Mercurial > p > roundup > code
view website/issues/extensions/spambayes.py @ 5118:57452bc6d989
issue2550853 - better error handling and cleanup on some postgres
tests by Stuart McGraw.
My postgres tests passed both before and after I applied his patch,
but the code change seems rational.
issue2086536 - back_postgresql: fixing pg_command and prefering
psycopg2. Patch done by Philipp Gortan (mephinet). His patch
also improves handling of retryable errors. Applied and
edited by John Rouillard. Edits included removing support for
psycopg1. See:
https://sourceforge.net/p/roundup/mailman/message/32855027/
for rational for dropping it
Again all 137 postgres tests pass.
| author | John Rouillard <rouilj@ieee.org> |
|---|---|
| date | Sat, 02 Jul 2016 21:15:23 -0400 |
| parents | ca692423e401 |
| children | 198b6e810c67 |
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import re, math from roundup.cgi.actions import Action from roundup.cgi.exceptions import * import xmlrpclib, socket REVPAT = re.compile(r'(r[0-9]+\b|rev(ision)? [0-9]+\b)') def extract_classinfo(db, classname, nodeid): node = db.getnode(classname, nodeid) authorage = node['creation'].timestamp() - \ db.getnode('user', node.get('author', node.get('creator')))['creation'].timestamp() authorid = node.get('author', node.get('creator')) content = db.getclass(classname).get(nodeid, 'content') tokens = ["klass:%s" % classname, "author:%s" % authorid, "authorage:%d" % int(math.log(authorage)), "hasrev:%s" % (REVPAT.search(content) is not None)] return (content, tokens) def train_spambayes(db, content, tokens, is_spam): spambayes_uri = db.config.detectors['SPAMBAYES_URI'] server = xmlrpclib.ServerProxy(spambayes_uri, verbose=False) try: server.train({'content':content}, tokens, {}, is_spam) return (True, None) except (socket.error, xmlrpclib.Error), e: return (False, str(e)) class SpambayesClassify(Action): permissionType = 'SB: May Classify' def handle(self): (content, tokens) = extract_classinfo(self.db, self.classname, self.nodeid) if self.form.has_key("trainspam"): is_spam = True elif self.form.has_key("trainham"): is_spam = False (status, errmsg) = train_spambayes(self.db, content, tokens, is_spam) node = self.db.getnode(self.classname, self.nodeid) props = {} if status: if node.get('spambayes_misclassified', False): props['spambayes_misclassified'] = True props['spambayes_score'] = 1.0 s = " SPAM" if not is_spam: props['spambayes_score'] = 0.0 s = " HAM" self.client.add_ok_message(self._('Message classified as') + s) else: self.client.add_error_message(self._('Unable to classify message, got error:') + errmsg) klass = self.db.getclass(self.classname) klass.set(self.nodeid, **props) self.db.commit() def sb_is_spam(obj): cutoff_score = float(obj._db.config.detectors['SPAMBAYES_SPAM_CUTOFF']) try: score = obj['spambayes_score'] except KeyError: return False return score >= cutoff_score def init(instance): instance.registerAction("spambayes_classify", SpambayesClassify) instance.registerUtil('sb_is_spam', sb_is_spam)
