def _fetch_tweets(twit,uid):
tweets = Tweets.get_id(uid)
if not tweets:
tweets_ = twit.user_timeline(uid)
tweets = Tweets(_id=uid,tweets=tweets_)
tweets.save()
return tweets
def geo_ats():
"""
fetch all at mentions from database
"""
for tweets in Tweets.find({},fields=['ats']):
if tweets.ats:
uid = tweets._id
yield User.mod_id(uid), (uid,tweets.ats)
def test_find_contacts_errors(self):
self.FS["mloc_users.04"] = [dict(id=404)]
self.FS["mloc_users.03"] = [dict(id=503)]
with _patch_twitter():
self.gob.run_job("find_contacts")
for uid in (404, 503):
missing = User.get_id(uid)
self.assertEqual(missing.error_status, uid)
self.assertEqual(missing.neighbors, None)
self.assertEqual(missing.rfriends, None)
self.assertEqual(Edges.get_id(uid), None)
self.assertEqual(Tweets.get_id(uid), None)
def nebrs_d(user_d,mloc_blur):
"""
create dict with lots of information about a target user's located contacts
"""
mb = MlocBlur(*mloc_blur)
user = User(user_d)
nebrs = User.find(User._id.is_in(user_d['nebrs']))
tweets = Tweets.get_id(user_d['_id'],fields=['ats'])
res = make_nebrs_d(user,nebrs,tweets.ats)
res['mloc'] = user_d['mloc']
res['gnp'] = _blur_gnp(mb, user_d)
return [res]
def total_contacts(user_ds):
"""
count the total number of contacts (to include in the paper)
"""
for user_d in itertools.islice(user_ds,2600):
user = User.get_id(user_d['id'])
if not user:
yield "no user"
elif user.error_status:
yield str(user.error_status)
else:
edges = Edges.get_id(user._id)
tweets = Tweets.get_id(user._id)
if not edges or not tweets:
yield "no contacts"
else:
sets = _contact_sets(tweets,edges)
yield [len(sets[k]) for k in User.NEBR_KEYS]
