Mercurial > p > roundup > code
view website/issues/extensions/spambayes.py @ 5132:0142b4fb5a2d
issue2550648 - partial fix for problem in this issue. Ezio Melotti
reported that the expression editor allowed the user to generate an
expression using retired values. To align the expression editor with
the simple dropdown search item, retired values are now removed from
the expression editor.
Do we really want this though? Supposed a keyword is retired and I
want to search for an issue with that retired keyword? Do we have a
best policy document that says to remove retired keywords from all
places it could possibly be used? It could be argued that the simple
search dropdown is wrong and should allow selecting retired values.
| author | John Rouillard <rouilj@ieee.org> |
|---|---|
| date | Fri, 08 Jul 2016 19:31:02 -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)
