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Link to books
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d690224559
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2 changed files with 11 additions and 11 deletions
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@ -29,8 +29,8 @@
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</a>
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</div>
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<div class="media-content">
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{% blocktrans trimmed with title=top_rated|book_title site_name=site.name rating=top_rated.rating|floatformat:1 %}
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<em>{{ title }}</em> is {{ site_name }}'s most beloved book, with an average rating of {{ rating }} out of 5.
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{% blocktrans trimmed with title=top_rated|book_title book_path=book.local_path site_name=site.name rating=top_rated.rating|floatformat:1 %}
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<a href="{{ book_path }}"><em>{{ title }}</em></a> is {{ site_name }}'s most beloved book, with an average rating of {{ rating }} out of 5.
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{% endblocktrans %}
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</div>
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</div>
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@ -43,8 +43,8 @@
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</a>
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</div>
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<div class="media-content">
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{% blocktrans trimmed with title=wanted|book_title site_name=site.name %}
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More {{ site_name }} users want to read <em>{{ title }}</em>.
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{% blocktrans trimmed with title=wanted|book_title book_path=book.local_path site_name=site.name %}
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More {{ site_name }} users want to read <a href="{{ book_path }}"><em>{{ title }}</em></a>.
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{% endblocktrans %}
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</div>
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</div>
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@ -57,8 +57,8 @@
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</a>
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</div>
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<div class="media-content">
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{% blocktrans trimmed with title=controversial|book_title site_name=site.name %}
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<em>{{ title }}</em> has the most divisive ratings of any book on {{ site_name }}.
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{% blocktrans trimmed with title=controversial|book_title book_path=book.local_path site_name=site.name %}
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<a href="{{ book_path }}"><em>{{ title }}</em></a> has the most divisive ratings of any book on {{ site_name }}.
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{% endblocktrans %}
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</div>
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</div>
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@ -29,17 +29,17 @@ def about(request):
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books = models.Edition.objects.exclude(cover__exact="")
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total_ratings = models.Review.objects.filter(user__local=True).count()
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total_ratings = models.Review.objects.filter(user__local=True, deleted=False).count()
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data["top_rated"] = books.annotate(
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rating=Avg("review__rating", filter=Q(review__user__local=True)),
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rating_count=Count("review__rating", filter=Q(review__user__local=True)),
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rating=Avg("review__rating", filter=Q(review__user__local=True, review__deleted=False)),
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rating_count=Count("review__rating", filter=Q(review__user__local=True, review__deleted=False)),
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).annotate(
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weighted=F("rating") * F("rating_count") / total_ratings
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).filter(weighted__gt=0).order_by("-weighted").first()
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data["controversial"] = books.annotate(
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deviation=StdDev("review__rating", filter=Q(review__user__local=True)),
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rating_count=Count("review__rating", filter=Q(review__user__local=True)),
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deviation=StdDev("review__rating", filter=Q(review__user__local=True, review__deleted=False)),
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rating_count=Count("review__rating", filter=Q(review__user__local=True, review__deleted=False)),
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).annotate(
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weighted=F("deviation") * F("rating_count") / total_ratings
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).filter(weighted__gt=0).order_by("-weighted").first()
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