Correctly handle container classes, use dicts instead of lists to be able to index by name. overriding __getitem__ and __getattr__ later

nwb_linkml/src/nwb_linkml/adapters/classes.py

@@ -192,13 +192,15 @@ class ClassAdapter(Adapter):
                 required=True,
                 ifabsent=f'string({self.cls.name})',
                 equals_string=self.cls.name,
-                range='string'
+                range='string',
+                identifier=True
             )
         else:
             name_slot = SlotDefinition(
                 name='name',
                 required=True,
-                range='string'
+                range='string',
+                identifier=True
             )
         return name_slot
 

nwb_linkml/src/nwb_linkml/adapters/group.py

@@ -18,8 +18,8 @@ class GroupAdapter(ClassAdapter):
     def build(self) -> BuildResult:
         # Handle container groups with only * quantity unnamed groups
         if len(self.cls.groups) > 0 and \
-                all([self._check_if_container(g) for g in self.cls.groups]) and \
+                all([self._check_if_container(g) for g in self.cls.groups]): # and \
-                self.parent is not None:
+                # self.parent is not None:
             return self.handle_container_group(self.cls)
 
         # handle if we are a terminal container group without making a new class
@@ -58,22 +58,38 @@ class GroupAdapter(ClassAdapter):
 
         """
 
+
         # don't build subgroups as their own classes, just make a slot
         # that can contain them
-        if not self.cls.name:
+        if self.cls.name:
-            name = 'children'
-        else:
             name = cls.name
+        # elif len(cls.groups) == 1:
+        #     name = camel_to_snake(cls.groups[0].neurodata_type_inc)
+        else:
+            name = 'children'
+
+        slot = SlotDefinition(
+                    name=name,
+                    multivalued=True,
+                    any_of=[{'range': subcls.neurodata_type_inc} for subcls in cls.groups],
+                    inlined=True,
+                    inlined_as_list=False
+                )
+
+        if self.parent is not None:
+            # if we  have a parent,
+            # just return the slot itself without the class
+            slot.description = cls.doc
+            return BuildResult(
+                slots=[slot]
+            )
+        else:
+            # We are a top-level container class like ProcessingModule
+            base = self.build_base()
+            # remove all the attributes and replace with child slot
+            base.classes[0].attributes = [slot]
+            return base
 
-        res = BuildResult(
-            slots = [SlotDefinition(
-                name=name,
-                multivalued=True,
-                description=cls.doc,
-                any_of=[{'range': subcls.neurodata_type_inc} for subcls in cls.groups]
-            )]
-        )
-        return res
 
     def handle_container_slot(self, cls:Group) -> BuildResult:
         """

nwb_linkml/src/nwb_linkml/generators/pydantic.py

@@ -67,7 +67,7 @@ def default_template(pydantic_ver: str = "1", extra_classes:Optional[List[Type[B
 from __future__ import annotations
 from datetime import datetime, date
 from enum import Enum
-from typing import List, Dict, Optional, Any, Union
+from typing import List, Dict, Optional, Any, Union, ClassVar
 from pydantic import BaseModel as BaseModel, Field
 from nptyping import Shape, Float, Float32, Double, Float64, LongLong, Int64, Int, Int32, Int16, Short, Int8, UInt, UInt32, UInt16, UInt8, UInt64, Number, String, Unicode, Unicode, Unicode, String, Bool, Datetime64
 from nwb_linkml.types import NDArray

nwb_linkml/src/nwb_linkml/lang_elements.py

@@ -57,6 +57,8 @@ AnyType = ClassDefinition(
     description="""Needed because some classes in hdmf-common are datasets without dtype"""
 )
 
+
+
 NwbLangSchema = SchemaDefinition(
     name="nwb.language",
     id='nwb.language',

nwb_linkml/src/nwb_linkml/maps/hdf5.py

@@ -6,7 +6,7 @@ so we will make our own mapping class here and re-evaluate whether they should b
 """
 from abc import ABC, abstractmethod
 from pathlib import Path
-from typing import Literal, List, Dict, Optional
+from typing import Literal, List, Dict, Optional, Type
 
 import h5py
 from enum import StrEnum
@@ -14,7 +14,7 @@ from enum import StrEnum
 from pydantic import BaseModel, Field, ConfigDict
 
 from nwb_linkml.providers.schema import SchemaProvider
-from nwb_linkml.maps.hdmf import dynamictable_to_df
+from nwb_linkml.maps.hdmf import dynamictable_to_model
 from nwb_linkml.types.hdf5 import HDF5_Path
 
 
@@ -71,6 +71,10 @@ class H5ReadResult(BaseModel):
     If completed, built result. A dict that can be instantiated into the model.
     If completed is True and result is None, then remove this object
     """
+    model: Optional[Type[BaseModel]] = None
+    """
+    The model that this item should be cast into
+    """
     completes: List[str] = Field(default_factory=list)
     """
     If this result completes any other fields, we remove them from the build queue
@@ -181,7 +185,7 @@ class ResolveDynamicTable(HDF5Map):
             else:
                 base_model = None
 
-            model = dynamictable_to_df(obj, base=base_model)
+            model = dynamictable_to_model(obj, base=base_model)
 
             completes = ['/'.join([src.path, child]) for child in obj.keys()]
 
@@ -227,9 +231,12 @@ class ResolveModelGroup(HDF5Map):
             source=src,
             completed=True,
             result = res,
+            model = model,
             namespace=src.namespace,
             neurodata_type=src.neurodata_type
         )
+
+
 #
 # class ResolveModelDataset(HDF5Map):
 #     phase = ReadPhases.read

nwb_linkml/src/nwb_linkml/maps/hdmf.py

@@ -59,6 +59,9 @@ def model_from_dynamictable(group:h5py.Group, base:Optional[BaseModel] = None) -
 
         #nptype = nptyping.typing_.name_per_dtype[group[col].dtype.type]
         nptype = group[col].dtype.type
+        if nptype == np.void:
+            warnings.warn(f"Cant handle numpy void type for column {col} in {group.name}")
+            continue
         type_ = Optional[NDArray[Any, nptype]]
 
 

nwb_linkml/tests/test_io/test_io_hdf5.py

@@ -10,7 +10,7 @@ from ..fixtures import tmp_output_dir, set_config_vars
 from nwb_linkml.io.hdf5 import HDF5IO
 from nwb_linkml.io.hdf5 import truncate_file
 
-@pytest.mark.skip()
+# @pytest.mark.skip()
 def test_hdf_read():
     NWBFILE = Path('/Users/jonny/Dropbox/lab/p2p_ld/data/nwb/sub-738651046_ses-760693773.nwb')
     if not NWBFILE.exists():