mirror of
https://github.com/Mikaela/Limnoria.git
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376 lines
14 KiB
Python
376 lines
14 KiB
Python
###
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# Copyright (c) 2002-2004, 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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Silently listens to a channel, building a database of Markov Chains for
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later hijinks. To read more about Markov Chains, check out
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<http://www.cs.bell-labs.com/cm/cs/pearls/sec153.html>. When the database is
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large enough, you can have it make fun little random messages from it.
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"""
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__revision__ = "$Id$"
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import supybot.plugins as plugins
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import sets
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import time
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import Queue
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import anydbm
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import random
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import os.path
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import threading
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import supybot.conf as conf
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import supybot.world as world
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from supybot.commands import *
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import supybot.ircmsgs as ircmsgs
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import supybot.ircutils as ircutils
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import supybot.registry as registry
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import supybot.schedule as schedule
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import supybot.callbacks as callbacks
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conf.registerPlugin('Markov')
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conf.registerGroup(conf.supybot.plugins.Markov, 'randomSpeaking')
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conf.registerChannelValue(conf.supybot.plugins.Markov.randomSpeaking,
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'probability', registry.Probability(0, """Determines the probability that
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will be checked against to determine whether the bot should randomly say
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something. If 0, the bot will never say anything on it's own. If 1, the
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bot will speak every time we make a check."""))
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conf.registerChannelValue(conf.supybot.plugins.Markov.randomSpeaking,
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'maxDelay', registry.PositiveInteger(10, """Determines the upper bound for
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how long the bot will wait before randomly speaking. The delay is a
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randomly generated number of seconds below the value of this config
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variable."""))
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conf.registerChannelValue(conf.supybot.plugins.Markov.randomSpeaking,
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'throttleTime', registry.PositiveInteger(300, """Determines the minimum
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number of seconds between the bot randomly speaking."""))
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conf.registerChannelValue(conf.supybot.plugins.Markov, 'minChainLength',
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registry.PositiveInteger(1, """Determines the length of the smallest chain
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which the markov command will generate."""))
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conf.registerChannelValue(conf.supybot.plugins.Markov, 'maxAttempts',
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registry.PositiveInteger(1, """Determines the maximum number of times the
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bot will attempt to generate a chain that meets or exceeds the size set in
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minChainLength."""))
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class DbmMarkovDB(object):
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def __init__(self, filename):
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self.dbs = ircutils.IrcDict()
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self.filename = filename
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def close(self):
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for db in self.dbs.values():
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db.close()
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def _getDb(self, channel):
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if channel not in self.dbs:
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filename = plugins.makeChannelFilename(self.filename, channel)
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# To keep the code simpler for addPair, I decided not to make
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# self.dbs[channel]['firsts'] and ['lasts']. Instead, we'll pad
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# the words list being sent to addPair such that ['\n \n'] will be
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# ['firsts'] and ['\n'] will be ['lasts']. This also means isFirst
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# and isLast aren't necessary, but they'll be left alone in case
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# one of the other Db formats uses them or someone decides that I
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# was wrong and changes my code.
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self.dbs[channel] = anydbm.open(filename, 'c')
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return self.dbs[channel]
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def _flush(self, db):
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if hasattr(db, 'sync'):
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db.sync()
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if hasattr(db, 'flush'):
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db.flush()
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def addPair(self, channel, first, second, follower,
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isFirst=False, isLast=False):
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db = self._getDb(channel)
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combined = self._combine(first, second)
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if db.has_key(combined): # EW!
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db[combined] = ' '.join([db[combined], follower])
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else:
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db[combined] = follower
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if follower == '\n':
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if db.has_key('\n'):
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db['\n'] = ' '.join([db['\n'], second])
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else:
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db['\n'] = second
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self._flush(db)
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def getFirstPair(self, channel):
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db = self._getDb(channel)
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firsts = db['\n \n'].split()
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if firsts:
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if firsts:
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return ('\n', random.choice(firsts))
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else:
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raise KeyError, 'No firsts for %s.' % channel
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else:
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raise KeyError, 'No firsts for %s.' % channel
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def _combine(self, first, second):
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return '%s %s' % (first, second)
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def getFollower(self, channel, first, second):
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db = self._getDb(channel)
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followers = db[self._combine(first, second)]
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follower = random.choice(followers.split(' '))
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return (follower, follower == '\n')
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def firsts(self, channel):
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db = self._getDb(channel)
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if db.has_key('\n \n'):
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return len(sets.Set(db['\n \n'].split()))
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else:
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return 0
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def lasts(self, channel):
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db = self._getDb(channel)
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if db.has_key('\n'):
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return len(sets.Set(db['\n'].split()))
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else:
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return 0
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def pairs(self, channel):
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db = self._getDb(channel)
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pairs = [k for k in db.keys() if '\n' not in k]
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return len(pairs)
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def follows(self, channel):
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db = self._getDb(channel)
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follows = [len(v.split()) for (k,v) in db.iteritems() if '\n' not in k]
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return sum(follows)
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MarkovDB = plugins.DB('Markov', {'anydbm': DbmMarkovDB})
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class MarkovWorkQueue(threading.Thread):
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def __init__(self, *args, **kwargs):
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name = 'Thread #%s (MarkovWorkQueue)' % world.threadsSpawned
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world.threadsSpawned += 1
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threading.Thread.__init__(self, name=name)
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self.db = MarkovDB(*args, **kwargs)
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self.q = Queue.Queue()
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self.killed = False
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self.setDaemon(True)
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self.start()
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def die(self):
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self.killed = True
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self.q.put(None)
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def enqueue(self, f):
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self.q.put(f)
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def run(self):
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while not self.killed:
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f = self.q.get()
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if f is not None:
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f(self.db)
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self.db.close()
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class Markov(callbacks.Privmsg):
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def __init__(self):
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self.q = MarkovWorkQueue()
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self.__parent = super(Markov, self)
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self.__parent.__init__()
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self.lastSpoke = time.time()
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def die(self):
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self.q.die()
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self.__parent.die()
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def tokenize(self, m):
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if ircmsgs.isAction(m):
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return ircmsgs.unAction(m).split()
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elif ircmsgs.isCtcp(m):
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return []
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else:
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return m.args[1].split()
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def doPrivmsg(self, irc, msg):
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channel = msg.args[0]
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if irc.isChannel(channel):
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canSpeak = False
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now = time.time()
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throttle = self.registryValue('randomSpeaking.throttleTime',
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channel)
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prob = self.registryValue('randomSpeaking.probability', channel)
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delay = self.registryValue('randomSpeaking.maxDelay', channel)
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irc = callbacks.SimpleProxy(irc, msg)
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if now > self.lastSpoke + throttle:
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canSpeak = True
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if canSpeak and random.random() < prob:
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f = self._markov(channel, irc, private=True, to=channel)
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schedule.addEvent(lambda: self.q.enqueue(f), now + delay)
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self.lastSpoke = now + delay
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words = self.tokenize(msg)
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words.insert(0, '\n')
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words.insert(0, '\n')
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words.append('\n')
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# This shouldn't happen often (CTCP messages being the possible exception)
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if not words or len(words) == 3:
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return
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def doPrivmsg(db):
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for (first, second, follower) in window(words, 3):
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db.addPair(channel, first, second, follower)
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self.q.enqueue(doPrivmsg)
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def _markov(self, channel, irc, word1=None, word2=None, **kwargs):
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def f(db):
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minLength = self.registryValue('minChainLength', channel)
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maxTries = self.registryValue('maxAttempts', channel)
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while maxTries > 0:
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maxTries -= 1;
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if word1 and word2:
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givenArgs = True
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words = [word1, word2]
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elif word1 or word2:
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# Can't just "raise callbacks.ArgumentError" because
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# exception is thrown in MarkovQueue, where it isn't
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# caught and no message is sent to the server
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irc.reply(self.getCommandHelp('markov'))
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return
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else:
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givenArgs = False
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try:
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# words is of the form ['\r', word]
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words = list(db.getFirstPair(channel))
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except KeyError:
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irc.error('I don\'t have any first pairs for %s.' %
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channel)
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return # We can't use raise here because the exception
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# isn't caught and therefore isn't sent to the
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# server
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follower = words[-1]
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last = False
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resp = []
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while not last:
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resp.append(follower)
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try:
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(follower,last) = db.getFollower(channel, words[-2],
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words[-1])
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except KeyError:
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irc.error('I found a broken link in the Markov chain. '
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' Maybe I received two bad links to start '
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'the chain.')
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return # ditto here re: Raise
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words.append(follower)
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if givenArgs:
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if len(words[:-1]) >= minLength:
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irc.reply(' '.join(words[:-1]), **kwargs)
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return
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else:
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continue
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else:
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if len(resp) >= minLength:
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irc.reply(' '.join(resp), **kwargs)
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return
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else:
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continue
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irc.error('I was unable to generate a Markov chain at least %s '
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'long.' % utils.nItems('word', minLength))
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return f
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def markov(self, irc, msg, args, channel, word1, word2):
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"""[<channel>] [word1 word2]
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Returns a randomly-generated Markov Chain generated sentence from the
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data kept on <channel> (which is only necessary if not sent in the
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channel itself). If word1 and word2 are specified, they will be used
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to start the Markov chain.
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"""
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f = self._markov(channel, irc, word1, word2)
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self.q.enqueue(f)
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markov = wrap(markov, ['channeldb', optional('something'),
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additional('something')])
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def firsts(self, irc, msg, args, channel):
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"""[<channel>]
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Returns the number of Markov's first links in the database for
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<channel>.
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"""
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def firsts(db):
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s = 'There are %s firsts in my Markov database for %s.'
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irc.reply(s % (db.firsts(channel), channel))
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self.q.enqueue(firsts)
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firsts = wrap(firsts, ['channeldb'])
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def lasts(self, irc, msg, args, channel):
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"""[<channel>]
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Returns the number of Markov's last links in the database for
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<channel>.
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"""
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def lasts(db):
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s = 'There are %s lasts in my Markov database for %s.'
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irc.reply(s % (db.lasts(channel), channel))
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self.q.enqueue(lasts)
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lasts = wrap(lasts, ['channeldb'])
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def pairs(self, irc, msg, args, channel):
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"""[<channel>]
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Returns the number of Markov's chain links in the database for
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<channel>.
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"""
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def pairs(db):
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s = 'There are %s pairs in my Markov database for %s.'
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irc.reply(s % (db.pairs(channel), channel))
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self.q.enqueue(pairs)
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pairs = wrap(pairs, ['channeldb'])
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def follows(self, irc, msg, args, channel):
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"""[<channel>]
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Returns the number of Markov's third links in the database for
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<channel>.
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"""
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def follows(db):
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s = 'There are %s follows in my Markov database for %s.'
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irc.reply(s % (db.follows(channel), channel))
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self.q.enqueue(follows)
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follows = wrap(follows, ['channeldb'])
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def stats(self, irc, msg, args, channel):
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"""[<channel>]
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Returns all stats (firsts, lasts, pairs, follows) for <channel>'s
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Markov database.
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"""
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def stats(db):
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s = '; '.join(['Firsts: %s', 'Lasts: %s', 'Pairs: %s',
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'Follows: %s'])
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irc.reply(s % (db.firsts(channel), db.lasts(channel),
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db.pairs(channel), db.follows(channel)))
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self.q.enqueue(stats)
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stats = wrap(stats, ['channeldb'])
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Class = Markov
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# vim:set shiftwidth=4 tabstop=8 expandtab textwidth=78:
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