linkml

import os from linkml_runtime.linkml_model.meta import SchemaDefinition from linkml.generators.pythongen import PythonGenerator from linkml_runtime.loaders import YAMLLoader from linkml_runtime.utils.datautils import dump_yaml # Define a simple LinkML schema in YAML string schema_content = """ id: http://example.org/my_schema name: my_schema description: A simple LinkML schema example prefixes: ex: http://example.org/my_schema/ default_prefix: ex classes: Person: slots: - id - name - age slots: id: identifier: true range: string name: range: string age: range: integer minimum_value: 0 """ # 1. Load the schema definition loader = YAMLLoader() schema = loader.loads(schema_content, target_class=SchemaDefinition) print(f"Successfully loaded schema: {schema.name}") # 2. Generate Python dataclasses from the schema gen = PythonGenerator(schema=schema) python_code = gen.serialize() # For quickstart, execute generated code in current namespace # In a real application, you'd write this to a file and import it. namespace = {} exec(python_code, namespace) # Get the generated 'Person' class Person = namespace['Person'] # 3. Create an instance of the generated class p = Person(id="P001", name="Alice Smith", age=30) print(f"Created person instance: {p.name}") # 4. Dump the instance to YAML yaml_output = dump_yaml(p) print("\n--- Generated YAML output ---") print(yaml_output)