ENH: JsonSchemaExporter accepts do_not_create parameter.

Summary

• DataModel.get_deep(name: str)
• Refactoring of json schema exporter.
• New parameter for json schema exporter.

Look at the new test function, this should explain the meaning.

Please do not delete the source branch after merging, we will probably still need it.

Focus

Does the get_deep() function look reasonable?

Test Environment

Run the unit tests, especially pytest unittests/test_json_schema_exporter.py -k options

Check List for the Author

Please, prepare your MR for a review. Be sure to write a summary and a focus and create gitlab comments for the reviewer. They should guide the reviewer through the changes, explain your changes and also point out open questions. For further good practices have a look at our review guidelines

• All automated tests pass
• Reference related issues caosdb/customers/dimr/management#65
• Up-to-date CHANGELOG.md (or not necessary)
• Up-to-date JSON schema (or not necessary)
• Appropriate user and developer documentation (or not necessary)
  • How do I use the software? Assume "stupid" users.
  • How do I develop or debug the software? Assume novice developers.
• Annotations in code (Gitlab comments)
  • Intent of new code
  • Problems with old code
  • Why this implementation?

Check List for the Reviewer

• I understand the intent of this MR
• All automated tests pass
• Up-to-date CHANGELOG.md (or not necessary)
• Appropriate user and developer documentation (or not necessary)
• The test environment setup works and the intended behavior is reproducible in the test environment
• In-code documentation and comments are up-to-date.
• Check: Are there specifications? Are they satisfied?

For further good practices have a look at our review guidelines.

src/caosadvancedtools/models/data_model.py

@@ -262,3 +262,37 @@ class DataModel(dict):
                 all_ents[prop.name] = prop
 
         return list(all_ents.values())
+
+    def get_deep(self, name: str, visited: set = None):
+        """Attempt to resolve references for the given ``name``.
+
+        This methods only uses data which is available in this datamodel, which acts kind of like a
+        cache pool.
+
+        Note that this may change this data model (subsequent "get" like calls may also return deep
+        content.)
+        """
+        entity = self.get(name)
+        if not entity:
+            return entity
+        if not visited:
+            visited = set()
+
+        # new_props = []
+        for prop in list(entity.get_properties()):  # Make a change-resistant list copy.
+            if prop.name in visited:
+                continue
+            visited.add(prop.name)
+            if prop.name in self:
+                deep_prop = self.get_deep(prop.name, visited=visited)
+                linked_prop = entity.get_property(prop)
+                if not linked_prop.datatype:
+                    if deep_prop.role == "Property":
+                        linked_prop.datatype = deep_prop.datatype
+                    elif deep_prop.role == "RecordType":
+                        linked_prop.datatype = deep_prop
+                if deep_prop.description:
+                    linked_prop.description = deep_prop.description
+            else:
+                print(f"Referenced property \"{prop.name}\" not found in data model.")
+        return entity