktop: Host networking not supported
The examples above all used docker’s --net=host
option. That is quite convenient for development, as basically your containers “share” your hosts networking and there is no need for any port publishing.
However when using Docker Desktop on Mac OS or Windows, host networking is not supported.
One alternative is using a Docker distribution, that does support it even on Mac OS or Windows. Rancher Desktop is an alternative that does.
With Docker Desktop you can still forward ports, so this should work:
docker run -it --rm --publish 55556:55556 ghcr.io/eclipse-kuksa/kuksa-databroker:latest --port 55556 --insecure
From your host computer you can now reach databroker at 127.0.0.1:55556
. To connect from another container, you need to use your computers IP address (not 127.0.0.1), i.e. to use the client
docker run -it --rm -e KUKSA_DATA_BROKER_PORT=55556 -e KUKSA_DATA_BROKER_ADDR=<YOUR_IP> ghcr.io/eclipse-kuksa/kuksa-databroker-cli:latest
Recent versions of the databroker-cli also support command line arguments, so you can also write
docker run -it --rm ghcr.io/eclipse-kuksa/kuksa-databroker-cli:latest --server http://<YOUR_IP>:55556
publish/set: Why is my data not updated?
Some VSS points are “sensors”, e.g. Vehicle.Speed. You can read/get Vehicle speed, but we are not expecting to be able to influence it via VSS.
Historically components, that gather the actual vehicle speed from some sensors/busses in a vehicle and providing a VSS representation to Kuksa have been called feeders
. Hence, to update the current speed in the Rust-cli, you use
publish Vehicle.Speed 200
while in the Python-cli you use
set Vehicle.Speed 200
The other thing, that VSS provides you are “actuators” Vehicle.Body.Trunk.Rear.IsOpen
. The most important thing to remember about actuators: Every actuators is also a sensor, so everything written on top applies as well!
The second-most important thing is: For VSS actuatorss, it is expected that you might be able to influence the state of the real Vehicle by writing to them. So while being used as a sensor, you will get the current position of the Window in the example, you might also want to set the desired position.
You express this in the databroker-cli as
actuate Vehicle.Body.Trunk.Rear.IsOpen true
In kuksa-client cli you do
Test Client> setTargetValue Vehicle.Body.Trunk.Rear.IsOpen True
In the code examples above you would do
client.set_target_values({
'Vehicle.Body.Trunk.Rear.IsOpen': Datapoint(True),
})
All I see is Python, shouldn’t this be high-performance?
Our Python library makes it easy to interact with Databroker. While this is often sufficient for many applications, you are not limited by it: Databroker’s native interface is based on gRPC, a high-performance GRPC framework. gRPC enables you to generate bindings for any language. Check the gRPC website and take a look at the Databroker interface definitions.