successfully building many versions of nwb schema.

working on hdf5 importing, come back to it when fresh, just sorta poking at it because it's so close.

nwb_linkml/src/nwb_linkml/adapters/namespaces.py

@@ -48,7 +48,7 @@ class NamespacesAdapter(Adapter):
         """
         from nwb_linkml.io import schema as schema_io
         ns_adapter = schema_io.load_namespaces(path)
-        ns_adapter = schema_io.load_namespace_schema(ns_adapter, path)
+        ns_adapter = schema_io.load_namespace_adapter(ns_adapter, path)
 
         # try and find imported schema
 
@@ -73,10 +73,19 @@ class NamespacesAdapter(Adapter):
         sch_result = BuildResult()
         for sch in self.schemas:
             if progress is not None:
-                progress.update(sch.namespace, action=sch.name)
+                try:
+                    progress.update(sch.namespace, action=sch.name)
+                except KeyError:
+                    # happens when we skip builds due to cachine
+                    pass
             sch_result += sch.build()
             if progress is not None:
-                progress.update(sch.namespace, advance=1)
+                try:
+                    progress.update(sch.namespace, advance=1)
+                except KeyError:
+                    # happens when we skip builds due to caching
+                    pass
+
 
         # recursive step
         if not skip_imports:
@@ -145,10 +154,9 @@ class NamespacesAdapter(Adapter):
                 sources = [sch.source for sch in ns.schema_]
                 if sch_name in sources or sch.path.stem in sources:
                     sch.namespace = ns.name
+                    sch.version = ns.version
                     break
 
-
-
     def find_type_source(self, name:str) -> SchemaAdapter:
         """
         Given some neurodata_type_inc, find the schema that it's defined in.

nwb_linkml/src/nwb_linkml/adapters/schema.py

@@ -33,6 +33,10 @@ class SchemaAdapter(Adapter):
     namespace: Optional[str] = Field(
         None,
         description="""String of containing namespace. Populated by NamespacesAdapter""")
+    version: Optional[str] = Field(
+        None,
+        description="Version of schema, populated by NamespacesAdapter since individual schema files dont know their version in NWB Schema Lang"
+    )
     split: bool = Field(
         False,
         description="Split anonymous subclasses into a separate schema file"
@@ -67,7 +71,6 @@ class SchemaAdapter(Adapter):
         - `id` (but need to have a placeholder to instantiate)
         - `version`
 
-
         """
         res = BuildResult()
         for dset in self.datasets:
@@ -90,7 +93,8 @@ class SchemaAdapter(Adapter):
                 imports = [i.name if isinstance(i, SchemaAdapter) else i for i in self.imports ],
                 classes=res.classes,
                 slots=res.slots,
-                types=res.types
+                types=res.types,
+                version=self.version
             )
             # every schema needs the language elements
             sch.imports.append('.'.join([self.namespace, 'nwb.language']))

nwb_linkml/src/nwb_linkml/generators/pydantic.py

@@ -219,10 +219,14 @@ class NWBPydanticGenerator(PydanticGenerator):
             # Don't get classes that are defined in this schema!
             if module_name == self.schema.name:
                 continue
-
-            if self.versions and module_name in self.versions:
-                version = version_module_case(self.versions[module_name])
-                local_mod_name = '....' + module_case(module_name) + '.' + version + '.' + 'namespace'
+            # pdb.set_trace()
+            schema_name = module_name.split('.')[0]
+            if self.versions and schema_name != self.schema.name.split('.')[0] and schema_name in self.versions:
+                version = version_module_case(self.versions[schema_name])
+                if self.split:
+                    local_mod_name = '...' + module_case(schema_name) + '.' + version + '.' + module_case(module_name)
+                else:
+                    local_mod_name = '...' + module_case(schema_name) + '.' + version + '.' + 'namespace'
             else:
 
                 local_mod_name = '.' + module_case(module_name)
@@ -372,7 +376,7 @@ class NWBPydanticGenerator(PydanticGenerator):
         try:
             dtype = flat_to_npytyping[list(attrs.values())[0].range]
         except KeyError as e:
-            warnings.warn(e)
+            warnings.warn(str(e))
             range = list(attrs.values())[0].range
             return f'List[{range}] | {range}'
         suffix = "]"

nwb_linkml/src/nwb_linkml/io/hdf5.py

@@ -1,11 +1,14 @@
 """
 This is a sandbox file that should be split out to its own pydantic-hdf5 package, but just experimenting here to get our bearings
 """
+import pdb
+import typing
 from typing import Optional, List, Dict, overload, Literal, Type, Any
 from pathlib import Path
 from types import ModuleType
 from typing import TypeVar, TYPE_CHECKING
 from abc import abstractmethod
+import json
 
 import h5py
 from pydantic import BaseModel
@@ -15,13 +18,14 @@ from nwb_linkml.translate import generate_from_nwbfile
 #from nwb_linkml.models.core_nwb_file import NWBFile
 if TYPE_CHECKING:
     from nwb_linkml.models.core_nwb_file import NWBFile
+from nwb_linkml.providers.schema import SchemaProvider
 
 @dataclass
 class HDF5Element():
 
     cls: h5py.Dataset | h5py.Group
-    models: Dict[str, ModuleType]
     parent: Type[BaseModel]
+    model: Optional[Any] = None
 
     @abstractmethod
     def read(self) -> BaseModel | List[BaseModel]:
@@ -40,34 +44,69 @@ class HDF5Element():
         """Just the terminal group name"""
         return self.cls.name.split('/')[-1]
 
-    def get_model(self) -> Type[BaseModel | dict]:
+    def get_model(self) -> Type[BaseModel | dict | list]:
         """
         Find our model
         - If we have a neurodata_type in our attrs, use that
         - Otherwise, use our parent to resolve the type
         """
+        if self.model is not None:
+            return self.model
+
         if 'neurodata_type' in self.cls.attrs.keys():
-            return get_model(self.cls.attrs, self.models)
+            return get_model(self.cls)
         else:
-            parent_model  = get_model(self.cls.parent.attrs, self.models)
+            parent_model  = get_model(self.cls.parent)
             field = parent_model.model_fields.get(self.name)
             if issubclass(type(field.annotation), BaseModel):
                 return field.annotation
+            else:
+                try:
+                    if issubclass(field.annotation, BaseModel):
+                        return field.annotation
+                except TypeError:
+                    pass
+            # remove any optionals
+            annotation = field.annotation
+            annotation = unwrap_optional(annotation)
+
+            if typing.get_origin(annotation) is list:
+                return list
+
             else:
                 return dict
                 #raise NotImplementedError('Need to unpack at least listlike annotations')
 
+def unwrap_optional(annotation):
+    if typing.get_origin(annotation) == typing.Union:
+        args = typing.get_args(annotation)
+
+        if len(args) == 2 and args[1].__name__ == 'NoneType':
+            annotation = args[0]
+    return annotation
+
+def take_outer_type(annotation):
+    if typing.get_origin(annotation) is list:
+        return list
+    return annotation
 @dataclass
 class H5Dataset(HDF5Element):
     cls: h5py.Dataset
 
     def read(self) -> Any:
+        model = self.get_model()
+
+        # TODO: Handle references
+        if self.cls.dtype == h5py.ref_dtype:
+            return None
+
         if self.cls.shape == ():
             return self.cls[()]
-        elif len(self.cls.shape) == 1:
+        elif model is list:
             return self.cls[:].tolist()
         else:
-            raise NotImplementedError('oop')
+            return {'array':self.cls[:], 'name': self.cls.name.split('/')[-1]}
+            #raise NotImplementedError('oop')
 
 @dataclass
 class H5Group(HDF5Element):
@@ -82,14 +121,25 @@ class H5Group(HDF5Element):
         }
         data.update(model_attrs)
 
+
         for k, v in self.cls.items():
+            child_model = None
+            if isinstance(model, type) and issubclass(model, BaseModel):
+                child_field = model.model_fields.get(k, None)
+                if child_field is not None:
+                    child_model = unwrap_optional(child_field.annotation)
+                    child_model = take_outer_type(child_model)
             if isinstance(v, h5py.Group):
-                data[k] = H5Group(cls=v, models=self.models, parent=model).read()
+                data[k] = H5Group(cls=v, parent=model, model=child_model).read()
             elif isinstance(v, h5py.Dataset):
-                data[k] = H5Dataset(cls=v, models=self.models, parent=model).read()
+                data[k] = H5Dataset(cls=v, parent=model, model=child_model).read()
 
 
-        return model(**data)
+        if issubclass(model, BaseModel):
+            data['name'] = self.cls.name.split('/')[-1]
+            return model(**data)
+        elif model is list:
+            return list(data.values())
 
 
 class HDF5IO():
@@ -112,20 +162,25 @@ class HDF5IO():
 
     def read(self, path:Optional[str] = None):
         h5f = h5py.File(str(self.path))
+        schema = read_specs(h5f.get('specifications'))
+        # build schema so we have them cached
+
+        provider = SchemaProvider()
+        res = provider.build_from_dicts(schema)
 
         if path:
             src = h5f.get(path)
-            parent = get_model(src.attrs, self.modules)
+            parent = get_model(src)
         else:
             src = h5f
-            parent = getattr(self.modules['core'], 'NWBFile')
+            parent = provider.get_class('core', 'NWBFile')
 
         data = {}
         for k, v in src.items():
             if isinstance(v, h5py.Group):
-                data[k] = H5Group(cls=v, models=self.modules, parent=parent).read()
+                data[k] = H5Group(cls=v, parent=parent).read()
             elif isinstance(v, h5py.Dataset):
-                data[k] = H5Dataset(cls=v, models=self.modules, parent=parent).read()
+                data[k] = H5Dataset(cls=v, parent=parent).read()
 
         if path is None:
             return parent(**data)
@@ -168,13 +223,36 @@ class HDF5IO():
         if len(data.shape) == 1:
             return list(data[:])
 
-def get_model(attrs: h5py.AttributeManager, models: Dict[str, ModuleType]) -> Type[BaseModel]:
+
+
+def read_specs(group: h5py.Group) -> dict:
+    spec_dict = {}
+    def _read_spec(name, node):
+
+        if isinstance(node, h5py.Dataset):
+            # make containing dict if they dont exist
+            pieces = node.name.split('/')
+            if pieces[-3] not in spec_dict.keys():
+                spec_dict[pieces[-3]] = {}
+
+            spec = json.loads(node[()])
+            spec_dict[pieces[-3]][pieces[-1]] = spec
+
+    group.visititems(_read_spec)
+    return spec_dict
+
+
+def get_model(cls: h5py.Group | h5py.Dataset) -> Type[BaseModel]:
+    attrs = cls.attrs
     ns = attrs.get('namespace')
     model_name = attrs.get('neurodata_type')
-    return getattr(models[ns], model_name)
 
-# if __name__ == "__main__":
-#     NWBFILE = Path('/Users/jonny/Dropbox/lab/p2p_ld/data/nwb/sub-738651046_ses-760693773.nwb')
-#     h5f = HDF5IO(NWBFILE)
+    try:
+        return SchemaProvider().get_class(ns, model_name)
+    except:
+        # try to get parent class
+        mod = get_model(cls.parent)
+        return mod.model_fields[cls.name.split('/')[-1]].annotation
+
 
 

nwb_linkml/src/nwb_linkml/io/schema.py

@@ -25,7 +25,8 @@ def load_yaml(path:Path) -> dict:
         ns_dict = amap.apply(ns_dict)
     return ns_dict
 
-def load_namespaces(path:Path|NamespaceRepo) -> Namespaces:
+def _load_namespaces(path:Path|NamespaceRepo) -> Namespaces:
+    """Loads the NWB SCHEMA LANGUAGE namespaces (not the namespacesadapter)"""
     if isinstance(path, NamespaceRepo):
         path = path.provide_from_git()
 
@@ -37,6 +38,10 @@ def load_namespaces(path:Path|NamespaceRepo) -> Namespaces:
 def load_schema_file(path:Path, yaml:Optional[dict] = None) -> SchemaAdapter:
     if yaml is not None:
         source = yaml
+        # apply maps
+        maps = [m for m in Map.instances if m.phase == PHASES.postload]
+        for amap in maps:
+            source = amap.apply(source)
     else:
         source = load_yaml(path)
 
@@ -64,25 +69,39 @@ def load_schema_file(path:Path, yaml:Optional[dict] = None) -> SchemaAdapter:
     )
     return schema
 
-def load_namespace_schema(namespace: Namespaces, path:Path=Path('..')) -> NamespacesAdapter:
+def load_namespace_adapter(namespace: Path | NamespaceRepo | Namespaces, path:Optional[Path]=None) -> NamespacesAdapter:
     """
     Load all schema referenced by a namespace file
 
     Args:
-        namespace (:class:`.Namespace`):
+        namespace (:class:`:class:`.Namespace`):
         path (:class:`pathlib.Path`): Location of the namespace file - all relative paths are interpreted relative to this
 
     Returns:
         :class:`.NamespacesAdapter`
     """
+    if path is None:
+        path = Path('..')
+
+    if isinstance(namespace, Path):
+        path = namespace
+        namespaces = _load_namespaces(path)
+    elif isinstance(namespace, NamespaceRepo):
+        path = namespace.provide_from_git()
+        namespaces = _load_namespaces(namespace)
+
+    elif isinstance(namespace, Namespaces):
+        namespaces = namespace
+    else:
+        raise ValueError(f"Namespace must be a path, namespace repo, or already loaded namespaces")
+
 
-    path = Path(path).resolve()
     if path.is_file():
         # given the namespace file itself, so find paths relative to its directory
         path = path.parent
 
     sch = []
-    for ns in namespace.namespaces:
+    for ns in namespaces.namespaces:
         for schema in ns.schema_:
             if schema.source is None:
                 # this is normal, we'll resolve later
@@ -91,7 +110,7 @@ def load_namespace_schema(namespace: Namespaces, path:Path=Path('..')) -> Namesp
             sch.append(load_schema_file(yml_file))
 
     adapter = NamespacesAdapter(
-        namespaces=namespace,
+        namespaces=namespaces,
         schemas=sch
     )
 
@@ -99,13 +118,8 @@ def load_namespace_schema(namespace: Namespaces, path:Path=Path('..')) -> Namesp
 
 def load_nwb_core() -> NamespacesAdapter:
     # First get hdmf-common:
-    hdmf_ns_file = HDMF_COMMON_REPO.provide_from_git()
-    hdmf_ns = load_namespaces(hdmf_ns_file)
-    hdmf_schema = load_namespace_schema(hdmf_ns, hdmf_ns_file)
-
-    namespace_file = NWB_CORE_REPO.provide_from_git()
-    ns = load_namespaces(namespace_file)
-    schema = load_namespace_schema(ns, namespace_file)
+    hdmf_schema = load_namespace_adapter(HDMF_COMMON_REPO)
+    schema = load_namespace_adapter(NWB_CORE_REPO)
 
     schema.imported.append(hdmf_schema)
 

nwb_linkml/src/nwb_linkml/providers/git.py

@@ -131,6 +131,7 @@ class GitRepo:
                 self._git_call('checkout', "HEAD")
         else:
             self._git_call('checkout', commit)
+        self._git_call('submodule', 'update', '--init', '--recursive')
         self._commit = commit
 
     @property
@@ -166,6 +167,7 @@ class GitRepo:
         self._git_call('fetch', '--all', '--tags')
         self._git_call('checkout', f'tags/{tag}')
         # error will be raised by _git_call if tag not found
+        self._git_call('submodule', 'update', '--init', '--recursive')
 
     @property
     def default_branch(self) -> str:

nwb_linkml/src/nwb_linkml/providers/schema.py

@@ -10,9 +10,37 @@ Relationship to other modules:
 * :mod:`.adapters` manage the conversion from NWB schema language to linkML.
 * :mod:`.generators` create models like pydantic models from the linkML schema
 * :mod:`.providers` then use ``adapters`` and ``generators`` to provide models from generated schema!
+
+Providers create a set of directories with namespaces and versions,
+so eg. for the linkML and pydantic providers:
+
+    cache_dir
+      - linkml
+        - nwb_core
+          - v0_2_0
+            - namespace.yaml
+            - nwb.core.file.yaml
+            - ...
+          - v0_2_1
+            - namespace.yaml
+            - ...
+        - my_schema
+          - v0_1_0
+            - ...
+      - pydantic
+        - nwb_core
+          - v0_2_0
+            - namespace.py
+            - ...
+          - v0_2_1
+            - namespace.py
+            - ...
+
+
 """
 import pdb
-from typing import Dict, TypedDict, List, Optional, Literal, TypeVar, Any, Dict
+import shutil
+from typing import Dict, TypedDict, List, Optional, Literal, TypeVar, Any, Dict, Type
 from types import ModuleType
 from pathlib import Path
 import os
@@ -83,6 +111,13 @@ class Provider(ABC):
         Whatever needs to be done to build this thing, if applicable
         """
 
+    @abstractmethod
+    def get(self, *args: Any) -> Any:
+        """
+        Get a cached item.
+
+        Optionally, try any build it if it's possible to do so
+        """
 
     def namespace_path(
             self,
@@ -136,12 +171,48 @@ class Provider(ABC):
 
         return version_path
 
+    @property
+    def versions(self) -> Dict[str,List[str]]:
+        """
+        Dictionary mapping a namespace to a list of built versions
+        """
+        versions = {} # type: Dict[str, List[Path]]
+
+        # first get any builtins provided by the package itself
+        # these get overwritten by
+        module_path = Path(importlib.util.find_spec('nwb_linkml').origin).parent
+        builtin_namespaces = []
+        if self.PROVIDES == 'linkml':
+            namespace_path = module_path / 'schema'
+            builtin_namespaces = list(namespace_path.iterdir())
+        elif self.PROVIDES == 'pydantic':
+            namespace_path = module_path / 'models'
+            builtin_namespaces = list(namespace_path.iterdir())
+
+        for ns_dir in builtin_namespaces + list(self.path.iterdir()):
+            if not ns_dir.is_dir():
+                continue
+            if ns_dir.name not in versions.keys():
+                versions[ns_dir.name] = []
+
+            versions[ns_dir.name].extend([v for v in ns_dir.iterdir() if v.is_dir()])
+
+        # flatten out in case we got duplicates between the builtins and cache
+        res = {
+            k: [v.name for v in sorted(set(v_paths), key=os.path.getmtime)]
+            for k, v_paths in versions.items()
+        }
+        return res
+
+
+
 
 class LinkMLSchemaBuild(TypedDict):
     """Build result from :meth:`.LinkMLProvider.build`"""
-    result: BuildResult
     version: str
     namespace: Path
+    name: str
+    result: Optional[BuildResult]
 
 
 class LinkMLProvider(Provider):
@@ -219,19 +290,35 @@ class LinkMLProvider(Provider):
                 to infer version and schema name. Post-load maps should have already
                 been applied
         """
-        ns = Namespaces(**schemas['namespace'])
-        typed_schemas = [
-            io.schema.load_schema_file(
-                path=Path(key + ".yaml"),
-                yaml=val)
-            for key, val in schemas.items()
-            if key != 'namespace'
-        ]
-        ns_adapter = adapters.NamespacesAdapter(
-            namespaces=ns,
-            schemas=typed_schemas
-        )
-        return self.build(ns_adapter, **kwargs)
+        ns_adapters = {}
+        for ns_name, ns_schemas in schemas.items():
+            ns = Namespaces(**ns_schemas['namespace'])
+            typed_schemas = [
+                io.schema.load_schema_file(
+                    path=Path(key + ".yaml"),
+                    yaml=val)
+                for key, val in ns_schemas.items()
+                if key != 'namespace'
+            ]
+            ns_adapter = adapters.NamespacesAdapter(
+                namespaces=ns,
+                schemas=typed_schemas
+            )
+            ns_adapters[ns_name] = ns_adapter
+
+        # get the correct imports
+        for ns_name, adapter in ns_adapters.items():
+            for schema_needs in adapter.needed_imports.values():
+                for needed in schema_needs:
+                    adapter.imported.append(ns_adapters[needed])
+
+        # then do the build
+        res = {}
+        for ns_name, adapter in ns_adapters.items():
+            res.update(self.build(adapter, **kwargs))
+
+        return res
+
 
 
     def build(
@@ -239,6 +326,7 @@ class LinkMLProvider(Provider):
         ns_adapter: adapters.NamespacesAdapter,
         versions: Optional[dict] = None,
         dump: bool = True,
+        force: bool = False
     ) -> Dict[str | SchemaDefinitionName, LinkMLSchemaBuild]:
         """
         Arguments:
@@ -249,8 +337,24 @@ class LinkMLProvider(Provider):
                  If none is provided, use the most recent version
                 available.
             dump (bool): If ``True`` (default), dump generated schema to YAML. otherwise just return
+            force (bool): If ``False`` (default), don't build schema that already exist. If ``True`` , clear directory and rebuild
+
+        Returns:
+            Dict[str, LinkMLSchemaBuild]. For normal builds, :attr:`.LinkMLSchemaBuild.result` will be populated with results
+            of the build. If ``force == False`` and the schema already exist, it will be ``None``
         """
 
+        if not force:
+            if all([(self.namespace_path(ns, version) / 'namespace.yaml').exists() for ns, version in ns_adapter.versions.items()]):
+                return {
+                    k: LinkMLSchemaBuild(
+                        name=k,
+                        result=None,
+                        namespace=self.namespace_path(k, v) / 'namespace.yaml',
+                        version=v
+                    ) for k,v in ns_adapter.versions.items()
+                }
+
         #self._find_imports(ns_adapter, versions, populate=True)
         if self.verbose:
             progress = AdapterProgress(ns_adapter)
@@ -265,27 +369,32 @@ class LinkMLProvider(Provider):
         build_result = {}
 
         namespace_sch = [sch for sch in built.schemas if 'namespace' in sch.annotations.keys()]
-        namespace_names = [sch.name for sch in namespace_sch]
         for ns_linkml in namespace_sch:
             version = ns_adapter.versions[ns_linkml.name]
             version_path = self.namespace_path(ns_linkml.name, version, allow_repo=False)
+            if version_path.exists() and force:
+                shutil.rmtree(str(version_path))
             version_path.mkdir(exist_ok=True, parents=True)
             ns_file = version_path / 'namespace.yaml'
-            ns_linkml = self._fix_schema_imports(ns_linkml, ns_adapter, ns_file)
-            yaml_dumper.dump(ns_linkml, ns_file)
+            # schema built as part of this namespace that aren't the namespace file
+            other_schema = [sch for sch in built.schemas if
+                            sch.name.split('.')[0] == ns_linkml.name and sch not in namespace_sch]
 
-            # write the schemas for this namespace
-            other_schema = [sch for sch in built.schemas if sch.name.split('.')[0] == ns_linkml.name and sch not in namespace_sch]
-            for sch in other_schema:
-                output_file = version_path / (sch.name + '.yaml')
-                # fix the paths for intra-schema imports
-                sch = self._fix_schema_imports(sch, ns_adapter, output_file)
+            if force or (not force and not ns_file.exists()):
+                ns_linkml = self._fix_schema_imports(ns_linkml, ns_adapter, ns_file)
+                yaml_dumper.dump(ns_linkml, ns_file)
 
-                yaml_dumper.dump(sch, output_file)
+                # write the schemas for this namespace
+                for sch in other_schema:
+                    output_file = version_path / (sch.name + '.yaml')
+                    # fix the paths for intra-schema imports
+                    sch = self._fix_schema_imports(sch, ns_adapter, output_file)
+                    yaml_dumper.dump(sch, output_file)
 
             # make return result for just this namespace
             build_result[ns_linkml.name] = LinkMLSchemaBuild(
                 namespace=ns_file,
+                name=ns_linkml.name,
                 result= BuildResult(schemas=[ns_linkml, *other_schema]),
                 version=version
             )
@@ -350,27 +459,40 @@ class PydanticProvider(Provider):
     def build(
             self,
             namespace: str | Path,
+            out_file: Optional[Path] = None,
             version: Optional[str] = None,
             versions: Optional[dict] = None,
+            split: bool = False,
             dump: bool = True,
+            force: bool = False,
             **kwargs
     ) -> str:
         """
 
+        Notes:
+            We currently infer namespace and version from the path when ``namespace`` is a Path,
+            which is a patently Bad Thing To Do. This is a temporary measure until we decide on
+            a permanent means by which we want to cache built artifacts <3. Hierarchies of folders
+            is not the target design.
+
 
         Args:
             namespace (Union[str, :class:`pathlib.Path`]): If a string, use a
                 :class:`.LinkMLProvider` to get the converted schema. If a path,
                 assume we have been given an explicit ``namespace.yaml`` from a converted
                 NWB -> LinkML schema to load from.
+            out_file (Optional[Path]): Optionally override the output file. If ``None``, generate from namespace and version
             version (Optional[str]): The version of the schema to build, if present.
-                Works similarly to ``version`` in :class:`.LinkMLProvider`
+                Works similarly to ``version`` in :class:`.LinkMLProvider`. Ignored if ``namespace`` is a Path.
             versions (Optional[dict]): An explicit mapping of namespaces and versions to use when
                 building the combined pydantic `namespace.py` file. Since NWB doesn't have an explicit
                 version dependency system between schema, there is intrinsic ambiguity between which version
                 of which schema should be used when imported from another. This mapping allows those ambiguities to be resolved.
                 See :class:`.NWBPydanticGenerator` 's ``versions`` argument for more information.
+            split (bool): If ``False`` (default), generate a single ``namespace.py`` file, otherwise generate a python file for each schema in the namespace
+                in addition to a ``namespace.py`` that imports from them
             dump (bool): If ``True`` (default), dump the model to the cache, otherwise just return the serialized string of built pydantic model
+            force (bool): If ``False`` (default), don't build the model if it already exists, if ``True`` , delete and rebuild any model
             **kwargs: Passed to :class:`.NWBPydanticGenerator`
 
         Returns:
@@ -379,13 +501,36 @@ class PydanticProvider(Provider):
 
         if isinstance(namespace, str) and not (namespace.endswith('.yaml') or namespace.endswith('.yml')):
             # we're given a name of a namespace to build
+            name = namespace
             path = LinkMLProvider(path=self.config.cache_dir).namespace_path(namespace, version) / 'namespace.yaml'
+            if version is None:
+                # Get the most recently built version
+                version = LinkMLProvider(path=self.config.cache_dir).versions[name][-1]
+            fn = path.parts[-1]
         else:
             # given a path to a namespace linkml yaml file
             path = Path(namespace)
+            # FIXME: this is extremely fragile, but get the details from the path. this is faster than reading yaml for now
+            name = path.parts[-3]
+            version = path.parts[-2]
+            fn = path.parts[-1]
+
+        version = version_module_case(version)
+
+        # this is extremely fragile, we should not be inferring version number from paths...
+        if out_file is None:
+            fn = fn.strip('.yaml')
+            fn = module_case(fn) + '.py'
+            out_file = self.path / name / version / fn
+
+        if out_file.exists() and not force:
+            with open(out_file, 'r') as ofile:
+                serialized = ofile.read()
+            return serialized
+
 
         default_kwargs = {
-            'split': False,
+            'split': split,
             'emit_metadata': True,
             'gen_slots': True,
             'pydantic_version': '2'
@@ -399,10 +544,16 @@ class PydanticProvider(Provider):
         )
         serialized = generator.serialize()
         if dump:
-            out_file = self.path / path.parts[-3] / path.parts[-2] / 'namespace.py'
             out_file.parent.mkdir(parents=True,exist_ok=True)
             with open(out_file, 'w') as ofile:
                 ofile.write(serialized)
+            with open(out_file.parent / '__init__.py', 'w') as initfile:
+                initfile.write(' ')
+            # make parent file, being a bit more careful because it could be for another module
+            parent_init = out_file.parent.parent / '__init__.py'
+            if not parent_init.exists():
+                with open(parent_init, 'w') as initfile:
+                    initfile.write(' ')
 
         return serialized
 
@@ -487,7 +638,7 @@ class PydanticProvider(Provider):
         module = self.import_module(namespace, version)
         return module
 
-    def get_class(self, namespace: str, class_: str, version: Optional[str] = None) -> BaseModel:
+    def get_class(self, namespace: str, class_: str, version: Optional[str] = None) -> Type[BaseModel]:
         """
         Get a class from a given namespace and version!
 
@@ -507,10 +658,10 @@ class PydanticProvider(Provider):
 
 
 
-class SchemaProvider:
+class SchemaProvider(Provider):
     """
     Class to manage building and caching linkml and pydantic models generated
-    from nwb schema language
+    from nwb schema language. Combines :class:`.LinkMLProvider` and :class:`.PydanticProvider`
 
     Behaves like a singleton without needing to be one - since we're working off
     caches on disk that are indexed by hash in most "normal" conditions you should
@@ -519,52 +670,81 @@ class SchemaProvider:
 
     Store each generated schema in a directory structure indexed by
     schema namespace name and version
-
-    eg:
-
-        cache_dir
-          - linkml
-            - nwb_core
-              - v0_2_0
-                - namespace.yaml
-                - nwb.core.file.yaml
-                - ...
-              - v0_2_1
-                - namespace.yaml
-                - ...
-            - my_schema
-              - v0_1_0
-                - ...
-          - pydantic
-            - nwb_core
-              - v0_2_0
-                - namespace.py
-                - ...
-              - v0_2_1
-                - namespace.py
-                - ...
-
+    """
+    build_from_yaml = LinkMLProvider.build_from_yaml
+    """
+    Alias for :meth:`.LinkMLProvider.build_from_yaml` that also builds a pydantic model
+    """
+    build_from_dicts = LinkMLProvider.build_from_dicts
+    """
+    Alias for :meth:`.LinkMLProvider.build_from_dicts` that also builds a pydantic model
     """
 
-    def __init__(self,
-                 path: Optional[Path] = None,
-                 verbose: bool = True):
+    @property
+    def path(self) -> Path:
+        return self.config.cache_dir
+
+
+    def build(
+        self,
+        ns_adapter: adapters.NamespacesAdapter,
+        verbose: bool = True,
+        linkml_kwargs: Optional[dict] = None,
+        pydantic_kwargs: Optional[dict] = None,
+        **kwargs
+    ) -> Dict[str, str]:
         """
-        Arguments:
-            path (bool): If provided, output to an explicit base directory.
-                Otherwise use that provided in ``NWB_LINKML_CACHE_DIR``
-            verbose (bool): If ``True`` (default), show progress bars and other messages
-                useful for interactive use
+        Build a namespace, storing its linkML and pydantic models.
+
+        Args:
+            ns_adapter:
+            verbose (bool): If ``True`` (default), show progress bars
+            linkml_kwargs (Optional[dict]): Dictionary of kwargs optionally passed to :meth:`.LinkMLProvider.build`
+            pydantic_kwargs (Optional[dict]): Dictionary of kwargs optionally passed to :meth:`.PydanticProvider.build`
+            **kwargs: Common options added to both ``linkml_kwargs`` and ``pydantic_kwargs``
+
+        Returns:
+            Dict[str,str] mapping namespaces to built pydantic sources
         """
-        if path is not None:
-            config = Config(cache_dir=path)
-        else:
-            config = Config()
-        self.cache_dir = config.cache_dir
-        self.pydantic_dir = config.pydantic_dir
-        self.linkml_dir = config.linkml_dir
+        if linkml_kwargs is None:
+            linkml_kwargs = {}
+        if pydantic_kwargs is None:
+            pydantic_kwargs = {}
+        linkml_kwargs.update(kwargs)
+        pydantic_kwargs.update(kwargs)
+
+        linkml_provider = LinkMLProvider(path=self.path, verbose=verbose)
+        pydantic_provider = PydanticProvider(path=self.path, verbose=verbose)
+
+        linkml_res = linkml_provider.build(ns_adapter=ns_adapter, **linkml_kwargs)
+        results = {}
+        for ns, ns_result in linkml_res.items():
+            results[ns] = pydantic_provider.build(ns_result['namespace'], **pydantic_kwargs)
+        return results
+
+    def get(self, namespace: str, version: Optional[str] = None) -> ModuleType:
+        """
+        Get a built pydantic model for a given namespace and version.
+
+        Wrapper around :meth:`.PydanticProvider.get`
+        """
+        return PydanticProvider(path=self.path).get(namespace, version)
+
+    def get_class(self, namespace: str, class_: str, version: Optional[str] = None) -> Type[BaseModel]:
+        """
+        Get a pydantic model class from a given namespace and version!
+
+        Wrapper around :meth:`.PydanticProvider.get_class`
+        """
+        return PydanticProvider(path=self.path).get_class(namespace, class_, version)
+
+
+
+
+
+
+
 
-        self.verbose = verbose
 
 
 

nwb_linkml/tests/test_io/test_io_hdf5.py

@@ -1,6 +1,10 @@
+import pdb
+
 import pytest
 from pathlib import Path
 
+from ..fixtures import tmp_output_dir, set_config_vars
+
 from nwb_linkml.io.hdf5 import HDF5IO
 @pytest.mark.skip()
 def test_hdf_read():
@@ -8,4 +12,6 @@ def test_hdf_read():
     if not NWBFILE.exists():
         return
     io = HDF5IO(path=NWBFILE)
-    model = io.read('/general')
+    model = io.read('acquisition')
+
+    pdb.set_trace()

scripts/generate_core.py

@@ -1,19 +1,34 @@
+import pdb
+import shutil
+import os
+import traceback
+
 from argparse import ArgumentParser
 from pathlib import Path
 from linkml_runtime.dumpers import yaml_dumper
+from rich.live import Live
+from rich.panel import Panel
+from rich.console import Group
+from rich.progress import Progress, SpinnerColumn, BarColumn, TextColumn, Column
+from rich import print
 from nwb_linkml.generators.pydantic import NWBPydanticGenerator
 
-from nwb_linkml.src.nwb_linkml import io
+from nwb_linkml.providers.schema import LinkMLProvider, PydanticProvider
+from nwb_linkml.providers.git import NWB_CORE_REPO, GitRepo
+from nwb_linkml.io import schema as io
 
+def generate_core_yaml(output_path:Path, dry_run:bool=False):
+    """Just build the latest version of the core schema"""
 
-def generate_core_yaml(output_path:Path):
     core = io.load_nwb_core()
     built_schemas = core.build().schemas
     for schema in built_schemas:
         output_file = output_path / (schema.name + '.yaml')
-        yaml_dumper.dump(schema, output_file)
+        if not dry_run:
+            yaml_dumper.dump(schema, output_file)
 
-def generate_core_pydantic(yaml_path:Path, output_path:Path):
+def generate_core_pydantic(yaml_path:Path, output_path:Path, dry_run:bool=False):
+    """Just generate the latest version of the core schema"""
     for schema in yaml_path.glob('*.yaml'):
         python_name = schema.stem.replace('.', '_').replace('-', '_')
         pydantic_file = (output_path / python_name).with_suffix('.py')
@@ -26,11 +41,109 @@ def generate_core_pydantic(yaml_path:Path, output_path:Path):
             gen_slots=True
         )
         gen_pydantic = generator.serialize()
-        with open(pydantic_file, 'w') as pfile:
-            pfile.write(gen_pydantic)
+        if not dry_run:
+            with open(pydantic_file, 'w') as pfile:
+                pfile.write(gen_pydantic)
+
+def generate_versions(yaml_path:Path, pydantic_path:Path, dry_run:bool=False):
+    """
+    Generate linkml models for all versions
+    """
+    repo = GitRepo(NWB_CORE_REPO)
+    #repo.clone(force=True)
+    repo.clone()
+
+    # use a directory underneath this one as the temporary directory rather than
+    # the default hidden one
+    tmp_dir = Path(__file__).parent / '__tmp__'
+    if tmp_dir.exists():
+        shutil.rmtree(tmp_dir)
+    tmp_dir.mkdir()
+
+    linkml_provider = LinkMLProvider(path=tmp_dir, verbose=False)
+    pydantic_provider = PydanticProvider(path=tmp_dir, verbose=False)
+
+    failed_versions = {}
+
+    overall_progress = Progress()
+    overall_task = overall_progress.add_task('All Versions', total=len(NWB_CORE_REPO.versions))
+
+    build_progress = Progress(
+        TextColumn("[bold blue]{task.fields[name]} - [bold green]{task.fields[action]}",
+                   table_column=Column(ratio=1)),
+        BarColumn(table_column=Column(ratio=1), bar_width=None)
+    )
+    panel = Panel(Group(build_progress, overall_progress))
+
+
+    with Live(panel) as live:
+        # make pbar tasks
+        linkml_task = None
+        pydantic_task = None
+
+        for version in NWB_CORE_REPO.versions:
+            # build linkml
+            try:
+                # check out the version (this should also refresh the hdmf-common schema)
+                linkml_task = build_progress.add_task('', name=version, action='Checkout Version', total=3)
+                repo.tag = version
+                build_progress.update(linkml_task, advance=1, action="Load Namespaces")
+
+                # first load the core namespace
+                core_ns = io.load_namespace_adapter(repo.namespace_file)
+                # then the hdmf-common namespace
+                hdmf_common_ns = io.load_namespace_adapter(repo.temp_directory / 'hdmf-common-schema' / 'common' / 'namespace.yaml')
+                core_ns.imported.append(hdmf_common_ns)
+                build_progress.update(linkml_task, advance=1, action="Build LinkML")
+
+
+                linkml_res = linkml_provider.build(core_ns)
+                build_progress.update(linkml_task, advance=1, action="Built LinkML")
+
+                # build pydantic
+                ns_files = [res['namespace'] for res in linkml_res.values()]
+                all_schema = []
+                for ns_file in ns_files:
+                    all_schema.extend(list(ns_file.parent.glob('*.yaml')))
+
+                pydantic_task = build_progress.add_task('', name=version, action='', total=len(all_schema))
+                for schema in all_schema:
+                    pbar_string = ' - '.join([schema.parts[-3], schema.parts[-2], schema.parts[-1]])
+                    build_progress.update(pydantic_task, action=pbar_string)
+                    pydantic_provider.build(schema, versions=core_ns.versions, split=True)
+                    build_progress.update(pydantic_task, advance=1)
+                build_progress.update(pydantic_task, action='Built Pydantic')
+
+
+
+            except Exception as e:
+                build_progress.stop_task(linkml_task)
+                if linkml_task is not None:
+                    build_progress.update(linkml_task, action='[bold red]LinkML Build Failed')
+                    build_progress.stop_task(linkml_task)
+                if pydantic_task is not None:
+                    build_progress.update(pydantic_task, action='[bold red]LinkML Build Failed')
+                    build_progress.stop_task(pydantic_task)
+                failed_versions[version] = traceback.format_exception(e)
+
+            finally:
+                overall_progress.update(overall_task, advance=1)
+                linkml_task = None
+                pydantic_task = None
+
+    if not dry_run:
+        shutil.move(tmp_dir / 'linkml', yaml_path)
+        shutil.move(tmp_dir / 'pydantic', pydantic_path)
+
+    if len(failed_versions) > 0:
+        print('Failed Building Versions:')
+        print(failed_versions)
+
+
+
 
 def parser() -> ArgumentParser:
-    parser = ArgumentParser('Generate NWB core schema')
+    parser = ArgumentParser('Generate all available versions of NWB core schema')
     parser.add_argument(
         '--yaml',
         help="directory to export linkML schema to",
@@ -43,15 +156,29 @@ def parser() -> ArgumentParser:
         type=Path,
         default=Path(__file__).parent.parent / 'nwb_linkml' / 'src' / 'nwb_linkml' / 'models'
     )
+    parser.add_argument(
+        '--latest',
+        help="Only generate the latest version of the core schemas.",
+        action="store_true"
+    )
+    parser.add_argument(
+        '--dry-run',
+        help="Generate schema and pydantic models without moving them into the target directories, for testing purposes",
+        action='store_true'
+    )
     return parser
 
 
 def main():
     args = parser().parse_args()
-    args.yaml.mkdir(exist_ok=True)
-    args.pydantic.mkdir(exist_ok=True)
-    generate_core_yaml(args.yaml)
-    generate_core_pydantic(args.yaml, args.pydantic)
+    if not args.dry_run:
+        args.yaml.mkdir(exist_ok=True)
+        args.pydantic.mkdir(exist_ok=True)
+    if args.latest:
+        generate_core_yaml(args.yaml, args.dry_run)
+        generate_core_pydantic(args.yaml, args.pydantic, args.dry_run)
+    else:
+        generate_versions(args.yaml, args.pydantic, args.dry_run)
 
 if __name__ == "__main__":
     main()