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regenerate models

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This commit is contained in:
sneakers-the-rat 2024-08-13 23:39:11 -07:00
parent 43ff3503dc
commit d61d1ecf22
Signed by untrusted user who does not match committer: jonny
GPG key ID: 6DCB96EF1E4D232D
12 changed files with 300 additions and 216 deletions
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43
nwb_linkml/src/nwb_linkml/models/pydantic/hdmf_common/v1_1_0/hdmf_common_table.py
View file

@ -245,7 +245,7 @@ class DynamicTableMixin(BaseModel):
"""
model_config = ConfigDict(extra="allow")
__pydantic_extra__: Dict[str, Union[list, "NDArray", "VectorDataMixin"]]
__pydantic_extra__: Dict[str, Union["VectorDataMixin", "VectorIndexMixin", "NDArray", list]]
NON_COLUMN_FIELDS: ClassVar[tuple[str]] = (
"name",
"colnames",
@ -445,8 +445,9 @@ class DynamicTableMixin(BaseModel):
model["colnames"] = colnames
return model
@model_validator(mode="after")
def cast_extra_columns(self) -> "DynamicTableMixin":
@model_validator(mode="before")
@classmethod
def cast_extra_columns(cls, model: Dict[str, Any]) -> Dict:
"""
If extra columns are passed as just lists or arrays, cast to VectorData
before we resolve targets for VectorData and VectorIndex pairs.
@ -454,22 +455,20 @@ class DynamicTableMixin(BaseModel):
See :meth:`.cast_specified_columns` for handling columns in the class specification
"""
# if columns are not in the specification, cast to a generic VectorData
for key, val in self.__pydantic_extra__.items():
for key, val in model.items():
if key in cls.model_fields:
continue
if not isinstance(val, (VectorData, VectorIndex)):
try:
if key.endswith("_index"):
self.__pydantic_extra__[key] = VectorIndex(
name=key, description="", value=val
)
model[key] = VectorIndex(name=key, description="", value=val)
else:
self.__pydantic_extra__[key] = VectorData(
name=key, description="", value=val
)
model[key] = VectorData(name=key, description="", value=val)
except ValidationError as e:
raise ValidationError(
f"field {key} cannot be cast to VectorData from {val}"
) from e
return self
return model
@model_validator(mode="after")
def resolve_targets(self) -> "DynamicTableMixin":
@ -481,6 +480,8 @@ class DynamicTableMixin(BaseModel):
# find an index
idx = None
for field_name in self.model_fields_set:
if field_name in self.NON_COLUMN_FIELDS or field_name == key:
continue
# implicit name-based index
field = getattr(self, field_name)
if isinstance(field, VectorIndex) and (
@ -519,17 +520,23 @@ class DynamicTableMixin(BaseModel):
"""
try:
return handler(val)
except ValidationError:
except ValidationError as e:
annotation = cls.model_fields[info.field_name].annotation
if type(annotation).__name__ == "_UnionGenericAlias":
annotation = annotation.__args__[0]
return handler(
annotation(
val,
name=info.field_name,
description=cls.model_fields[info.field_name].description,
try:
# should pass if we're supposed to be a VectorData column
# don't want to override intention here by insisting that it is
# *actually* a VectorData column in case an NDArray has been specified for now
return handler(
annotation(
val,
name=info.field_name,
description=cls.model_fields[info.field_name].description,
)
)
)
except Exception:
raise e
class AlignedDynamicTableMixin(DynamicTableMixin):

43
nwb_linkml/src/nwb_linkml/models/pydantic/hdmf_common/v1_1_2/hdmf_common_table.py
View file

@ -245,7 +245,7 @@ class DynamicTableMixin(BaseModel):
"""
model_config = ConfigDict(extra="allow")
__pydantic_extra__: Dict[str, Union[list, "NDArray", "VectorDataMixin"]]
__pydantic_extra__: Dict[str, Union["VectorDataMixin", "VectorIndexMixin", "NDArray", list]]
NON_COLUMN_FIELDS: ClassVar[tuple[str]] = (
"name",
"colnames",
@ -445,8 +445,9 @@ class DynamicTableMixin(BaseModel):
model["colnames"] = colnames
return model
@model_validator(mode="after")
def cast_extra_columns(self) -> "DynamicTableMixin":
@model_validator(mode="before")
@classmethod
def cast_extra_columns(cls, model: Dict[str, Any]) -> Dict:
"""
If extra columns are passed as just lists or arrays, cast to VectorData
before we resolve targets for VectorData and VectorIndex pairs.
@ -454,22 +455,20 @@ class DynamicTableMixin(BaseModel):
See :meth:`.cast_specified_columns` for handling columns in the class specification
"""
# if columns are not in the specification, cast to a generic VectorData
for key, val in self.__pydantic_extra__.items():
for key, val in model.items():
if key in cls.model_fields:
continue
if not isinstance(val, (VectorData, VectorIndex)):
try:
if key.endswith("_index"):
self.__pydantic_extra__[key] = VectorIndex(
name=key, description="", value=val
)
model[key] = VectorIndex(name=key, description="", value=val)
else:
self.__pydantic_extra__[key] = VectorData(
name=key, description="", value=val
)
model[key] = VectorData(name=key, description="", value=val)
except ValidationError as e:
raise ValidationError(
f"field {key} cannot be cast to VectorData from {val}"
) from e
return self
return model
@model_validator(mode="after")
def resolve_targets(self) -> "DynamicTableMixin":
@ -481,6 +480,8 @@ class DynamicTableMixin(BaseModel):
# find an index
idx = None
for field_name in self.model_fields_set:
if field_name in self.NON_COLUMN_FIELDS or field_name == key:
continue
# implicit name-based index
field = getattr(self, field_name)
if isinstance(field, VectorIndex) and (
@ -519,17 +520,23 @@ class DynamicTableMixin(BaseModel):
"""
try:
return handler(val)
except ValidationError:
except ValidationError as e:
annotation = cls.model_fields[info.field_name].annotation
if type(annotation).__name__ == "_UnionGenericAlias":
annotation = annotation.__args__[0]
return handler(
annotation(
val,
name=info.field_name,
description=cls.model_fields[info.field_name].description,
try:
# should pass if we're supposed to be a VectorData column
# don't want to override intention here by insisting that it is
# *actually* a VectorData column in case an NDArray has been specified for now
return handler(
annotation(
val,
name=info.field_name,
description=cls.model_fields[info.field_name].description,
)
)
)
except Exception:
raise e
class AlignedDynamicTableMixin(DynamicTableMixin):

43
nwb_linkml/src/nwb_linkml/models/pydantic/hdmf_common/v1_1_3/hdmf_common_table.py
View file

@ -245,7 +245,7 @@ class DynamicTableMixin(BaseModel):
"""
model_config = ConfigDict(extra="allow")
__pydantic_extra__: Dict[str, Union[list, "NDArray", "VectorDataMixin"]]
__pydantic_extra__: Dict[str, Union["VectorDataMixin", "VectorIndexMixin", "NDArray", list]]
NON_COLUMN_FIELDS: ClassVar[tuple[str]] = (
"name",
"colnames",
@ -445,8 +445,9 @@ class DynamicTableMixin(BaseModel):
model["colnames"] = colnames
return model
@model_validator(mode="after")
def cast_extra_columns(self) -> "DynamicTableMixin":
@model_validator(mode="before")
@classmethod
def cast_extra_columns(cls, model: Dict[str, Any]) -> Dict:
"""
If extra columns are passed as just lists or arrays, cast to VectorData
before we resolve targets for VectorData and VectorIndex pairs.
@ -454,22 +455,20 @@ class DynamicTableMixin(BaseModel):
See :meth:`.cast_specified_columns` for handling columns in the class specification
"""
# if columns are not in the specification, cast to a generic VectorData
for key, val in self.__pydantic_extra__.items():
for key, val in model.items():
if key in cls.model_fields:
continue
if not isinstance(val, (VectorData, VectorIndex)):
try:
if key.endswith("_index"):
self.__pydantic_extra__[key] = VectorIndex(
name=key, description="", value=val
)
model[key] = VectorIndex(name=key, description="", value=val)
else:
self.__pydantic_extra__[key] = VectorData(
name=key, description="", value=val
)
model[key] = VectorData(name=key, description="", value=val)
except ValidationError as e:
raise ValidationError(
f"field {key} cannot be cast to VectorData from {val}"
) from e
return self
return model
@model_validator(mode="after")
def resolve_targets(self) -> "DynamicTableMixin":
@ -481,6 +480,8 @@ class DynamicTableMixin(BaseModel):
# find an index
idx = None
for field_name in self.model_fields_set:
if field_name in self.NON_COLUMN_FIELDS or field_name == key:
continue
# implicit name-based index
field = getattr(self, field_name)
if isinstance(field, VectorIndex) and (
@ -519,17 +520,23 @@ class DynamicTableMixin(BaseModel):
"""
try:
return handler(val)
except ValidationError:
except ValidationError as e:
annotation = cls.model_fields[info.field_name].annotation
if type(annotation).__name__ == "_UnionGenericAlias":
annotation = annotation.__args__[0]
return handler(
annotation(
val,
name=info.field_name,
description=cls.model_fields[info.field_name].description,
try:
# should pass if we're supposed to be a VectorData column
# don't want to override intention here by insisting that it is
# *actually* a VectorData column in case an NDArray has been specified for now
return handler(
annotation(
val,
name=info.field_name,
description=cls.model_fields[info.field_name].description,
)
)
)
except Exception:
raise e
class AlignedDynamicTableMixin(DynamicTableMixin):

43
nwb_linkml/src/nwb_linkml/models/pydantic/hdmf_common/v1_2_0/hdmf_common_table.py
View file

@ -246,7 +246,7 @@ class DynamicTableMixin(BaseModel):
"""
model_config = ConfigDict(extra="allow")
__pydantic_extra__: Dict[str, Union[list, "NDArray", "VectorDataMixin"]]
__pydantic_extra__: Dict[str, Union["VectorDataMixin", "VectorIndexMixin", "NDArray", list]]
NON_COLUMN_FIELDS: ClassVar[tuple[str]] = (
"name",
"colnames",
@ -446,8 +446,9 @@ class DynamicTableMixin(BaseModel):
model["colnames"] = colnames
return model
@model_validator(mode="after")
def cast_extra_columns(self) -> "DynamicTableMixin":
@model_validator(mode="before")
@classmethod
def cast_extra_columns(cls, model: Dict[str, Any]) -> Dict:
"""
If extra columns are passed as just lists or arrays, cast to VectorData
before we resolve targets for VectorData and VectorIndex pairs.
@ -455,22 +456,20 @@ class DynamicTableMixin(BaseModel):
See :meth:`.cast_specified_columns` for handling columns in the class specification
"""
# if columns are not in the specification, cast to a generic VectorData
for key, val in self.__pydantic_extra__.items():
for key, val in model.items():
if key in cls.model_fields:
continue
if not isinstance(val, (VectorData, VectorIndex)):
try:
if key.endswith("_index"):
self.__pydantic_extra__[key] = VectorIndex(
name=key, description="", value=val
)
model[key] = VectorIndex(name=key, description="", value=val)
else:
self.__pydantic_extra__[key] = VectorData(
name=key, description="", value=val
)
model[key] = VectorData(name=key, description="", value=val)
except ValidationError as e:
raise ValidationError(
f"field {key} cannot be cast to VectorData from {val}"
) from e
return self
return model
@model_validator(mode="after")
def resolve_targets(self) -> "DynamicTableMixin":
@ -482,6 +481,8 @@ class DynamicTableMixin(BaseModel):
# find an index
idx = None
for field_name in self.model_fields_set:
if field_name in self.NON_COLUMN_FIELDS or field_name == key:
continue
# implicit name-based index
field = getattr(self, field_name)
if isinstance(field, VectorIndex) and (
@ -520,17 +521,23 @@ class DynamicTableMixin(BaseModel):
"""
try:
return handler(val)
except ValidationError:
except ValidationError as e:
annotation = cls.model_fields[info.field_name].annotation
if type(annotation).__name__ == "_UnionGenericAlias":
annotation = annotation.__args__[0]
return handler(
annotation(
val,
name=info.field_name,
description=cls.model_fields[info.field_name].description,
try:
# should pass if we're supposed to be a VectorData column
# don't want to override intention here by insisting that it is
# *actually* a VectorData column in case an NDArray has been specified for now
return handler(
annotation(
val,
name=info.field_name,
description=cls.model_fields[info.field_name].description,
)
)
)
except Exception:
raise e
class AlignedDynamicTableMixin(DynamicTableMixin):

43
nwb_linkml/src/nwb_linkml/models/pydantic/hdmf_common/v1_2_1/hdmf_common_table.py
View file

@ -246,7 +246,7 @@ class DynamicTableMixin(BaseModel):
"""
model_config = ConfigDict(extra="allow")
__pydantic_extra__: Dict[str, Union[list, "NDArray", "VectorDataMixin"]]
__pydantic_extra__: Dict[str, Union["VectorDataMixin", "VectorIndexMixin", "NDArray", list]]
NON_COLUMN_FIELDS: ClassVar[tuple[str]] = (
"name",
"colnames",
@ -446,8 +446,9 @@ class DynamicTableMixin(BaseModel):
model["colnames"] = colnames
return model
@model_validator(mode="after")
def cast_extra_columns(self) -> "DynamicTableMixin":
@model_validator(mode="before")
@classmethod
def cast_extra_columns(cls, model: Dict[str, Any]) -> Dict:
"""
If extra columns are passed as just lists or arrays, cast to VectorData
before we resolve targets for VectorData and VectorIndex pairs.
@ -455,22 +456,20 @@ class DynamicTableMixin(BaseModel):
See :meth:`.cast_specified_columns` for handling columns in the class specification
"""
# if columns are not in the specification, cast to a generic VectorData
for key, val in self.__pydantic_extra__.items():
for key, val in model.items():
if key in cls.model_fields:
continue
if not isinstance(val, (VectorData, VectorIndex)):
try:
if key.endswith("_index"):
self.__pydantic_extra__[key] = VectorIndex(
name=key, description="", value=val
)
model[key] = VectorIndex(name=key, description="", value=val)
else:
self.__pydantic_extra__[key] = VectorData(
name=key, description="", value=val
)
model[key] = VectorData(name=key, description="", value=val)
except ValidationError as e:
raise ValidationError(
f"field {key} cannot be cast to VectorData from {val}"
) from e
return self
return model
@model_validator(mode="after")
def resolve_targets(self) -> "DynamicTableMixin":
@ -482,6 +481,8 @@ class DynamicTableMixin(BaseModel):
# find an index
idx = None
for field_name in self.model_fields_set:
if field_name in self.NON_COLUMN_FIELDS or field_name == key:
continue
# implicit name-based index
field = getattr(self, field_name)
if isinstance(field, VectorIndex) and (
@ -520,17 +521,23 @@ class DynamicTableMixin(BaseModel):
"""
try:
return handler(val)
except ValidationError:
except ValidationError as e:
annotation = cls.model_fields[info.field_name].annotation
if type(annotation).__name__ == "_UnionGenericAlias":
annotation = annotation.__args__[0]
return handler(
annotation(
val,
name=info.field_name,
description=cls.model_fields[info.field_name].description,
try:
# should pass if we're supposed to be a VectorData column
# don't want to override intention here by insisting that it is
# *actually* a VectorData column in case an NDArray has been specified for now
return handler(
annotation(
val,
name=info.field_name,
description=cls.model_fields[info.field_name].description,
)
)
)
except Exception:
raise e
class AlignedDynamicTableMixin(DynamicTableMixin):

43
nwb_linkml/src/nwb_linkml/models/pydantic/hdmf_common/v1_3_0/hdmf_common_table.py
View file

@ -246,7 +246,7 @@ class DynamicTableMixin(BaseModel):
"""
model_config = ConfigDict(extra="allow")
__pydantic_extra__: Dict[str, Union[list, "NDArray", "VectorDataMixin"]]
__pydantic_extra__: Dict[str, Union["VectorDataMixin", "VectorIndexMixin", "NDArray", list]]
NON_COLUMN_FIELDS: ClassVar[tuple[str]] = (
"name",
"colnames",
@ -446,8 +446,9 @@ class DynamicTableMixin(BaseModel):
model["colnames"] = colnames
return model
@model_validator(mode="after")
def cast_extra_columns(self) -> "DynamicTableMixin":
@model_validator(mode="before")
@classmethod
def cast_extra_columns(cls, model: Dict[str, Any]) -> Dict:
"""
If extra columns are passed as just lists or arrays, cast to VectorData
before we resolve targets for VectorData and VectorIndex pairs.
@ -455,22 +456,20 @@ class DynamicTableMixin(BaseModel):
See :meth:`.cast_specified_columns` for handling columns in the class specification
"""
# if columns are not in the specification, cast to a generic VectorData
for key, val in self.__pydantic_extra__.items():
for key, val in model.items():
if key in cls.model_fields:
continue
if not isinstance(val, (VectorData, VectorIndex)):
try:
if key.endswith("_index"):
self.__pydantic_extra__[key] = VectorIndex(
name=key, description="", value=val
)
model[key] = VectorIndex(name=key, description="", value=val)
else:
self.__pydantic_extra__[key] = VectorData(
name=key, description="", value=val
)
model[key] = VectorData(name=key, description="", value=val)
except ValidationError as e:
raise ValidationError(
f"field {key} cannot be cast to VectorData from {val}"
) from e
return self
return model
@model_validator(mode="after")
def resolve_targets(self) -> "DynamicTableMixin":
@ -482,6 +481,8 @@ class DynamicTableMixin(BaseModel):
# find an index
idx = None
for field_name in self.model_fields_set:
if field_name in self.NON_COLUMN_FIELDS or field_name == key:
continue
# implicit name-based index
field = getattr(self, field_name)
if isinstance(field, VectorIndex) and (
@ -520,17 +521,23 @@ class DynamicTableMixin(BaseModel):
"""
try:
return handler(val)
except ValidationError:
except ValidationError as e:
annotation = cls.model_fields[info.field_name].annotation
if type(annotation).__name__ == "_UnionGenericAlias":
annotation = annotation.__args__[0]
return handler(
annotation(
val,
name=info.field_name,
description=cls.model_fields[info.field_name].description,
try:
# should pass if we're supposed to be a VectorData column
# don't want to override intention here by insisting that it is
# *actually* a VectorData column in case an NDArray has been specified for now
return handler(
annotation(
val,
name=info.field_name,
description=cls.model_fields[info.field_name].description,
)
)
)
except Exception:
raise e
class AlignedDynamicTableMixin(DynamicTableMixin):

43
nwb_linkml/src/nwb_linkml/models/pydantic/hdmf_common/v1_4_0/hdmf_common_table.py
View file

@ -246,7 +246,7 @@ class DynamicTableMixin(BaseModel):
"""
model_config = ConfigDict(extra="allow")
__pydantic_extra__: Dict[str, Union[list, "NDArray", "VectorDataMixin"]]
__pydantic_extra__: Dict[str, Union["VectorDataMixin", "VectorIndexMixin", "NDArray", list]]
NON_COLUMN_FIELDS: ClassVar[tuple[str]] = (
"name",
"colnames",
@ -446,8 +446,9 @@ class DynamicTableMixin(BaseModel):
model["colnames"] = colnames
return model
@model_validator(mode="after")
def cast_extra_columns(self) -> "DynamicTableMixin":
@model_validator(mode="before")
@classmethod
def cast_extra_columns(cls, model: Dict[str, Any]) -> Dict:
"""
If extra columns are passed as just lists or arrays, cast to VectorData
before we resolve targets for VectorData and VectorIndex pairs.
@ -455,22 +456,20 @@ class DynamicTableMixin(BaseModel):
See :meth:`.cast_specified_columns` for handling columns in the class specification
"""
# if columns are not in the specification, cast to a generic VectorData
for key, val in self.__pydantic_extra__.items():
for key, val in model.items():
if key in cls.model_fields:
continue
if not isinstance(val, (VectorData, VectorIndex)):
try:
if key.endswith("_index"):
self.__pydantic_extra__[key] = VectorIndex(
name=key, description="", value=val
)
model[key] = VectorIndex(name=key, description="", value=val)
else:
self.__pydantic_extra__[key] = VectorData(
name=key, description="", value=val
)
model[key] = VectorData(name=key, description="", value=val)
except ValidationError as e:
raise ValidationError(
f"field {key} cannot be cast to VectorData from {val}"
) from e
return self
return model
@model_validator(mode="after")
def resolve_targets(self) -> "DynamicTableMixin":
@ -482,6 +481,8 @@ class DynamicTableMixin(BaseModel):
# find an index
idx = None
for field_name in self.model_fields_set:
if field_name in self.NON_COLUMN_FIELDS or field_name == key:
continue
# implicit name-based index
field = getattr(self, field_name)
if isinstance(field, VectorIndex) and (
@ -520,17 +521,23 @@ class DynamicTableMixin(BaseModel):
"""
try:
return handler(val)
except ValidationError:
except ValidationError as e:
annotation = cls.model_fields[info.field_name].annotation
if type(annotation).__name__ == "_UnionGenericAlias":
annotation = annotation.__args__[0]
return handler(
annotation(
val,
name=info.field_name,
description=cls.model_fields[info.field_name].description,
try:
# should pass if we're supposed to be a VectorData column
# don't want to override intention here by insisting that it is
# *actually* a VectorData column in case an NDArray has been specified for now
return handler(
annotation(
val,
name=info.field_name,
description=cls.model_fields[info.field_name].description,
)
)
)
except Exception:
raise e
class AlignedDynamicTableMixin(DynamicTableMixin):

43
nwb_linkml/src/nwb_linkml/models/pydantic/hdmf_common/v1_5_0/hdmf_common_table.py
View file

@ -246,7 +246,7 @@ class DynamicTableMixin(BaseModel):
"""
model_config = ConfigDict(extra="allow")
__pydantic_extra__: Dict[str, Union[list, "NDArray", "VectorDataMixin"]]
__pydantic_extra__: Dict[str, Union["VectorDataMixin", "VectorIndexMixin", "NDArray", list]]
NON_COLUMN_FIELDS: ClassVar[tuple[str]] = (
"name",
"colnames",
@ -446,8 +446,9 @@ class DynamicTableMixin(BaseModel):
model["colnames"] = colnames
return model
@model_validator(mode="after")
def cast_extra_columns(self) -> "DynamicTableMixin":
@model_validator(mode="before")
@classmethod
def cast_extra_columns(cls, model: Dict[str, Any]) -> Dict:
"""
If extra columns are passed as just lists or arrays, cast to VectorData
before we resolve targets for VectorData and VectorIndex pairs.
@ -455,22 +456,20 @@ class DynamicTableMixin(BaseModel):
See :meth:`.cast_specified_columns` for handling columns in the class specification
"""
# if columns are not in the specification, cast to a generic VectorData
for key, val in self.__pydantic_extra__.items():
for key, val in model.items():
if key in cls.model_fields:
continue
if not isinstance(val, (VectorData, VectorIndex)):
try:
if key.endswith("_index"):
self.__pydantic_extra__[key] = VectorIndex(
name=key, description="", value=val
)
model[key] = VectorIndex(name=key, description="", value=val)
else:
self.__pydantic_extra__[key] = VectorData(
name=key, description="", value=val
)
model[key] = VectorData(name=key, description="", value=val)
except ValidationError as e:
raise ValidationError(
f"field {key} cannot be cast to VectorData from {val}"
) from e
return self
return model
@model_validator(mode="after")
def resolve_targets(self) -> "DynamicTableMixin":
@ -482,6 +481,8 @@ class DynamicTableMixin(BaseModel):
# find an index
idx = None
for field_name in self.model_fields_set:
if field_name in self.NON_COLUMN_FIELDS or field_name == key:
continue
# implicit name-based index
field = getattr(self, field_name)
if isinstance(field, VectorIndex) and (
@ -520,17 +521,23 @@ class DynamicTableMixin(BaseModel):
"""
try:
return handler(val)
except ValidationError:
except ValidationError as e:
annotation = cls.model_fields[info.field_name].annotation
if type(annotation).__name__ == "_UnionGenericAlias":
annotation = annotation.__args__[0]
return handler(
annotation(
val,
name=info.field_name,
description=cls.model_fields[info.field_name].description,
try:
# should pass if we're supposed to be a VectorData column
# don't want to override intention here by insisting that it is
# *actually* a VectorData column in case an NDArray has been specified for now
return handler(
annotation(
val,
name=info.field_name,
description=cls.model_fields[info.field_name].description,
)
)
)
except Exception:
raise e
class AlignedDynamicTableMixin(DynamicTableMixin):

43
nwb_linkml/src/nwb_linkml/models/pydantic/hdmf_common/v1_5_1/hdmf_common_table.py
View file

@ -246,7 +246,7 @@ class DynamicTableMixin(BaseModel):
"""
model_config = ConfigDict(extra="allow")
__pydantic_extra__: Dict[str, Union[list, "NDArray", "VectorDataMixin"]]
__pydantic_extra__: Dict[str, Union["VectorDataMixin", "VectorIndexMixin", "NDArray", list]]
NON_COLUMN_FIELDS: ClassVar[tuple[str]] = (
"name",
"colnames",
@ -446,8 +446,9 @@ class DynamicTableMixin(BaseModel):
model["colnames"] = colnames
return model
@model_validator(mode="after")
def cast_extra_columns(self) -> "DynamicTableMixin":
@model_validator(mode="before")
@classmethod
def cast_extra_columns(cls, model: Dict[str, Any]) -> Dict:
"""
If extra columns are passed as just lists or arrays, cast to VectorData
before we resolve targets for VectorData and VectorIndex pairs.
@ -455,22 +456,20 @@ class DynamicTableMixin(BaseModel):
See :meth:`.cast_specified_columns` for handling columns in the class specification
"""
# if columns are not in the specification, cast to a generic VectorData
for key, val in self.__pydantic_extra__.items():
for key, val in model.items():
if key in cls.model_fields:
continue
if not isinstance(val, (VectorData, VectorIndex)):
try:
if key.endswith("_index"):
self.__pydantic_extra__[key] = VectorIndex(
name=key, description="", value=val
)
model[key] = VectorIndex(name=key, description="", value=val)
else:
self.__pydantic_extra__[key] = VectorData(
name=key, description="", value=val
)
model[key] = VectorData(name=key, description="", value=val)
except ValidationError as e:
raise ValidationError(
f"field {key} cannot be cast to VectorData from {val}"
) from e
return self
return model
@model_validator(mode="after")
def resolve_targets(self) -> "DynamicTableMixin":
@ -482,6 +481,8 @@ class DynamicTableMixin(BaseModel):
# find an index
idx = None
for field_name in self.model_fields_set:
if field_name in self.NON_COLUMN_FIELDS or field_name == key:
continue
# implicit name-based index
field = getattr(self, field_name)
if isinstance(field, VectorIndex) and (
@ -520,17 +521,23 @@ class DynamicTableMixin(BaseModel):
"""
try:
return handler(val)
except ValidationError:
except ValidationError as e:
annotation = cls.model_fields[info.field_name].annotation
if type(annotation).__name__ == "_UnionGenericAlias":
annotation = annotation.__args__[0]
return handler(
annotation(
val,
name=info.field_name,
description=cls.model_fields[info.field_name].description,
try:
# should pass if we're supposed to be a VectorData column
# don't want to override intention here by insisting that it is
# *actually* a VectorData column in case an NDArray has been specified for now
return handler(
annotation(
val,
name=info.field_name,
description=cls.model_fields[info.field_name].description,
)
)
)
except Exception:
raise e
class AlignedDynamicTableMixin(DynamicTableMixin):

43
nwb_linkml/src/nwb_linkml/models/pydantic/hdmf_common/v1_6_0/hdmf_common_table.py
View file

@ -246,7 +246,7 @@ class DynamicTableMixin(BaseModel):
"""
model_config = ConfigDict(extra="allow")
__pydantic_extra__: Dict[str, Union[list, "NDArray", "VectorDataMixin"]]
__pydantic_extra__: Dict[str, Union["VectorDataMixin", "VectorIndexMixin", "NDArray", list]]
NON_COLUMN_FIELDS: ClassVar[tuple[str]] = (
"name",
"colnames",
@ -446,8 +446,9 @@ class DynamicTableMixin(BaseModel):
model["colnames"] = colnames
return model
@model_validator(mode="after")
def cast_extra_columns(self) -> "DynamicTableMixin":
@model_validator(mode="before")
@classmethod
def cast_extra_columns(cls, model: Dict[str, Any]) -> Dict:
"""
If extra columns are passed as just lists or arrays, cast to VectorData
before we resolve targets for VectorData and VectorIndex pairs.
@ -455,22 +456,20 @@ class DynamicTableMixin(BaseModel):
See :meth:`.cast_specified_columns` for handling columns in the class specification
"""
# if columns are not in the specification, cast to a generic VectorData
for key, val in self.__pydantic_extra__.items():
for key, val in model.items():
if key in cls.model_fields:
continue
if not isinstance(val, (VectorData, VectorIndex)):
try:
if key.endswith("_index"):
self.__pydantic_extra__[key] = VectorIndex(
name=key, description="", value=val
)
model[key] = VectorIndex(name=key, description="", value=val)
else:
self.__pydantic_extra__[key] = VectorData(
name=key, description="", value=val
)
model[key] = VectorData(name=key, description="", value=val)
except ValidationError as e:
raise ValidationError(
f"field {key} cannot be cast to VectorData from {val}"
) from e
return self
return model
@model_validator(mode="after")
def resolve_targets(self) -> "DynamicTableMixin":
@ -482,6 +481,8 @@ class DynamicTableMixin(BaseModel):
# find an index
idx = None
for field_name in self.model_fields_set:
if field_name in self.NON_COLUMN_FIELDS or field_name == key:
continue
# implicit name-based index
field = getattr(self, field_name)
if isinstance(field, VectorIndex) and (
@ -520,17 +521,23 @@ class DynamicTableMixin(BaseModel):
"""
try:
return handler(val)
except ValidationError:
except ValidationError as e:
annotation = cls.model_fields[info.field_name].annotation
if type(annotation).__name__ == "_UnionGenericAlias":
annotation = annotation.__args__[0]
return handler(
annotation(
val,
name=info.field_name,
description=cls.model_fields[info.field_name].description,
try:
# should pass if we're supposed to be a VectorData column
# don't want to override intention here by insisting that it is
# *actually* a VectorData column in case an NDArray has been specified for now
return handler(
annotation(
val,
name=info.field_name,
description=cls.model_fields[info.field_name].description,
)
)
)
except Exception:
raise e
class AlignedDynamicTableMixin(DynamicTableMixin):

43
nwb_linkml/src/nwb_linkml/models/pydantic/hdmf_common/v1_7_0/hdmf_common_table.py
View file

@ -246,7 +246,7 @@ class DynamicTableMixin(BaseModel):
"""
model_config = ConfigDict(extra="allow")
__pydantic_extra__: Dict[str, Union[list, "NDArray", "VectorDataMixin"]]
__pydantic_extra__: Dict[str, Union["VectorDataMixin", "VectorIndexMixin", "NDArray", list]]
NON_COLUMN_FIELDS: ClassVar[tuple[str]] = (
"name",
"colnames",
@ -446,8 +446,9 @@ class DynamicTableMixin(BaseModel):
model["colnames"] = colnames
return model
@model_validator(mode="after")
def cast_extra_columns(self) -> "DynamicTableMixin":
@model_validator(mode="before")
@classmethod
def cast_extra_columns(cls, model: Dict[str, Any]) -> Dict:
"""
If extra columns are passed as just lists or arrays, cast to VectorData
before we resolve targets for VectorData and VectorIndex pairs.
@ -455,22 +456,20 @@ class DynamicTableMixin(BaseModel):
See :meth:`.cast_specified_columns` for handling columns in the class specification
"""
# if columns are not in the specification, cast to a generic VectorData
for key, val in self.__pydantic_extra__.items():
for key, val in model.items():
if key in cls.model_fields:
continue
if not isinstance(val, (VectorData, VectorIndex)):
try:
if key.endswith("_index"):
self.__pydantic_extra__[key] = VectorIndex(
name=key, description="", value=val
)
model[key] = VectorIndex(name=key, description="", value=val)
else:
self.__pydantic_extra__[key] = VectorData(
name=key, description="", value=val
)
model[key] = VectorData(name=key, description="", value=val)
except ValidationError as e:
raise ValidationError(
f"field {key} cannot be cast to VectorData from {val}"
) from e
return self
return model
@model_validator(mode="after")
def resolve_targets(self) -> "DynamicTableMixin":
@ -482,6 +481,8 @@ class DynamicTableMixin(BaseModel):
# find an index
idx = None
for field_name in self.model_fields_set:
if field_name in self.NON_COLUMN_FIELDS or field_name == key:
continue
# implicit name-based index
field = getattr(self, field_name)
if isinstance(field, VectorIndex) and (
@ -520,17 +521,23 @@ class DynamicTableMixin(BaseModel):
"""
try:
return handler(val)
except ValidationError:
except ValidationError as e:
annotation = cls.model_fields[info.field_name].annotation
if type(annotation).__name__ == "_UnionGenericAlias":
annotation = annotation.__args__[0]
return handler(
annotation(
val,
name=info.field_name,
description=cls.model_fields[info.field_name].description,
try:
# should pass if we're supposed to be a VectorData column
# don't want to override intention here by insisting that it is
# *actually* a VectorData column in case an NDArray has been specified for now
return handler(
annotation(
val,
name=info.field_name,
description=cls.model_fields[info.field_name].description,
)
)
)
except Exception:
raise e
class AlignedDynamicTableMixin(DynamicTableMixin):

43
nwb_linkml/src/nwb_linkml/models/pydantic/hdmf_common/v1_8_0/hdmf_common_table.py
View file

@ -246,7 +246,7 @@ class DynamicTableMixin(BaseModel):
"""
model_config = ConfigDict(extra="allow")
__pydantic_extra__: Dict[str, Union[list, "NDArray", "VectorDataMixin"]]
__pydantic_extra__: Dict[str, Union["VectorDataMixin", "VectorIndexMixin", "NDArray", list]]
NON_COLUMN_FIELDS: ClassVar[tuple[str]] = (
"name",
"colnames",
@ -446,8 +446,9 @@ class DynamicTableMixin(BaseModel):
model["colnames"] = colnames
return model
@model_validator(mode="after")
def cast_extra_columns(self) -> "DynamicTableMixin":
@model_validator(mode="before")
@classmethod
def cast_extra_columns(cls, model: Dict[str, Any]) -> Dict:
"""
If extra columns are passed as just lists or arrays, cast to VectorData
before we resolve targets for VectorData and VectorIndex pairs.
@ -455,22 +456,20 @@ class DynamicTableMixin(BaseModel):
See :meth:`.cast_specified_columns` for handling columns in the class specification
"""
# if columns are not in the specification, cast to a generic VectorData
for key, val in self.__pydantic_extra__.items():
for key, val in model.items():
if key in cls.model_fields:
continue
if not isinstance(val, (VectorData, VectorIndex)):
try:
if key.endswith("_index"):
self.__pydantic_extra__[key] = VectorIndex(
name=key, description="", value=val
)
model[key] = VectorIndex(name=key, description="", value=val)
else:
self.__pydantic_extra__[key] = VectorData(
name=key, description="", value=val
)
model[key] = VectorData(name=key, description="", value=val)
except ValidationError as e:
raise ValidationError(
f"field {key} cannot be cast to VectorData from {val}"
) from e
return self
return model
@model_validator(mode="after")
def resolve_targets(self) -> "DynamicTableMixin":
@ -482,6 +481,8 @@ class DynamicTableMixin(BaseModel):
# find an index
idx = None
for field_name in self.model_fields_set:
if field_name in self.NON_COLUMN_FIELDS or field_name == key:
continue
# implicit name-based index
field = getattr(self, field_name)
if isinstance(field, VectorIndex) and (
@ -520,17 +521,23 @@ class DynamicTableMixin(BaseModel):
"""
try:
return handler(val)
except ValidationError:
except ValidationError as e:
annotation = cls.model_fields[info.field_name].annotation
if type(annotation).__name__ == "_UnionGenericAlias":
annotation = annotation.__args__[0]
return handler(
annotation(
val,
name=info.field_name,
description=cls.model_fields[info.field_name].description,
try:
# should pass if we're supposed to be a VectorData column
# don't want to override intention here by insisting that it is
# *actually* a VectorData column in case an NDArray has been specified for now
return handler(
annotation(
val,
name=info.field_name,
description=cls.model_fields[info.field_name].description,
)
)
)
except Exception:
raise e
class AlignedDynamicTableMixin(DynamicTableMixin):