258 lines
8.2 KiB
Python
258 lines
8.2 KiB
Python
from collections import defaultdict
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from math import e
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import os, zipfile
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from datetime import datetime
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import random
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from django.conf import settings
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from django.core.cache import cache
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from django.db.models import Case, Count, ExpressionWrapper, F, Max, Q, When
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from django.db.models.fields import FloatField
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from django.utils import timezone
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from django.utils.translation import gettext as _, gettext_noop
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from judge.models import Problem, Submission
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from judge.ml.collab_filter import CollabFilter
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__all__ = [
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"contest_completed_ids",
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"get_result_data",
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"user_completed_ids",
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"user_authored_ids",
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"user_editable_ids",
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]
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def user_authored_ids(profile):
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result = set(Problem.objects.filter(authors=profile).values_list("id", flat=True))
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return result
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def user_editable_ids(profile):
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result = set(
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(
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Problem.objects.filter(authors=profile)
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| Problem.objects.filter(curators=profile)
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).values_list("id", flat=True)
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)
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return result
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def contest_completed_ids(participation):
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key = "contest_complete:%d" % participation.id
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result = cache.get(key)
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if result is None:
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result = set(
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participation.submissions.filter(
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submission__result="AC", points=F("problem__points")
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)
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.values_list("problem__problem__id", flat=True)
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.distinct()
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)
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cache.set(key, result, 86400)
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return result
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def user_completed_ids(profile):
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key = "user_complete:%d" % profile.id
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result = cache.get(key)
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if result is None:
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result = set(
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Submission.objects.filter(
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user=profile, result="AC", points=F("problem__points")
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)
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.values_list("problem_id", flat=True)
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.distinct()
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)
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cache.set(key, result, 86400)
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return result
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def contest_attempted_ids(participation):
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key = "contest_attempted:%s" % participation.id
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result = cache.get(key)
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if result is None:
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result = {
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id: {"achieved_points": points, "max_points": max_points}
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for id, max_points, points in (
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participation.submissions.values_list(
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"problem__problem__id", "problem__points"
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)
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.annotate(points=Max("points"))
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.filter(points__lt=F("problem__points"))
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)
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}
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cache.set(key, result, 86400)
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return result
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def user_attempted_ids(profile):
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key = "user_attempted:%s" % profile.id
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result = cache.get(key)
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if result is None:
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result = {
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id: {
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"achieved_points": points,
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"max_points": max_points,
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"last_submission": last_submission,
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"code": problem_code,
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"name": problem_name,
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}
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for id, max_points, problem_code, problem_name, points, last_submission in (
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Submission.objects.filter(user=profile)
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.values_list(
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"problem__id", "problem__points", "problem__code", "problem__name"
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)
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.annotate(points=Max("points"), last_submission=Max("id"))
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.filter(points__lt=F("problem__points"))
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)
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}
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cache.set(key, result, 86400)
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return result
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def _get_result_data(results):
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return {
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"categories": [
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# Using gettext_noop here since this will be tacked into the cache, so it must be language neutral.
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# The caller, SubmissionList.get_result_data will run ugettext on the name.
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{"code": "AC", "name": gettext_noop("Accepted"), "count": results["AC"]},
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{"code": "WA", "name": gettext_noop("Wrong"), "count": results["WA"]},
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{
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"code": "CE",
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"name": gettext_noop("Compile Error"),
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"count": results["CE"],
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},
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{"code": "TLE", "name": gettext_noop("Timeout"), "count": results["TLE"]},
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{
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"code": "ERR",
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"name": gettext_noop("Error"),
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"count": results["MLE"]
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+ results["OLE"]
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+ results["IR"]
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+ results["RTE"]
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+ results["AB"]
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+ results["IE"],
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},
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],
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"total": sum(results.values()),
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}
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def get_result_data(*args, **kwargs):
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if args:
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submissions = args[0]
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if kwargs:
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raise ValueError(_("Can't pass both queryset and keyword filters"))
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else:
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submissions = (
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Submission.objects.filter(**kwargs)
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if kwargs is not None
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else Submission.objects
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)
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raw = (
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submissions.values("result")
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.annotate(count=Count("result"))
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.values_list("result", "count")
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)
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return _get_result_data(defaultdict(int, raw))
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def editable_problems(user, profile=None):
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subquery = Problem.objects.all()
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if profile is None:
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profile = user.profile
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if not user.has_perm("judge.edit_all_problem"):
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subfilter = Q(authors__id=profile.id) | Q(curators__id=profile.id)
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if user.has_perm("judge.edit_public_problem"):
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subfilter |= Q(is_public=True)
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subquery = subquery.filter(subfilter)
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return subquery
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def hot_problems(duration, limit):
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cache_key = "hot_problems:%d:%d" % (duration.total_seconds(), limit)
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qs = cache.get(cache_key)
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if qs is None:
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qs = Problem.get_public_problems().filter(
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submission__date__gt=timezone.now() - duration
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)
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qs0 = (
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qs.annotate(k=Count("submission__user", distinct=True))
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.order_by("-k")
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.values_list("k", flat=True)
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)
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if not qs0:
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return []
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# make this an aggregate
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mx = float(qs0[0])
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qs = qs.annotate(unique_user_count=Count("submission__user", distinct=True))
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# fix braindamage in excluding CE
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qs = qs.annotate(
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submission_volume=Count(
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Case(
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When(submission__result="AC", then=1),
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When(submission__result="WA", then=1),
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When(submission__result="IR", then=1),
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When(submission__result="RTE", then=1),
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When(submission__result="TLE", then=1),
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When(submission__result="OLE", then=1),
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output_field=FloatField(),
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)
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)
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)
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qs = qs.annotate(
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ac_volume=Count(
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Case(
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When(submission__result="AC", then=1),
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output_field=FloatField(),
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)
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)
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)
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qs = qs.filter(unique_user_count__gt=max(mx / 3.0, 1))
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qs = (
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qs.annotate(
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ordering=ExpressionWrapper(
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0.02
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* F("points")
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* (
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0.4 * F("ac_volume") / F("submission_volume")
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+ 0.6 * F("ac_rate")
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)
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+ 100 * e ** (F("unique_user_count") / mx),
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output_field=FloatField(),
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)
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)
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.order_by("-ordering")
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.defer("description")[:limit]
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)
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cache.set(cache_key, qs, 900)
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return qs
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def get_related_problems(profile, problem, limit=8):
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if not profile or not settings.ML_OUTPUT_PATH:
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return None
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cache_key = "related_problems:%d:%d" % (profile.id, problem.id)
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qs = cache.get(cache_key)
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if qs is not None:
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return qs
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problemset = Problem.get_visible_problems(profile.user).values_list("id", flat=True)
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problemset = problemset.exclude(id__in=user_completed_ids(profile))
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problemset = problemset.exclude(id=problem.id)
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cf_model = CollabFilter("collab_filter")
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results = cf_model.problem_neighbors(
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problem, problemset, CollabFilter.DOT, limit
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) + cf_model.problem_neighbors(problem, problemset, CollabFilter.COSINE, limit)
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results = list(set([i[1] for i in results]))
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seed = datetime.now().strftime("%d%m%Y")
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random.Random(seed).shuffle(results)
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results = results[:limit]
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results = [Problem.objects.get(id=i) for i in results]
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cache.set(cache_key, results, 21600)
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return results
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