def show_score(self, id):
if not c.user:
return redirect(url(controller='login', action='signin', id=None, return_to=url.current()))
c.entry = meta.find(model.FeedEntry, id)
feed = meta.find(model.Feed, c.entry.feed_id)
c.feed = feed
guesser = Guesser(feed, c.user, config)
guess = guesser.guess(c.entry)
log.debug("guess: %s" % guess)
log.debug("c.entry.title: %s" % c.entry.title)
c.score = str(guess)
c.score = guesser.guess(c.entry)
c.pool = guesser.trainer.poolData('spam')
c.is_spam = guesser.is_spam(c.entry)
import operator
c.pool_data_spam = guesser.trainer.poolData('spam')
c.pool_data_spam.sort(key=operator.itemgetter(1))
c.pool_data_spam.reverse()
c.pool_data_ham = guesser.trainer.poolData('ham')
c.pool_data_ham.sort(key=operator.itemgetter(1))
c.pool_data_ham.reverse()
c.tokens = set(guesser.trainer.getTokens(__relevant__(c.entry)))
return render('bayes/score.mako')
def mixed_rss_with_report(self, user_id, id):
c.rss_user = meta.find(model.User, user_id)
log.debug("c.rss_user: %s" % c.rss_user)
feed_data = meta.find(model.Feed, id)
log.debug("feed_data.id %s" % feed_data.id)
import feed
fetch_result = feed_data.fetch()
feed = h.DefaultFeed(
title=feed_data.title,
link=feed_data.link,
description="TESTING",
language=feed_data.language,
)
c.base_url = config['base_url']
log.debug('c.base_url: %s' % c.base_url)
guesser = Guesser(feed_data, c.rss_user, config)
settings = c.rss_user.get_bayes_feed_setting(feed_data.id)
meta.Session.add(settings)
delta = h.timedelta_from_string(settings.summarize_at)
log.debug("delta %s" % delta)
if not settings.report_offset:
entries = feed_data.get_entries().order_by(model.FeedEntry.id).all()
log.warn("no report_offset available, read %s entries" % len(entries))
else:
entries = feed_data.get_entries().filter(model.FeedEntry.id >= settings.report_offset).order_by(model.FeedEntry.id).all()
from rssmonster.lib.reporter import Reporter
reporter = Reporter(None, None, delta, 30)
for entry in entries:
reporter.add_item(entry, guesser.is_spam(entry))
for entry_box in reporter.entry_queue:
#log.debug("entry_box: %s" % entry_box)
if entry_box['type'] == 'ham':
c.entry = entry_box['entry']
c.entry.is_spam=guesser.is_spam(c.entry)
feed.add_item(title=c.entry.title,
link=c.entry.link,
description=render('bayes/rss_summary.mako'),
unique_id=c.entry.uid,
pubdate=c.entry.updated)
elif entry_box['type'] == 'spam':
add_spam_report(feed, entry_box['entries'])
settings.report_offset = reporter.offset_id()
log.debug("settings.report_offset: %s" % settings.report_offset)
log.debug("holding back: %s" % len(reporter.spam_entries))
meta.Session.commit()
return feed.writeString('utf-8')
def __mixed_rss__(self, user_id, id):
c.rss_user = meta.find(model.User, user_id)
log.debug("c.rss_user: %s" % c.rss_user)
feed_data = meta.find(model.Feed, id)
log.debug("feed_data.id %s" % feed_data.id)
import feed
fetch_result = feed_data.fetch()
feed = h.DefaultFeed(
title=feed_data.title,
link=feed_data.link,
description="TESTING",
language=feed_data.language,
)
c.base_url = config['base_url']
log.debug('c.base_url: %s' % c.base_url)
guesser = Guesser(feed_data, c.rss_user, config)
entries = feed_data.get_entries().order_by(model.FeedEntry.updated.desc()).limit(30)
for entry in entries:
c.entry = entry
c.entry.is_spam=guesser.is_spam(entry)
if c.entry.is_spam:
titel = "[SPAM] %s" % entry.title
else:
titel = entry.title
feed.add_item(title=titel,
link=entry.link,
description=render('bayes/rss_summary.mako'),
unique_id=entry.uid,
pubdate=entry.updated) #entry.summary
#meta.Session.commit()
response.content_type = 'application/atom+xml'
return feed.writeString('utf-8')
def redo(self, id):
if not c.user:
return redirect(url(controller='login', action='signin', id=None, return_to=url.current()))
c.feed = meta.find(model.Feed, id)
query = meta.Session\
.query(model.Classification)\
.join(model.FeedEntry)\
.filter_by(feed_id=id)
guesser = Guesser(c.feed, c.user, config)
guesser.clear()
cnt = 0
needles_cnt = 0
for entry in query:
# h.flash("%s :%s" % (entry.pool, __relevant__(entry.entry)))
# guesser.trainer.train(entry.pool, __relevant__(entry.entry))
if guesser.is_spam(entry.entry, use_classified=False) and (entry.pool == 'spam'):
needles_cnt += 1
elif not guesser.is_spam(entry.entry, use_classified=False) and (entry.pool == 'ham'):
needles_cnt += 1
self.__mark_as__(entry.entry, entry.pool, guesser, True)
cnt+=1
guesser.save()
log.debug("FOOOOOO")
if needles_cnt > 0:
h.flash("%d entries were needlessly trained (total: %s)" % (needles_cnt, cnt))
else:
h.flash("learned %s entries" % cnt)
return h.go_back()