mirror of
https://github.com/p2p-ld/nwb-linkml.git
synced 2024-09-19 23:44:28 +00:00
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
122 lines
4.3 KiB
Python
122 lines
4.3 KiB
Python
"""
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Base class for adapters
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"""
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from abc import abstractmethod
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import warnings
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from dataclasses import dataclass, field
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from typing import List, Dict, Type, Generator, Any, Tuple, Optional, TypeVar, TypeVarTuple, Unpack
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from pydantic import BaseModel, Field, validator
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from linkml_runtime.linkml_model import Element, SchemaDefinition, ClassDefinition, SlotDefinition, TypeDefinition
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# SchemaDefClass = dataclass(SchemaDefinition).__pydantic_model__
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@dataclass
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class BuildResult:
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# pass
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schemas: List[SchemaDefinition] = field(default_factory=list)
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classes: List[ClassDefinition] = field(default_factory=list)
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slots: List[SlotDefinition] = field(default_factory=list)
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types: List[TypeDefinition] = field(default_factory=list)
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def __post_init__(self):
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for field in ('schemas', 'classes', 'slots', 'types'):
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attr = getattr(self, field)
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if not isinstance(attr, list):
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setattr(self, field, [attr])
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def _dedupe(self, ours, others):
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existing_names = [c.name for c in ours]
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others_dedupe = [o for o in others if o.name not in existing_names]
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return others_dedupe
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def __add__(self, other:'BuildResult') -> 'BuildResult':
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# if not isinstance(other, 'BuildResult'):
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# raise TypeError('Can only add two build results together')
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self.schemas.extend(self._dedupe(self.schemas, other.schemas))
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self.classes.extend(self._dedupe(self.classes, other.classes))
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# existing_names = [c.name for c in self.classes]
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# for newc in other.classes:
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# if newc.name in existing_names:
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# warnings.warn(f'Not creating duplicate class for {newc.name}')
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# continue
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# self.classes.append(newc)
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# self.classes.extend(other.classes)
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self.slots.extend(other.slots)
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self.types.extend(other.types)
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return self
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T = TypeVar
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Ts = TypeVarTuple('Ts')
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class Adapter(BaseModel):
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@abstractmethod
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def build(self) -> 'BuildResult':
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"""
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Generate the corresponding linkML element for this adapter
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"""
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def walk(self, input: BaseModel | list | dict):
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yield input
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if isinstance(input, BaseModel):
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for key in input.__fields__.keys():
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val = getattr(input, key)
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yield (key, val)
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if isinstance(val, (BaseModel, dict, list)):
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yield from self.walk(val)
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elif isinstance(input, dict):
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for key, val in input.items():
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yield (key, val)
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if isinstance(val, (BaseModel, dict, list)):
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yield from self.walk(val)
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elif isinstance(input, (list, tuple)):
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yield input
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for val in input:
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yield from self.walk(val)
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else:
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# do nothing, is a string or whatever
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pass
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def walk_fields(self, input: BaseModel | list | dict, field: str | Tuple[str, ...]):
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if isinstance(field, str):
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field = (field,)
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for item in self.walk(input):
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if isinstance(item, tuple) and item[0] in field and item[1] is not None:
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yield item[1]
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def walk_types(self, input: BaseModel | list | dict, get_type: T | List[Unpack[Ts]] | Tuple[Unpack[T]]) -> Generator[T, None, None]:
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if not isinstance(get_type, (list, tuple)):
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get_type = [get_type]
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for item in self.walk(input):
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if any([type(item) == atype for atype in get_type]):
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yield item
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#
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#
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# if isinstance(input, BaseModel):
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# for key in input.__fields__.keys():
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# val = getattr(input, key)
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# if key == field:
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# yield val
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# if isinstance(val, (BaseModel, dict, list)):
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# yield from self.walk(val, field)
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#
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# elif isinstance(input, dict):
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# for key, val in input.items():
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# if key == field:
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# yield val
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# if isinstance(val, (BaseModel, dict, list)):
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# yield from self.walk(val, field)
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#
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# elif isinstance(input, (list, tuple)):
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# for val in input:
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# yield from self.walk(val, field)
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#
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# else:
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# # do nothing, is a string or whatever
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# pass
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