nwb-linkml/nwb_linkml/models/hdmf_experimental_experimental.py
sneakers-the-rat be21325123 Cleaner code generation, npytyping type hints for arrays
- split off generated subclasses into "include" files, not sure if that's good, but in any case we have them separable now.
- more work on cleanly un-nesting scalar and 1D-vector data into attributes and lists, respectively
- brought the pydantic generator in-repo to do a bunch of overrides
2023-08-28 22:16:58 -07:00

47 lines
1.6 KiB
Python

from __future__ import annotations
from datetime import datetime, date
from enum import Enum
from typing import List, Dict, Optional, Any, Union
from pydantic import BaseModel as BaseModel, Field
from nptyping import NDArray, 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
import sys
if sys.version_info >= (3, 8):
from typing import Literal
else:
from typing_extensions import Literal
from .hdmf_common_table import (
VectorData
)
metamodel_version = "None"
version = "None"
class WeakRefShimBaseModel(BaseModel):
__slots__ = '__weakref__'
class ConfiguredBaseModel(WeakRefShimBaseModel,
validate_assignment = True,
validate_all = True,
underscore_attrs_are_private = True,
extra = 'forbid',
arbitrary_types_allowed = True,
use_enum_values = True):
pass
class EnumData(VectorData):
"""
Data that come from a fixed set of values. A data value of i corresponds to the i-th value in the VectorData referenced by the 'elements' attribute.
"""
elements: Optional[VectorData] = Field(None, description="""Reference to the VectorData object that contains the enumerable elements""")
description: Optional[str] = Field(None, description="""Description of what these vectors represent.""")
array: Optional[NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], ]] = Field(None)
# Update forward refs
# see https://pydantic-docs.helpmanual.io/usage/postponed_annotations/
EnumData.update_forward_refs()