diff options
Diffstat (limited to 'askbot/models/badges.py')
| -rw-r--r-- | askbot/models/badges.py | 25 |
1 files changed, 14 insertions, 11 deletions
diff --git a/askbot/models/badges.py b/askbot/models/badges.py index 5e56b499..61149df3 100644 --- a/askbot/models/badges.py +++ b/askbot/models/badges.py @@ -24,8 +24,8 @@ from django.utils.translation import ugettext as _ from django.dispatch import Signal from askbot.models.repute import BadgeData, Award from askbot.models.user import Activity -from askbot.models.meta import Comment from askbot.models.question import FavoriteQuestion as Fave#name collision +from askbot.models.post import Post from askbot import const from askbot.conf import settings as askbot_settings from askbot.utils.decorators import auto_now_timestamp @@ -265,7 +265,7 @@ class SelfLearner(Badge): return False min_upvotes = askbot_settings.SELF_LEARNER_BADGE_MIN_UPVOTES - question = context_object.question + question = context_object.thread._question_post() answer = context_object if question.author == answer.author and answer.score >= min_upvotes: @@ -404,7 +404,7 @@ class FrequentedQuestion(Badge): context_object = None, timestamp = None): if context_object.post_type != 'question': return False - if context_object.view_count >= self.min_views: + if context_object.thread.view_count >= self.min_views: return self.award(context_object.author, context_object, timestamp) return False @@ -461,7 +461,7 @@ class Scholar(Badge): if context_object.post_type != 'answer': return False answer = context_object - if answer.question.author != actor: + if answer.thread._question_post().author != actor: return False return self.award(actor, context_object, timestamp) @@ -485,7 +485,7 @@ class VotedAcceptedAnswer(Badge): if context_object.post_type != 'answer': return None answer = context_object - if answer.score >= self.min_votes and answer.accepted: + if answer.score >= self.min_votes and answer.accepted(): return self.award(answer.author, answer, timestamp) class Enlightened(VotedAcceptedAnswer): @@ -533,7 +533,7 @@ class Necromancer(Badge): if context_object.post_type != 'answer': return False answer = context_object - question = answer.question + question = answer.thread._question_post() delta = datetime.timedelta(askbot_settings.NECROMANCER_BADGE_MIN_DELAY) min_score = askbot_settings.NECROMANCER_BADGE_MIN_UPVOTES if answer.added_at - question.added_at >= delta \ @@ -674,7 +674,7 @@ class FavoriteTypeBadge(Badge): question = context_object #model FavoriteQuestion imported under alias of Fave count = Fave.objects.filter( - question = question + thread = question.thread ).exclude( user = question.author ).count() @@ -739,7 +739,7 @@ class Commentator(Badge): def consider_award(self, actor = None, context_object = None, timestamp = None): - num_comments = Comment.objects.filter(user = actor).count() + num_comments = Post.objects.get_comments().filter(author=actor).count() if num_comments >= askbot_settings.COMMENTATOR_BADGE_MIN_COMMENTS: return self.award(actor, context_object, timestamp) return False @@ -762,9 +762,7 @@ class Taxonomist(Badge): tag = context_object taxonomist_threshold = askbot_settings.TAXONOMIST_BADGE_MIN_USE_COUNT - #the "-1" is used because tag counts are updated in a bulk query - #that does not update the value in the python object - if tag.used_count == taxonomist_threshold - 1: + if tag.used_count == taxonomist_threshold: return self.award(tag.created_by, tag, timestamp) return False @@ -880,6 +878,11 @@ def init_badges(): #from the __init__ function? for key in BADGES.keys(): get_badge(key).get_stored_data() + #remove any badges from the database + #that are no longer in the BADGES dictionary + BadgeData.objects.exclude( + slug__in = map(slugify, BADGES.keys()) + ).delete() award_badges_signal = Signal( providing_args=[ |