Limnoria/plugins/Markov.py

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#!/usr/bin/env python
###
# Copyright (c) 2002-2004, Jeremiah Fincher
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# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# * Redistributions of source code must retain the above copyright notice,
# this list of conditions, and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice,
# this list of conditions, and the following disclaimer in the
# documentation and/or other materials provided with the distribution.
# * Neither the name of the author of this software nor the name of
# contributors to this software may be used to endorse or promote products
# derived from this software without specific prior written consent.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
# ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
# LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
# CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
# SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
# INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
# CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
# ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
# POSSIBILITY OF SUCH DAMAGE.
###
"""
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Silently listens to a channel, building an SQL database of Markov Chains for
later hijinks. To read more about Markov Chains, check out
<http://www.cs.bell-labs.com/cm/cs/pearls/sec153.html>. When the database is
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
import Queue
import anydbm
import random
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import os.path
import threading
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import supybot.world as world
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import supybot.ircmsgs as ircmsgs
import supybot.ircutils as ircutils
import supybot.privmsgs as privmsgs
import supybot.callbacks as callbacks
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class MarkovDBInterface(object):
def close(self):
pass
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def addPair(self, channel, first, second, follower,
isFirst=False, isLast=False):
pass
def getFirstPair(self, channel):
pass
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def getPair(self, channel, first, second):
# Returns (follower, last) tuple.
pass
class SqliteMarkovDB(object):
def addPair(self, channel, first, second, follower,
isFirst=False, isLast=False):
pass
def getFirstPair(self, channel):
pass
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def getFollower(self, channel, first, second):
# Returns (follower, last) tuple.
pass
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class DbmMarkovDB(object):
def __init__(self):
self.dbs = ircutils.IrcDict()
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def close(self):
for db in self.dbs.values():
db.close()
def _getDb(self, channel):
if channel not in self.dbs:
# Stupid anydbm seems to append .db to the end of this.
filename = plugins.makeChannelFilename('DbmMarkovDB', channel)
# To keep the code simpler for addPair, I decided not to make
# self.dbs[channel]['firsts'] and ['lasts']. Instead, we'll pad
# the words list being sent to addPair such that ['\n \n'] will be
# ['firsts'] and ['\n'] will be ['lasts']. This also means isFirst
# and isLast aren't necessary, but they'll be left alone in case
# one of the other Db formats uses them or someone decides that I
# was wrong and changes my code.
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self.dbs[channel] = anydbm.open(filename, 'c')
return self.dbs[channel]
def _flush(self, db):
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if hasattr(db, 'sync'):
db.sync()
if hasattr(db, 'flush'):
db.flush()
def addPair(self, channel, first, second, follower,
isFirst=False, isLast=False):
db = self._getDb(channel)
combined = self._combine(first, second)
if db.has_key(combined): # EW!
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db[combined] = ' '.join([db[combined], follower])
else:
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db[combined] = follower
if follower == '\n':
if db.has_key('\n'):
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db['\n'] = ' '.join([db['\n'], second])
else:
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db['\n'] = second
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self._flush(db)
def getFirstPair(self, channel):
db = self._getDb(channel)
firsts = db['\n \n'].split()
if firsts:
if firsts:
return ('\n', random.choice(firsts))
else:
raise KeyError, 'No firsts for %s.' % channel
else:
raise KeyError, 'No firsts for %s.' % channel
def _combine(self, first, second):
return '%s %s' % (first, second)
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def getFollower(self, channel, first, second):
db = self._getDb(channel)
followers = db[self._combine(first, second)]
follower = random.choice(followers.split(' '))
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return (follower, follower == '\n')
def firsts(self, channel):
db = self._getDb(channel)
if db.has_key('\n \n'):
return len(sets.Set(db['\n \n'].split()))
else:
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return 0
def lasts(self, channel):
db = self._getDb(channel)
if db.has_key('\n'):
return len(sets.Set(db['\n'].split()))
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else:
return 0
def pairs(self, channel):
db = self._getDb(channel)
pairs = [k for k in db.keys() if '\n' not in k]
return len(pairs)
def follows(self, channel):
db = self._getDb(channel)
follows = [len(v.split()) for (k,v) in db.iteritems() if '\n' not in k]
return sum(follows)
def MarkovDB():
return DbmMarkovDB()
class MarkovWorkQueue(threading.Thread):
def __init__(self, *args, **kwargs):
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name = 'Thread #%s (MarkovWorkQueue)' % world.threadsSpawned
world.threadsSpawned += 1
threading.Thread.__init__(self, name=name)
self.db = MarkovDB(*args, **kwargs)
self.q = Queue.Queue()
self.killed = False
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self.setDaemon(True)
self.start()
def die(self):
self.killed = True
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self.q.put(None)
def enqueue(self, f):
self.q.put(f)
def run(self):
while not self.killed:
f = self.q.get()
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if f is not None:
f(self.db)
self.db.close()
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class Markov(callbacks.Privmsg):
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def __init__(self):
self.q = MarkovWorkQueue()
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callbacks.Privmsg.__init__(self)
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def die(self):
self.q.die()
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def tokenize(self, m):
if ircmsgs.isAction(m):
return ircmsgs.unAction(m).split()
elif ircmsgs.isCtcp(m):
return []
else:
return m.args[1].split()
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def doPrivmsg(self, irc, msg):
channel = msg.args[0]
if ircutils.isChannel(channel):
words = self.tokenize(msg)
words.insert(0, '\n')
words.insert(0, '\n')
words.append('\n')
# This shouldn't happen often (CTCP messages being the possible exception)
if not words or len(words) == 3:
return
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def doPrivmsg(db):
for (first, second, follower) in window(words, 3):
db.addPair(channel, first, second, follower)
self.q.enqueue(doPrivmsg)
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def markov(self, irc, msg, args):
"""[<channel>] [word1 word2]
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Returns a randomly-generated Markov Chain generated sentence from the
data kept on <channel> (which is only necessary if not sent in the
channel itself). If word1 and word2 are specified, they will be used
to start the Markov chain.
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"""
channel = privmsgs.getChannel(msg, args)
(word1, word2) = privmsgs.getArgs(args, required=0, optional=2)
def markov(db):
if word1 and word2:
givenArgs = True
words = [word1, word2]
else:
givenArgs = False
try:
# words is of the form ['\r', word]
words = list(db.getFirstPair(channel))
except KeyError:
irc.error('I don\'t have any first pairs for %s.' %channel)
return
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follower = words[-1]
last = False
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resp = []
while not last:
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resp.append(follower)
try:
(follower,last) = db.getFollower(channel, words[-2],
words[-1])
except KeyError:
irc.error('I found a broken link in the Markov chain. '
'Maybe I received two bad links to start the '
'chain.')
return
words.append(follower)
if givenArgs:
irc.reply(' '.join(words))
else:
irc.reply(' '.join(resp))
self.q.enqueue(markov)
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def firsts(self, irc, msg, args):
"""[<channel>]
Returns the number of Markov's first links in the database for
<channel>.
"""
channel = privmsgs.getChannel(msg, args)
def firsts(db):
s = 'There are %s firsts in my Markov database for %s.'
irc.reply(s % (db.firsts(channel), channel))
self.q.enqueue(firsts)
def lasts(self, irc, msg, args):
"""[<channel>]
Returns the number of Markov's last links in the database for
<channel>.
"""
channel = privmsgs.getChannel(msg, args)
def lasts(db):
s = 'There are %s lasts in my Markov database for %s.'
irc.reply(s % (db.lasts(channel), channel))
self.q.enqueue(lasts)
def pairs(self, irc, msg, args):
"""[<channel>]
Returns the number of Markov's chain links in the database for
<channel>.
"""
channel = privmsgs.getChannel(msg, args)
def pairs(db):
s = 'There are %s pairs in my Markov database for %s.'
irc.reply(s % (db.pairs(channel), channel))
self.q.enqueue(pairs)
def follows(self, irc, msg, args):
"""[<channel>]
Returns the number of Markov's third links in the database for
<channel>.
"""
channel = privmsgs.getChannel(msg, args)
def follows(db):
s = 'There are %s follows in my Markov database for %s.'
irc.reply(s % (db.follows(channel), channel))
self.q.enqueue(follows)
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Class = Markov
# vim:set shiftwidth=4 tabstop=8 expandtab textwidth=78: