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
line wrap: on
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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)
    

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