def find_contacts(user_ds):
"""
for each target user, fetch edges and tweets, pick 100 located contact ids
"""
gis = gisgraphy.GisgraphyResource()
twit = twitter.TwitterResource()
for user_d in itertools.islice(user_ds,2600):
user = User.get_id(user_d['id'])
if user:
logging.warn("not revisiting %d",user._id)
else:
user = User(user_d)
user.geonames_place = gis.twitter_loc(user.location)
_save_user_contacts(twit, user, _pick_random_contacts, limit=100)
for mod_nebr in _my_contacts(user):
yield mod_nebr
def predict(self, user_d, steps=0):
"""
Attept to locate a Twitter user.
user_d should be a Twitter-style user dictionary
steps is the number of steps on the social graph to crawl. It should
be 0, 1, or 2. If 0, predict makes no Twitter API calls, 1 uses
4 calls, and 2 uses around 80 API calls.
returns (longitude, latitude) or None if no location can be found
"""
user = User(user_d)
if steps == 0 and not user.location:
return None
gnp = self.gis.twitter_loc(user.location)
if steps == 0:
return gnp.to_tup() if gnp else None
if gnp and gnp.mdist < MAX_GNP_MDIST:
user.geonames_place = gnp
return gnp.to_tup()
_crawl_pred_one(user, self.twit, self.gis, self.pred, fast=(steps == 1))
return user.pred_loc