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pythondatasetsactive-learningtext-annotationdatasetnatural-language-processingdata-labelingmachine-learningannotation-tool
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32 lines
1.4 KiB
32 lines
1.4 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 = (
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self.filter(example_id__in=examples).values("confirmed_by__username").annotate(total=Count("confirmed_by"))
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)
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response = {
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"total": examples.count(),
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"progress": [{"user": obj["confirmed_by__username"], "done": obj["total"]} for obj in done_count],
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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({"user": member.username, "done": 0})
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return response
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