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pythonannotation-tooldatasetsactive-learningtext-annotationdatasetnatural-language-processingdata-labelingmachine-learning
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42 lines
1.5 KiB
42 lines
1.5 KiB
from django.db.models import Count, Manager
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class ExampleManager(Manager):
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def bulk_create(self, objs, batch_size=None, ignore_conflicts=False):
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super().bulk_create(objs, batch_size=batch_size, ignore_conflicts=ignore_conflicts)
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uuids = [data.uuid for data in objs]
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examples = self.in_bulk(uuids, field_name='uuid')
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return [examples[uid] for uid in uuids]
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class ExampleStateManager(Manager):
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def count_done(self, examples, user=None):
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if user:
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queryset = self.filter(example_id__in=examples, confirmed_by=user)
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else:
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queryset = self.filter(example_id__in=examples)
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return queryset.distinct().values('example').count()
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def measure_member_progress(self, examples, members):
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done_count = self.filter(example_id__in=examples)\
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.values('confirmed_by__username')\
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.annotate(total=Count('confirmed_by'))
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response = {
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'total': examples.count(),
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'progress': [
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{
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'user': obj['confirmed_by__username'],
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'done': obj['total']
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} for obj in done_count
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]
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}
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members_with_progress = {o['confirmed_by__username'] for o in done_count}
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for member in members:
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if member.username not in members_with_progress:
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response['progress'].append({
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'user': member.username,
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'done': 0
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})
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return response
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