nwb-linkml/nwb_linkml/models/nwb_language.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

41 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
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 Arraylike(ConfiguredBaseModel):
"""
Container for arraylike information held in the dims, shape, and dtype properties.this is a special case to be interpreted by downstream i/o. this class has no slotsand is abstract by default.- Each slot within a subclass indicates a possible dimension.- Only dimensions that are present in all the dimension specifiers in the original schema are required.- Shape requirements are indicated using max/min cardinalities on the slot.
"""
None
# Update forward refs
# see https://pydantic-docs.helpmanual.io/usage/postponed_annotations/
Arraylike.update_forward_refs()