mirror of
https://github.com/p2p-ld/nwb-linkml.git
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sneakers-the-rat
be21325123
- 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
41 lines
1.6 KiB
Python
41 lines
1.6 KiB
Python
from __future__ import annotations
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from datetime import datetime, date
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from enum import Enum
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from typing import List, Dict, Optional, Any, Union
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from pydantic import BaseModel as BaseModel, Field
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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
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import sys
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if sys.version_info >= (3, 8):
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from typing import Literal
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else:
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from typing_extensions import Literal
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metamodel_version = "None"
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version = "None"
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class WeakRefShimBaseModel(BaseModel):
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__slots__ = '__weakref__'
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class ConfiguredBaseModel(WeakRefShimBaseModel,
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validate_assignment = True,
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validate_all = True,
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underscore_attrs_are_private = True,
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extra = 'forbid',
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arbitrary_types_allowed = True,
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use_enum_values = True):
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pass
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class Arraylike(ConfiguredBaseModel):
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"""
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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.
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"""
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None
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# Update forward refs
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# see https://pydantic-docs.helpmanual.io/usage/postponed_annotations/
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Arraylike.update_forward_refs()
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