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pythondatasetsactive-learningtext-annotationdatasetnatural-language-processingdata-labelingmachine-learningannotation-tool
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55 lines
2.1 KiB
55 lines
2.1 KiB
import abc
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from rest_framework import status
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from rest_framework.permissions import IsAuthenticated
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from rest_framework.response import Response
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from rest_framework.views import APIView
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from api.models import Example, ExampleState
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from label_types.models import LabelType, CategoryType, SpanType
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from labels.models import Label, Category, Span
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from members.models import Member
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from members.permissions import IsInProjectReadOnlyOrAdmin
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class ProgressAPI(APIView):
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permission_classes = [IsAuthenticated & IsInProjectReadOnlyOrAdmin]
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def get(self, request, *args, **kwargs):
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examples = Example.objects.filter(project=self.kwargs['project_id']).values('id')
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total = examples.count()
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done = ExampleState.objects.count_done(examples, user=self.request.user)
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return {'total': total, 'remaining': total - done}
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class MemberProgressAPI(APIView):
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permission_classes = [IsAuthenticated & IsInProjectReadOnlyOrAdmin]
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def get(self, request, *args, **kwargs):
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examples = Example.objects.filter(project=self.kwargs['project_id']).values('id')
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members = Member.objects.filter(project=self.kwargs['project_id'])
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data = ExampleState.objects.measure_member_progress(examples, members)
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return Response(data=data, status=status.HTTP_200_OK)
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class LabelDistribution(abc.ABC, APIView):
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permission_classes = [IsAuthenticated & IsInProjectReadOnlyOrAdmin]
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model = Label
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label_type = LabelType
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def get(self, request, *args, **kwargs):
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labels = self.label_type.objects.filter(project=self.kwargs['project_id'])
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examples = Example.objects.filter(project=self.kwargs['project_id']).values('id')
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members = Member.objects.filter(project=self.kwargs['project_id'])
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data = self.model.objects.calc_label_distribution(examples, members, labels)
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return Response(data=data, status=status.HTTP_200_OK)
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class CategoryTypeDistribution(LabelDistribution):
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model = Category
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label_type = CategoryType
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class SpanTypeDistribution(LabelDistribution):
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model = Span
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label_type = SpanType
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