mirror of https://github.com/doccano/doccano.git
pythondatasetsactive-learningtext-annotationdatasetnatural-language-processingdata-labelingmachine-learningannotation-tool
61 lines
1.6 KiB
61 lines
1.6 KiB
import abc
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from typing import Any, Dict
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from pydantic import UUID4, BaseModel, validator
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from examples.models import Example
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from projects.models import Project
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class BaseData(BaseModel, abc.ABC):
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filename: str
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upload_name: str
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uuid: UUID4
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meta: Dict[Any, Any] = {}
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def __init__(self, **data):
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super().__init__(**data)
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@classmethod
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def parse(cls, example_uuid: UUID4, filename: str, upload_name: str, text: str = "", **kwargs):
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return cls(uuid=example_uuid, filename=filename, upload_name=upload_name, text=text, meta=kwargs)
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def __hash__(self):
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return hash(tuple(self.dict()))
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@abc.abstractmethod
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def create(self, project: Project) -> Example:
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raise NotImplementedError("Please implement this method in the subclass.")
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class TextData(BaseData):
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text: str
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@validator("text")
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def text_is_not_empty(cls, value: str):
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if value:
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return value
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else:
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raise ValueError("The empty text is not allowed.")
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def create(self, project: Project) -> Example:
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return Example(
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uuid=self.uuid,
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project=project,
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filename=self.filename,
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upload_name=self.upload_name,
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text=self.text,
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meta=self.meta,
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)
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class BinaryData(BaseData):
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def create(self, project: Project) -> Example:
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return Example(
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uuid=self.uuid,
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project=project,
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filename=self.filename,
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upload_name=self.upload_name,
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text=None,
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meta=self.meta,
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)
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