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pythonannotation-tooldatasetsactive-learningtext-annotationdatasetnatural-language-processingdata-labelingmachine-learning
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42 lines
1.1 KiB
42 lines
1.1 KiB
import abc
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import uuid
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from typing import Any, Dict
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from pydantic import BaseModel, validator
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from projects.models import Project
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from examples.models import Example
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class BaseData(BaseModel, abc.ABC):
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filename: str
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@classmethod
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def parse(cls, **kwargs):
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return cls.parse_obj(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, meta: Dict[Any, Any]) -> 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("is not empty.")
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def create(self, project: Project, meta: Dict[Any, Any]) -> Example:
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return Example(uuid=uuid.uuid4(), project=project, filename=self.filename, text=self.text, meta=meta)
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class FileData(BaseData):
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def create(self, project: Project, meta: Dict[Any, Any]) -> Example:
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return Example(uuid=uuid.uuid4(), project=project, filename=self.filename, meta=meta)
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