Dump yaml

nwb_linkml/pyproject.toml

@@ -21,7 +21,7 @@ dependencies = [
     "h5py>=3.9.0",
     "pydantic-settings>=2.0.3",
     "tqdm>=4.66.1",
-    'typing-extensions>=4.12.2;python_version<"3.11"',
+    'typing-extensions>=4.12.2;python_version<"3.13"',
     "numpydantic>=1.6.0",
     "black>=24.4.2",
     "pandas>=2.2.2",

nwb_linkml/src/nwb_linkml/adapters/adapter.py

@@ -4,10 +4,23 @@
 
 import os
 import sys
-from abc import abstractmethod
+from abc import abstractmethod, ABC
 from dataclasses import dataclass, field
 from logging import Logger
-from typing import Any, Generator, List, Literal, Optional, Tuple, Type, TypeVar, Union, overload
+from typing import (
+    Any,
+    Generator,
+    List,
+    Literal,
+    Optional,
+    Tuple,
+    Type,
+    TypeVar,
+    Union,
+    overload,
+    Sequence,
+    Mapping,
+)
 
 from linkml_runtime.dumpers import yaml_dumper
 from linkml_runtime.linkml_model import (
@@ -273,6 +286,23 @@ def walk_types(
                 yield item
 
 
+class Map(ABC):
+    """
+    The generic top-level mapping class is just a classmethod for checking if the map applies and a
+    method for applying the check if it does
+    """
+
+    @classmethod
+    @abstractmethod
+    def check(cls, *args: Sequence, **kwargs: Mapping) -> bool:
+        """Check if this map applies to the given item to read"""
+
+    @classmethod
+    @abstractmethod
+    def apply(cls, *args: Sequence, **kwargs: Mapping) -> Any:
+        """Actually apply the map!"""
+
+
 def is_1d(cls: Dataset | Attribute) -> bool:
     """
     Check if the values of a dataset are 1-dimensional.

nwb_linkml/src/nwb_linkml/adapters/attribute.py

@@ -7,9 +7,8 @@
 
 from linkml_runtime.linkml_model.meta import SlotDefinition
 
-from nwb_linkml.adapters.adapter import Adapter, BuildResult, defaults, is_1d
+from nwb_linkml.adapters.adapter import Adapter, BuildResult, defaults, is_1d, Map
 from nwb_linkml.adapters.array import ArrayAdapter
-from nwb_linkml.maps import Map
 from nwb_linkml.maps.dtype import handle_dtype, inlined
 from nwb_schema_language import Attribute
 

nwb_linkml/src/nwb_linkml/adapters/dataset.py

@@ -7,10 +7,10 @@
 
 from linkml_runtime.linkml_model.meta import ArrayExpression, SlotDefinition
 
-from nwb_linkml.adapters.adapter import BuildResult, defaults, has_attrs, is_1d, is_compound
+from nwb_linkml.adapters.adapter import BuildResult, defaults, has_attrs, is_1d, is_compound, Map
 from nwb_linkml.adapters.array import ArrayAdapter
 from nwb_linkml.adapters.classes import ClassAdapter
-from nwb_linkml.maps import QUANTITY_MAP, Map
+from nwb_linkml.maps import QUANTITY_MAP
 from nwb_linkml.maps.dtype import flat_to_linkml, handle_dtype, inlined
 from nwb_linkml.maps.naming import camel_to_snake
 from nwb_schema_language import Dataset

nwb_linkml/src/nwb_linkml/generators/pydantic.py

@@ -284,9 +284,9 @@ def inject_dynamictable(cls: ClassResult) -> ClassResult:
             cls.cls.bases = ["AlignedDynamicTableMixin", "DynamicTable"]
         elif cls.cls.name == "ElementIdentifiers":
             cls.cls.bases = ["ElementIdentifiersMixin", "Data"]
-            # make ``value`` generic on T
+            # Formerly make this generic, but that breaks json serialization
             if "value" in cls.cls.attributes:
-                cls.cls.attributes["value"].range = "Optional[T]"
+                cls.cls.attributes["value"].range = "Optional[NDArray]"
         elif cls.cls.name == "TimeSeriesReferenceVectorData":
             # in core.nwb.base, so need to inject and import again
             cls.cls.bases = ["TimeSeriesReferenceVectorDataMixin", "VectorData"]

nwb_linkml/src/nwb_linkml/includes/hdmf.py

@@ -13,10 +13,10 @@
     List,
     Optional,
     Tuple,
-    TypeVar,
     Union,
     overload,
 )
+from typing_extensions import TypeVar
 
 import numpy as np
 import pandas as pd
@@ -36,8 +36,8 @@
 if TYPE_CHECKING:  # pragma: no cover
     from nwb_models.models import VectorData, VectorIndex
 
-T = TypeVar("T", bound=NDArray)
-T_INJECT = 'T = TypeVar("T", bound=NDArray)'
+T = TypeVar("T", default=NDArray)
+T_INJECT = 'T = TypeVar("T", default=NDArray)'
 
 if "pytest" in sys.modules:
     from nwb_models.models import ConfiguredBaseModel
@@ -71,7 +71,7 @@ class DynamicTableMixin(ConfiguredBaseModel):
     """
 
     model_config = ConfigDict(extra="allow", validate_assignment=True)
-    __pydantic_extra__: Dict[str, Union["VectorDataMixin", "VectorIndexMixin", "NDArray", list]]
+    __pydantic_extra__: Dict[str, Union["VectorDataMixin", "VectorIndexMixin"]]
     NON_COLUMN_FIELDS: ClassVar[tuple[str]] = (
         "id",
         "name",
@@ -899,10 +899,10 @@ class ElementIdentifiersMixin(VectorDataMixin):
                 ObjectImport(name="Generic"),
                 ObjectImport(name="Iterable"),
                 ObjectImport(name="Tuple"),
-                ObjectImport(name="TypeVar"),
                 ObjectImport(name="overload"),
             ],
         ),
+        Import(module="typing_extensions", objects=[ObjectImport(name="TypeVar")]),
         Import(
             module="numpydantic", objects=[ObjectImport(name="NDArray"), ObjectImport(name="Shape")]
         ),