本文整理汇总了Python中r2.models.Subreddit.default_subreddits方法的典型用法代码示例。如果您正苦于以下问题：Python Subreddit.default_subreddits方法的具体用法？Python Subreddit.default_subreddits怎么用？Python Subreddit.default_subreddits使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类r2.models.Subreddit的用法示例。
在下文中一共展示了Subreddit.default_subreddits方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: get_recommended_content
# 需要导入模块: from r2.models import Subreddit [as 别名]
# 或者: from r2.models.Subreddit import default_subreddits [as 别名]
def get_recommended_content(prefs, src, settings):
"""Get a mix of content from subreddits recommended for someone with
the given preferences (likes and dislikes.)
Returns a list of ExploreItems.
"""
# numbers chosen empirically to give enough results for explore page
num_liked = 10 # how many liked srs to use when generating the recs
num_recs = 20 # how many recommended srs to ask for
num_discovery = 2 # how many discovery-related subreddits to mix in
num_rising = 4 # how many rising links to mix in
num_items = 20 # total items to return
rising_items = discovery_items = comment_items = hot_items = []
# make a list of srs that shouldn't be recommended
default_srid36s = [to36(srid) for srid in Subreddit.default_subreddits()]
omit_srid36s = list(prefs.likes.union(prefs.dislikes,
prefs.recent_views,
default_srid36s))
# pick random subset of the user's liked srs
liked_srid36s = random_sample(prefs.likes, num_liked) if settings.personalized else []
# pick random subset of discovery srs
candidates = set(get_discovery_srid36s()).difference(prefs.dislikes)
discovery_srid36s = random_sample(candidates, num_discovery)
# multiget subreddits
to_fetch = liked_srid36s + discovery_srid36s
srs = Subreddit._byID36(to_fetch)
liked_srs = [srs[sr_id36] for sr_id36 in liked_srid36s]
discovery_srs = [srs[sr_id36] for sr_id36 in discovery_srid36s]
if settings.personalized:
# generate recs from srs we know the user likes
recommended_srs = get_recommendations(liked_srs,
count=num_recs,
to_omit=omit_srid36s,
source=src,
match_set=False,
over18=settings.nsfw)
random.shuffle(recommended_srs)
# split list of recommended srs in half
midpoint = len(recommended_srs) / 2
srs_slice1 = recommended_srs[:midpoint]
srs_slice2 = recommended_srs[midpoint:]
# get hot links plus top comments from one half
comment_items = get_comment_items(srs_slice1, src)
# just get hot links from the other half
hot_items = get_hot_items(srs_slice2, TYPE_HOT, src)
if settings.discovery:
# get links from subreddits dedicated to discovery
discovery_items = get_hot_items(discovery_srs, TYPE_DISCOVERY, 'disc')
if settings.rising:
# grab some (non-personalized) rising items
omit_sr_ids = set(int(id36, 36) for id36 in omit_srid36s)
rising_items = get_rising_items(omit_sr_ids, count=num_rising)
# combine all items and randomize order to get a mix of types
all_recs = list(chain(rising_items,
comment_items,
discovery_items,
hot_items))
random.shuffle(all_recs)
# make sure subreddits aren't repeated
seen_srs = set()
recs = []
for r in all_recs:
if not settings.nsfw and r.is_over18():
continue
if not is_visible(r.sr): # could happen in rising items
continue
if r.sr._id not in seen_srs:
recs.append(r)
seen_srs.add(r.sr._id)
if len(recs) >= num_items:
break
return recs