kgrid-python-runtime 0.0.12

A runtime for python-based Knowledge Objects

kgrid-python-runtime

KGrid runtime for Knowledge Objects in python

Getting started:

• Install Python 3.8 or higher

• Install pip

• Run python -m pip install kgrid-python-runtime to download the latest package

• Create a directory called pyshelf in the directory the runtime will be running from.

• To start the server run python -m kgrid_python_runtime

• If this runtime will not be running locally, you must specify the address with KGRID_PYTHON_ENV_URL. This will be the address given to the Kgrid Activator upon activation.

• The runtime starts on port 5000, but can be specified with KGRID_PYTHON_ENV_PORT

• By default, the python runtime points to a Kgrid activator at url: http://localhost:8080.

  This can be customized by setting the environment variable: KGRID_PROXY_ADAPTER_URL

• By default, the python runtime will tell the Kgrid Activator that it is started at http://localhost:5000.

  If you're starting the runtime at a different address, that url must be specified by setting the environment variable: KGRID_PYTHON_ENV_URL

• The KGRID_PYTHON_CACHE_STRATEGY can take three values: never, always, or use_checksum

  • never or if no value is set means that existing objects will be overwritten whenever objects are re-downloaded from the activator.
  • always means that existing objects stored in the python runtime will never be re-downloaded from the activator and the local pyshelf and context.json files must be deleted and the runtime restarted for the objects to be replaced.
  • use_checksum means that objects will look for a checksum in the deployment descriptor sent over during activation and only re-download the object if that checksum has changed.

To run the tests:

python -m unittest discover -s tests

##Creating a python Knowledge-Object: Just like other knowledge objects, python objects have 4 basic parts: service.yaml, deployment.yaml, metadata.txt, and a payload that can be any number of python files.

The packaging spec for knowledge objects can be found here.

If your python package requires other python packages, simply specify them in a file called requirements.txt at the root of your object thusly:

package-name=0.1.5
other-package-name=1.3.5
third-package-name=1.5.4

That's it! as long as the payload is written in valid python, and the object is built to the spec, you're ready to go. An example python object can be found in the example collection

Important Notes

• Editing the cache directly from the runtime's shelf will not propagate changes to the endpoints in the runtime. New KOs must come from the activator.