How to use RDFDumper?

[WolfgangFahl]

Since I didn't find any RDFDumper documentation in https://linkml.io/linkml/data/conversion.html I looked into the source code
and did some try and error. The conversion asks for a JSON-LD context ... but doesn't explain how to get it.
Where would i find a working example or tutorial?

class RDFDumper(Dumper):
    def as_rdf_graph(self, element: YAMLRoot, contexts: CONTEXTS_PARAM_TYPE, namespaces: CONTEXT_TYPE = None) -> Graph:
        """
        Convert element into an RDF graph guided by the context(s) in contexts
        :param element: element to represent in RDF
        :param contexts: JSON-LD context(s) in the form of:
            * file name
            * URL
            * JSON String
            * dict
            * JSON Object
            * A list containing elements of any type named above
        :param namespaces: A file name, URL, JSON String, dict or JSON object that includes the set of namespaces to
        be bound to the return graph.  If absent, contexts get used
        :return: rdflib Graph containing element
        """

[WolfgangFahl]

gen-jsonld-context personinfo.yaml > personinfo.context.jsonld? as described in https://linkml.io/linkml/generators/jsonld-context.html?

[WolfgangFahl]

I am trying the tests code below with the given data and schema. I am using a bash script to generate the code and json ld context.
The resulting rdf graph has only one triple. What needs to be done to get proper triples for the input?

The code may be found in https://github.com/WolfgangFahl/dcm/tree/main/dcm/linkml for
WolfgangFahl/dcm#32

#!/bin/bash
# WF 2024-01-20
gen-python dcm_schema.yaml > dcm_model.py
gen-jsonld-context dcm_schema.yaml > dcm.context.jsonld

test_rdf.py

'''
Created on  2024-01-20

@author: wf
'''
import os
import json
from ngwidgets.basetest import Basetest
#from dcm.dcm_core import Learner
from dcm.linkml.dcm_model import Learner 
from linkml_runtime.loaders.json_loader import JSONLoader
from linkml_runtime.dumpers.rdf_dumper import RDFDumper
from rdflib import Graph

class TestTriplify(Basetest):
    """
    test triplifying the dcm core classes
    """
    def setUp(self, debug=False, profile=True):
        Basetest.setUp(self, debug=debug, profile=profile)
        # Path to the JSON file
        scriptdir=os.path.dirname(__file__)
        topdir=os.path.dirname(scriptdir)
        self.json_file_path = os.path.join(topdir, 'dcm_examples/arch_student_123.json')
        self.linkml_map_path = os.path.join(topdir, "dcm/linkml/dcm_schema.yaml")
        self.json_ld_context= os.path.join(topdir, "dcm/linkml/dcm.context.jsonld")
        
    def getLearner(self) -> Learner:
        # Read the JSON file as a dict
        with open(self.json_file_path, 'r') as file:
            json_data = json.load(file)

        # Load JSON data into a Learner instance
        json_loader = JSONLoader()
        json_data["@type"]="Learner"
        learner = json_loader.load(json_data, Learner)

        return learner
    
    def testLearner(self):
        """
        test the learner example
        """
        learner=self.getLearner()
        self.assertIsInstance(learner,Learner)
        pass
     
        # Serialize Learner instance to RDF
        rdf_dumper=RDFDumper()
        
        g=rdf_dumper.as_rdf_graph(learner,self.json_ld_context)

        for subj, pred, obj in g:
            print(f"Subject: {subj}, Predicate: {pred}, Object: {obj}")

        # Your assertions to validate the RDF triples
        # For example, you could assert the number of triples or specific content
        assert len(g) > 0  # Example assertion: there should be at least one triple

arch_student_123.json

{
  "learner_id": "arch_student_123",
  "achievements": [{
      "path": "architecture/DandP/ArchDesign",
      "level": 2,
      "score": 75.0,
      "date_assessed_iso": "2023-06-15"
    },
    {
      "path": "architecture/DandP/UrbanPlanning",
      "level": 1,
      "score": 60.0,
      "date_assessed_iso": "2023-06-12"
    },
    {
      "path": "architecture/DandP/BuildCodes",
      "level": 1,
      "score": 50.0,
      "date_assessed_iso": "2023-06-10"
    },
    {
      "path": "architecture/DandP/SustainDesign",
      "level": 2,
      "score": 80.0,
      "date_assessed_iso": "2023-06-18"
    },
    {
      "path": "architecture/TandC/StructEng",
      "level": 1,
      "score": 65.0,
      "date_assessed_iso": "2023-06-11"
    },
    {
      "path": "architecture/TandC/BuildTech",
      "level": 2,
      "score": 70.0,
      "date_assessed_iso": "2023-06-14"
    },
    {
      "path": "architecture/PMandA/ProjMan",
      "level": 1,
      "score": 55.0,
      "date_assessed_iso": "2023-06-09"
    },
    {
      "path": "architecture/PMandA/CostEst",
      "level": 1,
      "score": 50.0,
      "date_assessed_iso": "2023-06-09"
    },
    {
      "path": "architecture/PCandC/InterpSkills",
      "level": 2,
      "score": 85.0,
      "date_assessed_iso": "2023-06-20"
    },
    {
      "path": "architecture/PCandC/TeamCollab",
      "level": 1,
      "score": 70.0,
      "date_assessed_iso": "2023-06-17"
    }
  ]
}

dcm_schema.yaml

# Dynamic Competence Map LinkML schema
# WF 2024-01-20
#
# to install LinkML:
# pip install linkml
# 
# to generate python code:
# gen-python dcm_schema.yaml > dcm_model.py

id: https://dcm.org/learner-schema
name: learner-schema
description: Schema for representing learners and their achievements.
prefixes:
  linkml: https://w3id.org/linkml/
  dcm: https://dcm.org/learner-schema/

imports:
  - linkml:types

default_range: string
default_prefix: dcm

classes:
  Learner:
    description: An individual learner with a unique identifier and a list of achievements.
    slots:
      - learner_id
      - achievements

  Achievement:
    description: A record of an achievement attained by a learner.
    slots:
      - path
      - level
      - score
      - date_assessed_iso

slots:
  learner_id:
    description: Unique identifier for the learner.
    range: string

  achievements:
    description: A list of achievements attained by the learner.
    range: Achievement
    multivalued: true

  path:
    description: The path representing the specific area of achievement.
    range: string

  level:
    description: The level of achievement.
    range: integer

  score:
    description: The score attained in the achievement.
    range: float

  date_assessed_iso:
    description: The ISO format date when the achievement was assessed.
    range: string