Limnoria/plugins/Markov.py

219 lines
7.1 KiB
Python

#!/usr/bin/env python
###
# Copyright (c) 2002, Jeremiah Fincher
# 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.
###
"""
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.
"""
__revision__ = "$Id$"
import supybot.plugins as plugins
import Queue
import anydbm
import random
import os.path
import threading
import supybot.ircmsgs as ircmsgs
import supybot.ircutils as ircutils
import supybot.privmsgs as privmsgs
import supybot.callbacks as callbacks
class MarkovDBInterface(object):
def close(self):
pass
def addPair(self, channel, first, second, follower,
isFirst=False, isLast=False):
pass
def getFirstPair(self, channel):
pass
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
def getFollower(self, channel, first, second):
# Returns (follower, last) tuple.
pass
class DbmMarkovDB(object):
def __init__(self):
self.dbs = ircutils.IrcDict()
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.
self.dbs[channel] = anydbm.open('%s-DbmMarkovDB' % channel, 'c')
self.dbs[channel]['lasts'] = ''
self.dbs[channel]['firsts'] = ''
return self.dbs[channel]
def _addFirst(self, db, combined):
db['firsts'] = db['firsts'] + (combined + '\n')
def _addLast(self, db, second, follower):
combined = self._combine(second, follower)
db['lasts'] = db['lasts'] + (combined + '\n')
def addPair(self, channel, first, second, follower,
isFirst=False, isLast=False):
db = self._getDb(channel)
combined = self._combine(first, second)
if isFirst:
self._addFirst(db, combined)
elif isLast:
self._addLast(db, second, follower)
else:
if db.has_key(combined): # EW!
db[combined] = db[combined] + (' ' + follower)
else:
db[combined] = follower
#db.flush()
def getFirstPair(self, channel):
db = self._getDb(channel)
firsts = db['firsts'].splitlines()
if firsts:
firsts.pop() # Empty line.
if firsts:
return random.choice(firsts).split()
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)
def getFollower(self, channel, first, second):
db = self._getDb(channel)
followers = db[self._combine(first, second)]
follower = random.choice(followers.split())
if self._combine(second, follower) in db['lasts']:
last = True
else:
last = False
return (follower, last)
def MarkovDB():
return DbmMarkovDB()
class MarkovWorkQueue(threading.Thread):
def __init__(self, *args, **kwargs):
threading.Thread.__init__(self)
self.db = MarkovDB(*args, **kwargs)
self.q = Queue.Queue()
self.killed = False
self.start()
def die(self):
self.killed = True
def enqueue(self, f):
self.q.put(f)
def run(self):
while not self.killed:
f = self.q.get()
f(self.db)
self.db.close()
class Markov(callbacks.Privmsg):
def __init__(self):
self.q = MarkovWorkQueue()
callbacks.Privmsg.__init__(self)
def die(self):
self.q.die()
def tokenize(self, s):
# XXX: Should this be smarter?
return s.split()
def doPrivmsg(self, irc, msg):
channel = msg.args[0]
if ircutils.isChannel(channel):
words = self.tokenize(msg.args[1])
if len(words) >= 3:
def doPrivmsg(db):
db.addPair(channel, words[0], words[1], words[2],
isFirst=True)
db.addPair(channel, words[-3], words[-2], words[-1],
isLast=True)
del words[0] # Remove first.
del words[-1] # Remove last.
for (first, second, follower) in window(words, 3):
db.addPair(channel, first, second, follower)
self.q.enqueue(doPrivmsg)
def markov(self, irc, msg, args):
"""[<channel>]
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).
"""
channel = privmsgs.getChannel(msg, args)
def markov(db):
try:
words = list(db.getFirstPair(channel))
except KeyError:
irc.error('I don\'t have any first pairs for %s.' % channel)
return
last = False
while not last:
(follower,last) = db.getFollower(channel, words[-2], words[-1])
words.append(follower)
irc.reply(' '.join(words))
self.q.enqueue(markov)
Class = Markov