mirror of
https://github.com/Mikaela/Limnoria.git
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204 lines
7.5 KiB
Python
204 lines
7.5 KiB
Python
###
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# Copyright (c) 2004, Jeremiah Fincher
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# All rights reserved.
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#
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# Redistribution and use in source and binary forms, with or without
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# modification, are permitted provided that the following conditions are met:
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#
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# * Redistributions of source code must retain the above copyright notice,
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# this list of conditions, and the following disclaimer.
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# * Redistributions in binary form must reproduce the above copyright notice,
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# this list of conditions, and the following disclaimer in the
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# documentation and/or other materials provided with the distribution.
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# * Neither the name of the author of this software nor the name of
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# contributors to this software may be used to endorse or promote products
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# derived from this software without specific prior written consent.
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#
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# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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# ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
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# LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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# CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
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# SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
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# INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
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# CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
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# ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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# POSSIBILITY OF SUCH DAMAGE.
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###
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"""
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Watches for paste-floods in a channel and takes appropriate measures against
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violators.
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"""
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import supybot
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__revision__ = "$Id$"
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__author__ = supybot.authors.jemfinch
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__contributors__ = {}
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import supybot.plugins as plugins
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import glob
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import os.path
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import reverend.thomas
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from cStringIO import StringIO as sio
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import supybot.conf as conf
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import supybot.utils as utils
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from supybot.commands import *
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import supybot.ircutils as ircutils
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import supybot.registry as registry
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import supybot.callbacks as callbacks
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def configure(advanced):
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# This will be called by setup.py to configure this module. Advanced is
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# a bool that specifies whether the user identified himself as an advanced
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# user or not. You should effect your configuration by manipulating the
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# registry as appropriate.
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from supybot.questions import expect, anything, something, yn
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conf.registerPlugin('Bayes', True)
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Bayes = conf.registerPlugin('Bayes')
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conf.registerChannelValue(Bayes, 'maximumLines',
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registry.NonNegativeInteger(4, """Determines the maximum allowable number
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of consecutive messages that classify as a paste. If this value is 0, no
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checking will be done."""))
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def tokenize(s):
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return s.lower().split()
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class PickleBayesDB(plugins.DbiChannelDB):
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class DB(object):
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def __init__(self, filename):
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self.filename = filename
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self.nickFilename = self.filename.replace('pickle', 'nick.pickle')
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self.bayes = reverend.thomas.Bayes(tokenize)
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if os.path.exists(self.filename):
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self.bayes.load(self.filename)
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self.nickBayes = reverend.thomas.Bayes(tokenize)
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if os.path.exists(self.nickFilename):
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self.nickBayes.load(self.nickFilename)
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def close(self):
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self.bayes.save(self.filename)
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self.nickBayes.save(self.nickFilename)
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flush = close
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def train(self, kind, s):
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self.bayes.train(kind, s)
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def trainNick(self, nick, s):
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self.nickBayes.train(nick, s)
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def guess(self, s):
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matches = self.bayes.guess(s)
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if matches:
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if matches[0][1] > 0.5:
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if len(matches) > 1 and \
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matches[0][1] - matches[1][1] < 0.4:
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return None
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else:
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return matches[0]
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else:
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self.bayes.train('normal', s)
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return None
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def guessNick(self, s):
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L = [t for t in self.nickBayes.guess(s) if t[1] > 0.01]
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if len(L) > 1:
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if L[0][1] / L[1][1] > 2:
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return [L[0]]
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return L
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BayesDB = plugins.DB('Bayes', {'pickle': PickleBayesDB})
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class Bayes(callbacks.Privmsg):
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def __init__(self):
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self.__parent = super(Bayes, self)
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self.__parent.__init__()
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self.db = BayesDB()
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def die(self):
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self.db.close()
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def doPrivmsg(self, irc, msg):
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(channel, text) = msg.args
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if not ircutils.isChannel(channel) or msg.guessed:
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return
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kind = self.db.guess(channel, text)
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if kind is not None:
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(kind, prob) = kind
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prob *= 100
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text = utils.ellipsisify(text, 30)
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self.log.debug('Classified %r as %s. (%.2f%%)', text, kind, prob)
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self.db.trainNick(channel, msg.nick, text)
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def guess(self, irc, msg, args, channel, text):
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"""[<channel>] <text>
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Guesses how <text> should be classified according to the Bayesian
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classifier for <channel>. <channel> is only necessary if the message
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isn't sent in the channel itself, and then only if
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supybot.databases.plugins.channelSpecific is True.
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"""
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msg.tag('guessed')
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kind = self.db.guess(channel, text)
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if kind is not None:
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(kind, prob) = kind
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prob *= 100
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irc.reply('That seems to me to be %s, '
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'but I\'m only %.2f certain.' % (kind, prob))
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else:
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irc.reply('I don\'t know what the heck that is.')
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guess = wrap(guess, ['channeldb', 'something'])
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def who(self, irc, msg, args, channel, text):
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"""[<channel>] <text>
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Guesses who might have said <text>. <channel> is only necessary if the
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message isn't sent in the channel itself, and then only if
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supybot.databases.plugins.channelSpecific is True.
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"""
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msg.tag('guessed')
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kinds = self.db.guessNick(channel, text)
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if kinds:
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if len(kinds) == 1:
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(kind, prob) = kinds.pop()
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irc.reply('It seems to me (with %.2f%% certainty) '
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'that %s said that.' % (prob*100, kind))
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else:
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kinds = ['%s (%.2f%%)' % (k, prob*100) for (k, prob) in kinds]
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irc.reply('I\'m not quite sure who said that, but it could be '
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+ utils.commaAndify(kinds, And='or'))
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else:
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irc.reply('I have no idea who might\'ve said that.')
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who = wrap(who, ['channeldb', 'something'])
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def train(self, irc, msg, args, channel, language, pattern):
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"""[<channel>] <language> <glob>
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Trains the bot to recognize text similar to that contained in the files
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matching <glob> as text of the language <language>. <channel> is only
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necessary if the message isn't sent in the channel itself, and then
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only if supybot.databases.plugins.channelSpecific is True.
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"""
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filenames = glob.glob(pattern)
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if not filenames:
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irc.errorInvalid('glob', pattern)
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for filename in filenames:
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fd = file(filename)
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for line in fd:
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self.db.train(channel, language, line)
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fd.close()
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irc.replySuccess()
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train = wrap(train, ['channeldb', 'something', 'something'])
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Class = Bayes
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# vim:set shiftwidth=4 tabstop=8 expandtab textwidth=78:
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