def get_context_data(self, **kwargs):
context = super(UserAboutPage, self).get_context_data(**kwargs)
ratings = context['ratings'] = self.object.ratings.order_by('-contest__end_time').select_related('contest') \
.defer('contest__description')
context['rating_data'] = mark_safe(json.dumps([{
'label': rating.contest.name,
'rating': rating.rating,
'ranking': rating.rank,
'link': reverse('contest_ranking', args=(rating.contest.key,)),
'timestamp': (rating.contest.end_time - EPOCH).total_seconds() * 1000,
'date': date_format(rating.contest.end_time, _('M j, Y, G:i')),
'class': rating_class(rating.rating),
'height': '%.3fem' % rating_progress(rating.rating)
} for rating in ratings]))
if ratings:
user_data = self.object.ratings.aggregate(Min('rating'), Max('rating'))
global_data = Rating.objects.aggregate(Min('rating'), Max('rating'))
min_ever, max_ever = global_data['rating__min'], global_data['rating__max']
min_user, max_user = user_data['rating__min'], user_data['rating__max']
delta = max_user - min_user
ratio = (max_ever - max_user) / (max_ever - min_ever) if max_ever != min_ever else 1.0
context['max_graph'] = max_user + ratio * delta
context['min_graph'] = min_user + ratio * delta - delta
return context
def get_context_data(self, **kwargs):
context = super(UserAboutPage, self).get_context_data(**kwargs)
ratings = context['ratings'] = self.object.ratings.order_by('-contest__end_time').select_related('contest') \
.defer('contest__description')
context['rating_data'] = mark_safe(json.dumps([{
'label': rating.contest.name,
'rating': rating.rating,
'ranking': rating.rank,
'link': reverse('contest_ranking', args=(rating.contest.key,)),
'timestamp': (rating.contest.end_time - EPOCH).total_seconds() * 1000,
'date': date_format(rating.contest.end_time, _('M j, Y, G:i')),
'class': rating_class(rating.rating),
'height': '%.3fem' % rating_progress(rating.rating)
} for rating in ratings]))
if ratings:
user_data = self.object.ratings.aggregate(Min('rating'), Max('rating'))
global_data = Rating.objects.aggregate(Min('rating'), Max('rating'))
min_ever, max_ever = global_data['rating__min'], global_data['rating__max']
min_user, max_user = user_data['rating__min'], user_data['rating__max']
delta = max_user - min_user
ratio = (max_ever - max_user + 0.0) / (max_ever - min_ever)
context['max_graph'] = max_user + ratio * delta
context['min_graph'] = min_user + ratio * delta - delta
return context
def get_context_data(self, **kwargs):
context = super(UserAboutPage, self).get_context_data(**kwargs)
ratings = context['ratings'] = self.object.ratings.order_by('-contest__end_time').select_related('contest') \
.defer('contest__description')
context['rating_data'] = mark_safe(
json.dumps([{
'label':
rating.contest.name,
'rating':
rating.rating,
'ranking':
rating.rank,
'link':
reverse('contest_ranking', args=(rating.contest.key, )),
'timestamp':
(rating.contest.end_time - EPOCH).total_seconds() * 1000,
'date':
date_format(rating.contest.end_time, _('M j, Y, G:i')),
'class':
rating_class(rating.rating),
'height':
'%.3fem' % rating_progress(rating.rating),
} for rating in ratings]))
context['awards'] = self.get_awards(ratings)
if ratings:
user_data = self.object.ratings.aggregate(Min('rating'),
Max('rating'))
global_data = Rating.objects.aggregate(Min('rating'),
Max('rating'))
min_ever, max_ever = global_data['rating__min'], global_data[
'rating__max']
min_user, max_user = user_data['rating__min'], user_data[
'rating__max']
delta = max_user - min_user
ratio = (max_ever - max_user) / (
max_ever - min_ever) if max_ever != min_ever else 1.0
context['max_graph'] = max_user + ratio * delta
context['min_graph'] = min_user + ratio * delta - delta
submissions = (self.object.submission_set.annotate(
date_only=Cast('date', DateField())).values('date_only').annotate(
cnt=Count('id')))
context['submission_data'] = mark_safe(
json.dumps({
date_counts['date_only'].isoformat(): date_counts['cnt']
for date_counts in submissions
}))
context['submission_metadata'] = mark_safe(
json.dumps({
'min_year': (self.object.submission_set.annotate(
year_only=ExtractYear('date')).aggregate(
min_year=Min('year_only'))['min_year']),
}))
return context
def get_user_css_class(cls,
display_rank,
rating,
rating_colors=settings.DMOJ_RATING_COLORS):
if rating_colors:
return 'rating %s %s' % (rating_class(rating) if rating is not None
else 'rate-none', display_rank)
return display_rank
def get_user_rating(username, rating):
element = Element('a', {
'class': 'rate-group',
'href': reverse('user_page', args=[username])
})
if rating:
rating_css = rating_class(rating)
rate_box = Element('span', {'class': 'rate-box ' + rating_css})
rate_box.append(
Element('span',
{'style': 'height: %3.fem' % rating_progress(rating)}))
user = Element('span', {'class': 'rating ' + rating_css})
user.text = username
element.append(rate_box)
element.append(user)
else:
element.text = username
return element
def get_user_rating(username, data):
if not data:
element = Element('span')
element.text = username
return element
rating = data[1]
element = Element('a', {'class': 'rate-group', 'href': reverse('user_page', args=[username])})
if rating:
rating_css = rating_class(rating)
rate_box = Element('span', {'class': 'rate-box ' + rating_css})
rate_box.append(Element('span', {'style': 'height: %3.fem' % rating_progress(rating)}))
user = Element('span', {'class': 'rating ' + rating_css})
user.text = username
element.append(rate_box)
element.append(user)
else:
element.text = username
return element
def get_user_css_class(cls, display_rank, rating, rating_colors=getattr(settings, 'DMOJ_RATING_COLORS', False)):
if rating_colors:
return 'rating %s %s' % (rating_class(rating) if rating is not None else 'rate-none', display_rank)
return display_rank
def get_class(rating):
return 'rate-none' if rating is None else rating_class(int(rating))
def get_class(rating):
return rating_class(int(rating)) if rating else 'rate-none'
