Python utilities.localtime_for_timezone函数代码示例

def load_starred_stories(request):
    user = get_user(request)
    offset = int(request.REQUEST.get('offset', 0))
    limit = int(request.REQUEST.get('limit', 10))
    page = int(request.REQUEST.get('page', 0))
    if page: offset = limit * (page - 1)
        
    mstories = MStarredStory.objects(user_id=user.pk).order_by('-starred_date')[offset:offset+limit]
    stories = Feed.format_stories(mstories)
    
    for story in stories:
        story_date = localtime_for_timezone(story['story_date'], user.profile.timezone)
        now = localtime_for_timezone(datetime.datetime.now(), user.profile.timezone)
        story['short_parsed_date'] = format_story_link_date__short(story_date, now)
        story['long_parsed_date'] = format_story_link_date__long(story_date, now)
        starred_date = localtime_for_timezone(story['starred_date'], user.profile.timezone)
        story['starred_date'] = format_story_link_date__long(starred_date, now)
        story['read_status'] = 1
        story['starred'] = True
        story['intelligence'] = {
            'feed': 0,
            'author': 0,
            'tags': 0,
            'title': 0,
        }
    
    logging.user(request, "~FCLoading starred stories: ~SB%s stories" % (len(stories)))
    
    return dict(stories=stories)

 def test_localtime_for_timezone(self):
     self.assertEqual(
         localtime_for_timezone(
             datetime(2008, 6, 25, 18, 0, 0), "America/Denver"
         ).strftime("%m/%d/%Y %H:%M:%S"),
         "06/25/2008 12:00:00"
     )

def load_features(request):
    user = get_user(request)
    page = int(request.REQUEST.get('page', 0))
    logging.user(request, "~FBBrowse features: ~SBPage #%s" % (page+1))
    features = Feature.objects.all()[page*3:(page+1)*3+1].values()
    features = [{
        'description': f['description'], 
        'date': localtime_for_timezone(f['date'], user.profile.timezone).strftime("%b %d, %Y")
    } for f in features]
    return features

def localtime(value, timezone):
    return localtime_for_timezone(value, timezone)

def localdatetime(context, date, date_format):
    user = get_user(context['user'])
    date = localtime_for_timezone(date, user.profile.timezone).strftime(date_format)
    return date

#.........这里部分代码省略.........
    feed_ids = [f[0] for f in feed_counts]
    feed_last_reads = dict([(str(feed_id), feed_last_reads[feed_id]) for feed_id in feed_ids
                            if feed_id in feed_last_reads])
    feed_counts = dict(feed_counts)

    # After excluding read stories, all that's left are stories 
    # past the mark_read_date. Everything returned is guaranteed to be unread.
    mstories = MStory.objects(
        story_guid__nin=read_stories,
        story_feed_id__in=feed_ids,
        # story_date__gte=start - bottom_delta
    ).map_reduce("""function() {
            var d = feed_last_reads[this[~story_feed_id]];
            if (this[~story_date].getTime()/1000 > d) {
                emit(this[~id], this);
            }
        }""",
        """function(key, values) {
            return values[0];
        }""",
        output='inline',
        scope={
            'feed_last_reads': feed_last_reads
        }
    )
    mstories = [story.value for story in mstories if story and story.value]

    mstories = sorted(mstories, cmp=lambda x, y: cmp(story_score(y, bottom_delta), story_score(x, bottom_delta)))

    # story_feed_counts = defaultdict(int)
    # mstories_pruned = []
    # for story in mstories:
    #     print story['story_title'], story_feed_counts[story['story_feed_id']]
    #     if story_feed_counts[story['story_feed_id']] >= 3: continue
    #     mstories_pruned.append(story)
    #     story_feed_counts[story['story_feed_id']] += 1
    stories = []
    for i, story in enumerate(mstories):
        if i < offset: continue
        if i >= offset + limit: break
        stories.append(bunch(story))
    stories = Feed.format_stories(stories)
    found_feed_ids = list(set([story['story_feed_id'] for story in stories]))
    
    # Find starred stories
    starred_stories = MStarredStory.objects(
        user_id=user.pk,
        story_feed_id__in=found_feed_ids
    ).only('story_guid', 'starred_date')
    starred_stories = dict([(story.story_guid, story.starred_date) 
                            for story in starred_stories])
    
    # Intelligence classifiers for all feeds involved
    def sort_by_feed(classifiers):
        feed_classifiers = defaultdict(list)
        for classifier in classifiers:
            feed_classifiers[classifier.feed_id].append(classifier)
        return feed_classifiers
    classifier_feeds   = sort_by_feed(MClassifierFeed.objects(user_id=user.pk, feed_id__in=found_feed_ids))
    classifier_authors = sort_by_feed(MClassifierAuthor.objects(user_id=user.pk, feed_id__in=found_feed_ids))
    classifier_titles  = sort_by_feed(MClassifierTitle.objects(user_id=user.pk, feed_id__in=found_feed_ids))
    classifier_tags    = sort_by_feed(MClassifierTag.objects(user_id=user.pk, feed_id__in=found_feed_ids))
    
    classifiers = {}
    for feed_id in found_feed_ids:
        classifiers[feed_id] = get_classifiers_for_user(user, feed_id, classifier_feeds[feed_id], 
                                                        classifier_authors[feed_id],
                                                        classifier_titles[feed_id],
                                                        classifier_tags[feed_id])
    
    # Just need to format stories
    for story in stories:
        story_date = localtime_for_timezone(story['story_date'], user.profile.timezone)
        now = localtime_for_timezone(datetime.datetime.now(), user.profile.timezone)
        story['short_parsed_date'] = format_story_link_date__short(story_date, now)
        story['long_parsed_date']  = format_story_link_date__long(story_date, now)
        story['read_status'] = 0
        if story['id'] in starred_stories:
            story['starred'] = True
            starred_date = localtime_for_timezone(starred_stories[story['id']], user.profile.timezone)
            story['starred_date'] = format_story_link_date__long(starred_date, now)
        story['intelligence'] = {
            'feed':   apply_classifier_feeds(classifier_feeds[story['story_feed_id']], story['story_feed_id']),
            'author': apply_classifier_authors(classifier_authors[story['story_feed_id']], story),
            'tags':   apply_classifier_tags(classifier_tags[story['story_feed_id']], story),
            'title':  apply_classifier_titles(classifier_titles[story['story_feed_id']], story),
        }
    
    diff = datetime.datetime.utcnow() - start
    timediff = float("%s.%.2s" % (diff.seconds, (diff.microseconds / 1000)))
    logging.user(request, "~FCLoading river stories: page %s - ~SB%s/%s "
                               "stories ~SN(%s/%s/%s feeds) ~FB(%s seconds)" % 
                               (page, len(stories), len(mstories), len(found_feed_ids), 
                               len(feed_ids), len(original_feed_ids), timediff))
    
    if new_flag:
        return dict(stories=stories, classifiers=classifiers)
    else:
        logging.user(request, "~BR~FCNo new flag on river")
        return dict(stories=stories)

def load_single_feed(request, feed_id):
    start        = time.time()
    user         = get_user(request)
    offset       = int(request.REQUEST.get('offset', 0))
    limit        = int(request.REQUEST.get('limit', 12))
    page         = int(request.REQUEST.get('page', 1))
    dupe_feed_id = None
    userstories_db = None
    
    if page: offset = limit * (page-1)
    if not feed_id: raise Http404
        
    try:
        feed = Feed.objects.get(id=feed_id)
    except Feed.DoesNotExist:
        feed_address = request.REQUEST.get('feed_address')
        dupe_feed = DuplicateFeed.objects.filter(duplicate_address=feed_address)
        if dupe_feed:
            feed = dupe_feed[0].feed
            dupe_feed_id = feed_id
        else:
            raise Http404
        
    stories = feed.get_stories(offset, limit) 
        
    # Get intelligence classifier for user
    classifier_feeds   = list(MClassifierFeed.objects(user_id=user.pk, feed_id=feed_id))
    classifier_authors = list(MClassifierAuthor.objects(user_id=user.pk, feed_id=feed_id))
    classifier_titles  = list(MClassifierTitle.objects(user_id=user.pk, feed_id=feed_id))
    classifier_tags    = list(MClassifierTag.objects(user_id=user.pk, feed_id=feed_id))
    
    checkpoint1 = time.time()
    
    usersub = UserSubscription.objects.get(user=user, feed=feed)
    userstories = []
    if usersub and stories:
        story_ids = [story['id'] for story in stories]
        userstories_db = MUserStory.objects(user_id=user.pk,
                                            feed_id=feed.pk,
                                            story_id__in=story_ids).only('story_id')
        starred_stories = MStarredStory.objects(user_id=user.pk, 
                                                story_feed_id=feed_id, 
                                                story_guid__in=story_ids).only('story_guid', 'starred_date')
        starred_stories = dict([(story.story_guid, story.starred_date) for story in starred_stories])
        userstories = set(us.story_id for us in userstories_db)
            
    checkpoint2 = time.time()
    
    for story in stories:
        story_date = localtime_for_timezone(story['story_date'], user.profile.timezone)
        now = localtime_for_timezone(datetime.datetime.now(), user.profile.timezone)
        story['short_parsed_date'] = format_story_link_date__short(story_date, now)
        story['long_parsed_date'] = format_story_link_date__long(story_date, now)
        if usersub:
            if story['id'] in userstories:
                story['read_status'] = 1
            elif not story.get('read_status') and story['story_date'] < usersub.mark_read_date:
                story['read_status'] = 1
            elif not story.get('read_status') and story['story_date'] > usersub.last_read_date:
                story['read_status'] = 0
            if story['id'] in starred_stories:
                story['starred'] = True
                starred_date = localtime_for_timezone(starred_stories[story['id']], user.profile.timezone)
                story['starred_date'] = format_story_link_date__long(starred_date, now)
        else:
            story['read_status'] = 1
        story['intelligence'] = {
            'feed': apply_classifier_feeds(classifier_feeds, feed),
            'author': apply_classifier_authors(classifier_authors, story),
            'tags': apply_classifier_tags(classifier_tags, story),
            'title': apply_classifier_titles(classifier_titles, story),
        }

    checkpoint3 = time.time()
    
    # Intelligence
    feed_tags = json.decode(feed.data.popular_tags) if feed.data.popular_tags else []
    feed_authors = json.decode(feed.data.popular_authors) if feed.data.popular_authors else []
    classifiers = get_classifiers_for_user(user, feed_id, classifier_feeds, 
                                           classifier_authors, classifier_titles, classifier_tags)
    
    if usersub:
        usersub.feed_opens += 1
        usersub.save()
    diff1 = checkpoint1-start
    diff2 = checkpoint2-start
    diff3 = checkpoint3-start
    timediff = time.time()-start
    last_update = relative_timesince(feed.last_update)
    logging.user(request, "~FYLoading feed: ~SB%s%s ~SN(%.4s seconds, ~SB%.4s/%.4s(%s)/%.4s~SN)" % (
        feed.feed_title[:32], ('~SN/p%s' % page) if page > 1 else '', timediff,
        diff1, diff2, userstories_db and userstories_db.count() or '~SN0~SB', diff3))
    FeedLoadtime.objects.create(feed=feed, loadtime=timediff)
    
    data = dict(stories=stories, 
                feed_tags=feed_tags, 
                feed_authors=feed_authors, 
                classifiers=classifiers,
                last_update=last_update,
                feed_id=feed.pk)
#.........这里部分代码省略.........

        return feed_classifiers
    classifier_feeds   = sort_by_feed(MClassifierFeed.objects(user_id=user.pk, feed_id__in=found_feed_ids))
    classifier_authors = sort_by_feed(MClassifierAuthor.objects(user_id=user.pk, feed_id__in=found_feed_ids))
    classifier_titles  = sort_by_feed(MClassifierTitle.objects(user_id=user.pk, feed_id__in=found_feed_ids))
    classifier_tags    = sort_by_feed(MClassifierTag.objects(user_id=user.pk, feed_id__in=found_feed_ids))
    
    classifiers = {}
    for feed_id in found_feed_ids:
        classifiers[feed_id] = get_classifiers_for_user(user, feed_id, classifier_feeds[feed_id], 
                                                        classifier_authors[feed_id],
                                                        classifier_titles[feed_id],
                                                        classifier_tags[feed_id])
    
    # Just need to format stories
    for story in stories:
        story_date = localtime_for_timezone(story['story_date'], user.profile.timezone)
        now = localtime_for_timezone(datetime.datetime.now(), user.profile.timezone)
        story['short_parsed_date'] = format_story_link_date__short(story_date, now)
        story['long_parsed_date']  = format_story_link_date__long(story_date, now)
        story['read_status'] = 0
        if story['id'] in starred_stories:
            story['starred'] = True
            starred_date = localtime_for_timezone(starred_stories[story['id']], user.profile.timezone)
            story['starred_date'] = format_story_link_date__long(starred_date, now)
        story['intelligence'] = {
            'feed':   apply_classifier_feeds(classifier_feeds[story['story_feed_id']], story['story_feed_id']),
            'author': apply_classifier_authors(classifier_authors[story['story_feed_id']], story),
            'tags':   apply_classifier_tags(classifier_tags[story['story_feed_id']], story),
            'title':  apply_classifier_titles(classifier_titles[story['story_feed_id']], story),
        }

def load_feed_statistics(request, feed_id):
    user = get_user(request)
    timezone = user.profile.timezone
    stats = dict()
    feed = get_object_or_404(Feed, pk=feed_id)
    feed.update_all_statistics()
    feed.set_next_scheduled_update(verbose=True, skip_scheduling=True)
    feed.save_feed_story_history_statistics()
    feed.save_classifier_counts()
    
    # Dates of last and next update
    stats['active'] = feed.active
    stats['last_update'] = relative_timesince(feed.last_update)
    stats['next_update'] = relative_timeuntil(feed.next_scheduled_update)
    stats['push'] = feed.is_push
    if feed.is_push:
        try:
            stats['push_expires'] = localtime_for_timezone(feed.push.lease_expires, 
                                                           timezone).strftime("%Y-%m-%d %H:%M:%S")
        except PushSubscription.DoesNotExist:
            stats['push_expires'] = 'Missing push'
            feed.is_push = False
            feed.save()

    # Minutes between updates
    update_interval_minutes = feed.get_next_scheduled_update(force=True, verbose=False)
    stats['update_interval_minutes'] = update_interval_minutes
    original_active_premium_subscribers = feed.active_premium_subscribers
    original_premium_subscribers = feed.premium_subscribers
    feed.active_premium_subscribers = max(feed.active_premium_subscribers+1, 1)
    feed.premium_subscribers += 1
    premium_update_interval_minutes = feed.get_next_scheduled_update(force=True, verbose=False,
                                                                     premium_speed=True)
    feed.active_premium_subscribers = original_active_premium_subscribers
    feed.premium_subscribers = original_premium_subscribers
    stats['premium_update_interval_minutes'] = premium_update_interval_minutes
    stats['errors_since_good'] = feed.errors_since_good
    
    # Stories per month - average and month-by-month breakout
    average_stories_per_month, story_count_history = feed.average_stories_per_month, feed.data.story_count_history
    stats['average_stories_per_month'] = average_stories_per_month
    story_count_history = story_count_history and json.decode(story_count_history)
    if story_count_history and isinstance(story_count_history, dict):
        stats['story_count_history'] = story_count_history['months']
        stats['story_days_history'] = story_count_history['days']
        stats['story_hours_history'] = story_count_history['hours']
    else:
        stats['story_count_history'] = story_count_history
    
    # Rotate hours to match user's timezone offset
    localoffset = timezone.utcoffset(datetime.datetime.utcnow())
    hours_offset = int(localoffset.total_seconds() / 3600)
    rotated_hours = {}
    for hour, value in stats['story_hours_history'].items():
        rotated_hours[str(int(hour)+hours_offset)] = value
    stats['story_hours_history'] = rotated_hours
    
    # Subscribers
    stats['subscriber_count'] = feed.num_subscribers
    stats['num_subscribers'] = feed.num_subscribers
    stats['stories_last_month'] = feed.stories_last_month
    stats['last_load_time'] = feed.last_load_time
    stats['premium_subscribers'] = feed.premium_subscribers
    stats['active_subscribers'] = feed.active_subscribers
    stats['active_premium_subscribers'] = feed.active_premium_subscribers

    # Classifier counts
    stats['classifier_counts'] = json.decode(feed.data.feed_classifier_counts)
    
    # Fetch histories
    fetch_history = MFetchHistory.feed(feed_id, timezone=timezone)
    stats['feed_fetch_history'] = fetch_history['feed_fetch_history']
    stats['page_fetch_history'] = fetch_history['page_fetch_history']
    stats['feed_push_history'] = fetch_history['push_history']
    
    logging.user(request, "~FBStatistics: ~SB%s" % (feed))

    return stats

def load_feed_statistics(request, feed_id):
    user = get_user(request)
    timezone = user.profile.timezone
    stats = dict()
    feed = get_object_or_404(Feed, pk=feed_id)
    feed.update_all_statistics()
    feed.set_next_scheduled_update(verbose=True, skip_scheduling=True)
    feed.save_feed_story_history_statistics()
    feed.save_classifier_counts()

    # Dates of last and next update
    stats["active"] = feed.active
    stats["last_update"] = relative_timesince(feed.last_update)
    stats["next_update"] = relative_timeuntil(feed.next_scheduled_update)
    stats["push"] = feed.is_push
    if feed.is_push:
        try:
            stats["push_expires"] = localtime_for_timezone(feed.push.lease_expires, timezone).strftime(
                "%Y-%m-%d %H:%M:%S"
            )
        except PushSubscription.DoesNotExist:
            stats["push_expires"] = "Missing push"
            feed.is_push = False
            feed.save()

    # Minutes between updates
    update_interval_minutes = feed.get_next_scheduled_update(force=True, verbose=False)
    stats["update_interval_minutes"] = update_interval_minutes
    original_active_premium_subscribers = feed.active_premium_subscribers
    original_premium_subscribers = feed.premium_subscribers
    feed.active_premium_subscribers = max(feed.active_premium_subscribers + 1, 1)
    feed.premium_subscribers += 1
    premium_update_interval_minutes = feed.get_next_scheduled_update(force=True, verbose=False, premium_speed=True)
    feed.active_premium_subscribers = original_active_premium_subscribers
    feed.premium_subscribers = original_premium_subscribers
    stats["premium_update_interval_minutes"] = premium_update_interval_minutes
    stats["errors_since_good"] = feed.errors_since_good

    # Stories per month - average and month-by-month breakout
    average_stories_per_month, story_count_history = feed.average_stories_per_month, feed.data.story_count_history
    stats["average_stories_per_month"] = average_stories_per_month
    stats["story_count_history"] = story_count_history and json.decode(story_count_history)

    # Subscribers
    stats["subscriber_count"] = feed.num_subscribers
    stats["num_subscribers"] = feed.num_subscribers
    stats["stories_last_month"] = feed.stories_last_month
    stats["last_load_time"] = feed.last_load_time
    stats["premium_subscribers"] = feed.premium_subscribers
    stats["active_subscribers"] = feed.active_subscribers
    stats["active_premium_subscribers"] = feed.active_premium_subscribers

    # Classifier counts
    stats["classifier_counts"] = json.decode(feed.data.feed_classifier_counts)

    # Fetch histories
    fetch_history = MFetchHistory.feed(feed_id, timezone=timezone)
    stats["feed_fetch_history"] = fetch_history["feed_fetch_history"]
    stats["page_fetch_history"] = fetch_history["page_fetch_history"]
    stats["feed_push_history"] = fetch_history["push_history"]

    logging.user(request, "~FBStatistics: ~SB%s" % (feed))

    return stats

def load_social_stories(request, user_id, username=None):
    start          = time.time()
    user           = get_user(request)
    social_user_id = int(user_id)
    social_user    = get_object_or_404(User, pk=social_user_id)
    offset         = int(request.REQUEST.get('offset', 0))
    limit          = int(request.REQUEST.get('limit', 6))
    page           = request.REQUEST.get('page')
    order          = request.REQUEST.get('order', 'newest')
    read_filter    = request.REQUEST.get('read_filter', 'all')
    stories        = []
    
    if page: offset = limit * (int(page) - 1)
    now = localtime_for_timezone(datetime.datetime.now(), user.profile.timezone)
    UNREAD_CUTOFF = datetime.datetime.utcnow() - datetime.timedelta(days=settings.DAYS_OF_UNREAD)
    
    social_profile = MSocialProfile.get_user(social_user.pk)
    try:
        socialsub = MSocialSubscription.objects.get(user_id=user.pk, subscription_user_id=social_user_id)
    except MSocialSubscription.DoesNotExist:
        socialsub = None
    mstories = MSharedStory.objects(user_id=social_user.pk).order_by('-shared_date')[offset:offset+limit]
    stories = Feed.format_stories(mstories)
    
    if socialsub and (read_filter == 'unread' or order == 'oldest'):
        story_ids = socialsub.get_stories(order=order, read_filter=read_filter, offset=offset, limit=limit)
        story_date_order = "%sshared_date" % ('' if order == 'oldest' else '-')
        if story_ids:
            mstories = MSharedStory.objects(user_id=social_user.pk,
                                            story_db_id__in=story_ids).order_by(story_date_order)
            stories = Feed.format_stories(mstories)
    else:
        mstories = MSharedStory.objects(user_id=social_user.pk).order_by('-shared_date')[offset:offset+limit]
        stories = Feed.format_stories(mstories)

    if not stories:
        return dict(stories=[])
    
    checkpoint1 = time.time()
    
    stories, user_profiles = MSharedStory.stories_with_comments_and_profiles(stories, user.pk, check_all=True)

    story_feed_ids = list(set(s['story_feed_id'] for s in stories))
    usersubs = UserSubscription.objects.filter(user__pk=user.pk, feed__pk__in=story_feed_ids)
    usersubs_map = dict((sub.feed_id, sub) for sub in usersubs)
    unsub_feed_ids = list(set(story_feed_ids).difference(set(usersubs_map.keys())))
    unsub_feeds = Feed.objects.filter(pk__in=unsub_feed_ids)
    unsub_feeds = [feed.canonical(include_favicon=False) for feed in unsub_feeds]
    date_delta = UNREAD_CUTOFF
    if socialsub and date_delta < socialsub.mark_read_date:
        date_delta = socialsub.mark_read_date
    
    # Get intelligence classifier for user
    classifier_feeds   = list(MClassifierFeed.objects(user_id=user.pk, social_user_id=social_user_id))
    classifier_authors = list(MClassifierAuthor.objects(user_id=user.pk, social_user_id=social_user_id))
    classifier_titles  = list(MClassifierTitle.objects(user_id=user.pk, social_user_id=social_user_id))
    classifier_tags    = list(MClassifierTag.objects(user_id=user.pk, social_user_id=social_user_id))
    # Merge with feed specific classifiers
    classifier_feeds   = classifier_feeds + list(MClassifierFeed.objects(user_id=user.pk, feed_id__in=story_feed_ids))
    classifier_authors = classifier_authors + list(MClassifierAuthor.objects(user_id=user.pk, feed_id__in=story_feed_ids))
    classifier_titles  = classifier_titles + list(MClassifierTitle.objects(user_id=user.pk, feed_id__in=story_feed_ids))
    classifier_tags    = classifier_tags + list(MClassifierTag.objects(user_id=user.pk, feed_id__in=story_feed_ids))

    checkpoint2 = time.time()
    
    story_ids = [story['id'] for story in stories]
    userstories_db = MUserStory.objects(user_id=user.pk,
                                        feed_id__in=story_feed_ids,
                                        story_id__in=story_ids).only('story_id')
    userstories = set(us.story_id for us in userstories_db)

    starred_stories = MStarredStory.objects(user_id=user.pk, 
                                            story_feed_id__in=story_feed_ids, 
                                            story_guid__in=story_ids).only('story_guid', 'starred_date')
    shared_stories = MSharedStory.objects(user_id=user.pk, 
                                          story_feed_id__in=story_feed_ids, 
                                          story_guid__in=story_ids)\
                                 .only('story_guid', 'shared_date', 'comments')
    starred_stories = dict([(story.story_guid, story.starred_date) for story in starred_stories])
    shared_stories = dict([(story.story_guid, dict(shared_date=story.shared_date, comments=story.comments))
                           for story in shared_stories])
    
    for story in stories:
        story['social_user_id'] = social_user_id
        story_feed_id = story['story_feed_id']
        # story_date = localtime_for_timezone(story['story_date'], user.profile.timezone)
        shared_date = localtime_for_timezone(story['shared_date'], user.profile.timezone)
        story['short_parsed_date'] = format_story_link_date__short(shared_date, now)
        story['long_parsed_date'] = format_story_link_date__long(shared_date, now)
        
        if not socialsub:
            story['read_status'] = 1
        elif story['id'] in userstories:
            story['read_status'] = 1
        elif story['shared_date'] < date_delta:
            story['read_status'] = 1
        elif not usersubs_map.get(story_feed_id):
            story['read_status'] = 0
        elif not story.get('read_status') and story['story_date'] < usersubs_map[story_feed_id].mark_read_date:
            story['read_status'] = 1
#.........这里部分代码省略.........

def load_social_page(request, user_id, username=None, **kwargs):
    start = time.time()
    user = request.user
    social_user_id = int(user_id)
    social_user = get_object_or_404(User, pk=social_user_id)
    offset = int(request.REQUEST.get('offset', 0))
    limit = int(request.REQUEST.get('limit', 6))
    page = request.REQUEST.get('page')
    format = request.REQUEST.get('format', None)
    has_next_page = False
    feed_id = kwargs.get('feed_id') or request.REQUEST.get('feed_id')
    if page: offset = limit * (int(page) - 1)

    user_social_profile = None
    if user.is_authenticated():
        user_social_profile = MSocialProfile.get_user(user.pk)
    social_profile = MSocialProfile.get_user(social_user_id)
    params = dict(user_id=social_user.pk)
    if feed_id:
        params['story_feed_id'] = feed_id
    mstories = MSharedStory.objects(**params).order_by('-shared_date')[offset:offset+limit+1]
    stories = Feed.format_stories(mstories)
    if len(stories) > limit:
        has_next_page = True
        stories = stories[:-1]

    checkpoint1 = time.time()

    if not stories:
        params = {
            "user": user,
            "stories": [],
            "feeds": {},
            "social_user": social_user,
            "social_profile": social_profile,
            'user_social_profile' : json.encode(user_social_profile and user_social_profile.page()),
        }
        template = 'social/social_page.xhtml'
        return render_to_response(template, params, context_instance=RequestContext(request))

    story_feed_ids = list(set(s['story_feed_id'] for s in stories))
    feeds = Feed.objects.filter(pk__in=story_feed_ids)
    feeds = dict((feed.pk, feed.canonical(include_favicon=False)) for feed in feeds)
    for story in stories:
        if story['story_feed_id'] in feeds:
            # Feed could have been deleted.
            story['feed'] = feeds[story['story_feed_id']]
        shared_date = localtime_for_timezone(story['shared_date'], social_user.profile.timezone)
        story['shared_date'] = shared_date
    
    stories, profiles = MSharedStory.stories_with_comments_and_profiles(stories, social_user.pk, 
                                                                        check_all=True)

    checkpoint2 = time.time()
    
    if user.is_authenticated():
        for story in stories:
            if user.pk in story['shared_by_friends'] or user.pk in story['shared_by_public']:
                story['shared_by_user'] = True
                shared_story = MSharedStory.objects.get(user_id=user.pk, 
                                                        story_feed_id=story['story_feed_id'],
                                                        story_guid=story['id'])
                story['user_comments'] = shared_story.comments

    stories = MSharedStory.attach_users_to_stories(stories, profiles)

    params = {
        'social_user'   : social_user,
        'stories'       : stories,
        'user_social_profile' : json.encode(user_social_profile and user_social_profile.page()),
        'social_profile': social_profile,
        'feeds'         : feeds,
        'user_profile'  : hasattr(user, 'profile') and user.profile,
        'has_next_page' : has_next_page,
        'holzer_truism' : random.choice(jennyholzer.TRUISMS) #if not has_next_page else None
    }

    diff1 = checkpoint1-start
    diff2 = checkpoint2-start
    timediff = time.time()-start
    logging.user(request, "~FYLoading ~FMsocial page~FY: ~SB%s%s ~SN(%.4s seconds, ~SB%.4s/%.4s~SN)" % (
        social_profile.title[:22], ('~SN/p%s' % page) if page > 1 else '', timediff,
        diff1, diff2))
    if format == 'html':
        template = 'social/social_stories.xhtml'
    else:
        template = 'social/social_page.xhtml'
        
    return render_to_response(template, params, context_instance=RequestContext(request))

def load_social_page(request, user_id, username=None, **kwargs):
    start = time.time()
    user = request.user
    social_user_id = int(user_id)
    social_user = get_object_or_404(User, pk=social_user_id)
    offset = int(request.REQUEST.get("offset", 0))
    limit = int(request.REQUEST.get("limit", 6))
    page = request.REQUEST.get("page")
    format = request.REQUEST.get("format", None)
    has_next_page = False
    feed_id = kwargs.get("feed_id") or request.REQUEST.get("feed_id")
    if page:
        offset = limit * (int(page) - 1)

    user_social_profile = None
    user_social_services = None
    if user.is_authenticated():
        user_social_profile = MSocialProfile.get_user(user.pk)
        user_social_services = MSocialServices.get_user(user.pk)
    social_profile = MSocialProfile.get_user(social_user_id)

    params = dict(user_id=social_user.pk)
    if feed_id:
        params["story_feed_id"] = feed_id
    mstories = MSharedStory.objects(**params).order_by("-shared_date")[offset : offset + limit + 1]
    stories = Feed.format_stories(mstories)
    if len(stories) > limit:
        has_next_page = True
        stories = stories[:-1]

    checkpoint1 = time.time()

    if not stories:
        params = {
            "user": user,
            "stories": [],
            "feeds": {},
            "social_user": social_user,
            "social_profile": social_profile,
            "user_social_services": user_social_services,
            "user_social_profile": json.encode(user_social_profile and user_social_profile.page()),
        }
        template = "social/social_page.xhtml"
        return render_to_response(template, params, context_instance=RequestContext(request))

    story_feed_ids = list(set(s["story_feed_id"] for s in stories))
    feeds = Feed.objects.filter(pk__in=story_feed_ids)
    feeds = dict((feed.pk, feed.canonical(include_favicon=False)) for feed in feeds)
    for story in stories:
        if story["story_feed_id"] in feeds:
            # Feed could have been deleted.
            story["feed"] = feeds[story["story_feed_id"]]
        shared_date = localtime_for_timezone(story["shared_date"], social_user.profile.timezone)
        story["shared_date"] = shared_date

    stories, profiles = MSharedStory.stories_with_comments_and_profiles(stories, social_user.pk, check_all=True)

    checkpoint2 = time.time()

    if user.is_authenticated():
        for story in stories:
            if user.pk in story["share_user_ids"]:
                story["shared_by_user"] = True
                shared_story = MSharedStory.objects.get(
                    user_id=user.pk, story_feed_id=story["story_feed_id"], story_guid=story["id"]
                )
                story["user_comments"] = shared_story.comments

    stories = MSharedStory.attach_users_to_stories(stories, profiles)

    params = {
        "social_user": social_user,
        "stories": stories,
        "user_social_profile": user_social_profile,
        "user_social_profile_page": json.encode(user_social_profile and user_social_profile.page()),
        "user_social_services": user_social_services,
        "user_social_services_page": json.encode(user_social_services and user_social_services.to_json()),
        "social_profile": social_profile,
        "feeds": feeds,
        "user_profile": hasattr(user, "profile") and user.profile,
        "has_next_page": has_next_page,
        "holzer_truism": random.choice(jennyholzer.TRUISMS),  # if not has_next_page else None
    }

    diff1 = checkpoint1 - start
    diff2 = checkpoint2 - start
    timediff = time.time() - start
    logging.user(
        request,
        "~FYLoading ~FMsocial page~FY: ~SB%s%s ~SN(%.4s seconds, ~SB%.4s/%.4s~SN)"
        % (social_profile.title[:22], ("~SN/p%s" % page) if page > 1 else "", timediff, diff1, diff2),
    )
    if format == "html":
        template = "social/social_stories.xhtml"
    else:
        template = "social/social_page.xhtml"

    return render_to_response(template, params, context_instance=RequestContext(request))

def load_river_blurblog(request):
    limit = 10
    start = time.time()
    user = get_user(request)
    social_user_ids = [int(uid) for uid in request.REQUEST.getlist("social_user_ids") if uid]
    original_user_ids = list(social_user_ids)
    page = int(request.REQUEST.get("page", 1))
    order = request.REQUEST.get("order", "newest")
    read_filter = request.REQUEST.get("read_filter", "unread")
    relative_user_id = request.REQUEST.get("relative_user_id", None)
    now = localtime_for_timezone(datetime.datetime.now(), user.profile.timezone)
    UNREAD_CUTOFF = datetime.datetime.utcnow() - datetime.timedelta(days=settings.DAYS_OF_UNREAD)

    if not relative_user_id:
        relative_user_id = get_user(request).pk

    if not social_user_ids:
        socialsubs = MSocialSubscription.objects.filter(user_id=user.pk)
        social_user_ids = [s.subscription_user_id for s in socialsubs]

    offset = (page - 1) * limit
    limit = page * limit - 1

    story_ids, story_dates = MSocialSubscription.feed_stories(
        user.pk, social_user_ids, offset=offset, limit=limit, order=order, read_filter=read_filter
    )
    mstories = MStory.objects(id__in=story_ids)
    story_id_to_dates = dict(zip(story_ids, story_dates))

    def sort_stories_by_id(a, b):
        return int(story_id_to_dates[str(b.id)]) - int(story_id_to_dates[str(a.id)])

    sorted_mstories = sorted(mstories, cmp=sort_stories_by_id)
    stories = Feed.format_stories(sorted_mstories)
    for s, story in enumerate(stories):
        story["story_date"] = datetime.datetime.fromtimestamp(story_dates[s])
    stories, user_profiles = MSharedStory.stories_with_comments_and_profiles(stories, relative_user_id, check_all=True)

    story_feed_ids = list(set(s["story_feed_id"] for s in stories))
    usersubs = UserSubscription.objects.filter(user__pk=user.pk, feed__pk__in=story_feed_ids)
    usersubs_map = dict((sub.feed_id, sub) for sub in usersubs)
    unsub_feed_ids = list(set(story_feed_ids).difference(set(usersubs_map.keys())))
    unsub_feeds = Feed.objects.filter(pk__in=unsub_feed_ids)
    unsub_feeds = [feed.canonical(include_favicon=False) for feed in unsub_feeds]

    # Find starred stories
    if story_feed_ids:
        story_ids = [story["id"] for story in stories]
        starred_stories = MStarredStory.objects(user_id=user.pk, story_guid__in=story_ids).only(
            "story_guid", "starred_date"
        )
        starred_stories = dict([(story.story_guid, story.starred_date) for story in starred_stories])
        shared_stories = MSharedStory.objects(user_id=user.pk, story_guid__in=story_ids).only(
            "story_guid", "shared_date", "comments"
        )
        shared_stories = dict(
            [
                (story.story_guid, dict(shared_date=story.shared_date, comments=story.comments))
                for story in shared_stories
            ]
        )

        userstories_db = MUserStory.objects(user_id=user.pk, feed_id__in=story_feed_ids, story_id__in=story_ids).only(
            "story_id"
        )
        userstories = set(us.story_id for us in userstories_db)

    else:
        starred_stories = {}
        shared_stories = {}
        userstories = []

    # Intelligence classifiers for all feeds involved
    if story_feed_ids:
        classifier_feeds = list(MClassifierFeed.objects(user_id=user.pk, feed_id__in=story_feed_ids))
        classifier_authors = list(MClassifierAuthor.objects(user_id=user.pk, feed_id__in=story_feed_ids))
        classifier_titles = list(MClassifierTitle.objects(user_id=user.pk, feed_id__in=story_feed_ids))
        classifier_tags = list(MClassifierTag.objects(user_id=user.pk, feed_id__in=story_feed_ids))
    else:
        classifier_feeds = []
        classifier_authors = []
        classifier_titles = []
        classifier_tags = []
    classifiers = sort_classifiers_by_feed(
        user=user,
        feed_ids=story_feed_ids,
        classifier_feeds=classifier_feeds,
        classifier_authors=classifier_authors,
        classifier_titles=classifier_titles,
        classifier_tags=classifier_tags,
    )

    # Just need to format stories
    for story in stories:
        if story["id"] in userstories:
            story["read_status"] = 1
        elif story["story_date"] < UNREAD_CUTOFF:
            story["read_status"] = 1
        else:
            story["read_status"] = 0
#.........这里部分代码省略.........

def load_single_feed(request, feed_id):
    start = datetime.datetime.utcnow()
    user = get_user(request)
    offset = int(request.REQUEST.get('offset', 0))
    limit = int(request.REQUEST.get('limit', 12))
    page = int(request.REQUEST.get('page', 1))
    if page:
        offset = limit * (page-1)
    dupe_feed_id = None
    if not feed_id:
        raise Http404
        
    try:
        feed = Feed.objects.get(id=feed_id)
    except Feed.DoesNotExist:
        feed_address = request.REQUEST.get('feed_address')
        dupe_feed = DuplicateFeed.objects.filter(duplicate_address=feed_address)
        if dupe_feed:
            feed = dupe_feed[0].feed
            dupe_feed_id = feed_id
        else:
            raise Http404
        
    stories = feed.get_stories(offset, limit) 
        
    # Get intelligence classifier for user
    classifier_feeds   = MClassifierFeed.objects(user_id=user.pk, feed_id=feed_id)
    classifier_authors = MClassifierAuthor.objects(user_id=user.pk, feed_id=feed_id)
    classifier_titles  = MClassifierTitle.objects(user_id=user.pk, feed_id=feed_id)
    classifier_tags    = MClassifierTag.objects(user_id=user.pk, feed_id=feed_id)
    
    usersub = UserSubscription.objects.get(user=user, feed=feed)
    userstories = []
    if usersub:
        userstories_db = MUserStory.objects(user_id=user.pk,
                                            feed_id=feed.pk,
                                            read_date__gte=usersub.mark_read_date)
        starred_stories = MStarredStory.objects(user_id=user.pk, story_feed_id=feed_id).only('story_guid', 'starred_date')
        starred_stories = dict([(story.story_guid, story.starred_date) for story in starred_stories])

        for us in userstories_db:
            if hasattr(us.story, 'story_guid') and isinstance(us.story.story_guid, unicode):
                userstories.append(us.story.story_guid)
            elif hasattr(us.story, 'id') and isinstance(us.story.id, unicode):
                userstories.append(us.story.id) # TODO: Remove me after migration from story.id->guid
            
    for story in stories:
        [x.rewind() for x in [classifier_feeds, classifier_authors, classifier_tags, classifier_titles]]
        story_date = localtime_for_timezone(story['story_date'], user.profile.timezone)
        now = localtime_for_timezone(datetime.datetime.now(), user.profile.timezone)
        story['short_parsed_date'] = format_story_link_date__short(story_date, now)
        story['long_parsed_date'] = format_story_link_date__long(story_date, now)
        if usersub:
            if story['id'] in userstories:
                story['read_status'] = 1
            elif not story.get('read_status') and story['story_date'] < usersub.mark_read_date:
                story['read_status'] = 1
            elif not story.get('read_status') and story['story_date'] > usersub.last_read_date:
                story['read_status'] = 0
            if story['id'] in starred_stories:
                story['starred'] = True
                starred_date = localtime_for_timezone(starred_stories[story['id']], user.profile.timezone)
                story['starred_date'] = format_story_link_date__long(starred_date, now)
        else:
            story['read_status'] = 1
        story['intelligence'] = {
            'feed': apply_classifier_feeds(classifier_feeds, feed),
            'author': apply_classifier_authors(classifier_authors, story),
            'tags': apply_classifier_tags(classifier_tags, story),
            'title': apply_classifier_titles(classifier_titles, story),
        }
    
    # Intelligence
    feed_tags = json.decode(feed.data.popular_tags) if feed.data.popular_tags else []
    feed_authors = json.decode(feed.data.popular_authors) if feed.data.popular_authors else []
    classifiers = get_classifiers_for_user(user, feed_id, classifier_feeds, 
                                           classifier_authors, classifier_titles, classifier_tags)
    
    if usersub:
        usersub.feed_opens += 1
        usersub.save()
    
    diff = datetime.datetime.utcnow()-start
    timediff = float("%s.%.2s" % (diff.seconds, (diff.microseconds / 1000)))
    last_update = relative_timesince(feed.last_update)
    logging.user(request.user, "~FYLoading feed: ~SB%s%s ~SN(%s seconds)" % (
        feed, ('~SN/p%s' % page) if page > 1 else '', timediff))
    FeedLoadtime.objects.create(feed=feed, loadtime=timediff)
    
    data = dict(stories=stories, 
                feed_tags=feed_tags, 
                feed_authors=feed_authors, 
                classifiers=classifiers,
                last_update=last_update,
                feed_id=feed.pk)
    
    if dupe_feed_id: data['dupe_feed_id'] = dupe_feed_id
    if not usersub:
        data.update(feed.canonical())
        
#.........这里部分代码省略.........