mirror of
https://github.com/Mikaela/Limnoria.git
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234 lines
7.8 KiB
Python
234 lines
7.8 KiB
Python
#!/usr/bin/env python
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###
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# Copyright (c) 2002, 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 later
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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 plugins
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import anydbm
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import random
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import os.path
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import conf
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import world
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import ircmsgs
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import ircutils
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import privmsgs
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import callbacks
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class MarkovDB(object):
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def __init__(self):
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self.dbs = {}
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def die(self):
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for db in self.dbs.values():
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try:
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db.close()
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except:
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continue
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def _getDb(self, channel):
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channel = channel.lower()
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if channel not in self.dbs:
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filename = '%s-Markov.db' % channel
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filename = os.path.join(conf.supybot.directories.data(), filename)
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self.dbs[channel] = anydbm.open(filename, 'c')
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return self.dbs[channel]
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def __getitem__(self, (channel, item)):
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return self._getDb(channel)[item]
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def __setitem__(self, (channel, item), value):
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self._getDb(channel)[item] = value
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def getNumberOfPairs(self, channel):
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try:
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# Minus one, because we have a key storing the first pairs.
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return len(self[channel.lower()]) - 1
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except KeyError:
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return 0
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def getNumberOfFirstPairs(self, channel):
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try:
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return len(self[channel, ''].split())
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except KeyError:
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return 0
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def getFirstPair(self, channel):
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try:
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pairs = self[channel, ''].split()
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except KeyError:
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raise ValueError('No starting pairs in the database.')
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pair = random.choice(pairs)
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return pair.split('\x00', 1)
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def getFollower(self, channel, first, second):
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pair = '%s %s' % (first, second)
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try:
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followers = self[channel, pair].split()
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except KeyError:
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return '\x00'
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return random.choice(followers)
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def addFirstPair(self, channel, first, second):
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pair = '%s\x00%s' % (first, second)
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try:
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startingPairs = self[channel, '']
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except KeyError:
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startingPairs = ''
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self[channel, ''] = '%s%s ' % (startingPairs, pair)
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def addPair(self, channel, first, second, follower):
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pair = '%s %s' % (first, second)
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try:
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followers = self[channel, pair]
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except KeyError:
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followers = ''
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self[channel, pair] = '%s%s ' % (followers, follower)
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class Markov(callbacks.Privmsg):
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def __init__(self):
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callbacks.Privmsg.__init__(self)
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self.db = MarkovDB()
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def doPrivmsg(self, irc, msg):
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if not ircutils.isChannel(msg.args[0]):
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return
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channel = msg.args[0]
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if ircmsgs.isAction(msg):
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words = ircmsgs.unAction(msg).split()
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words.insert(0, '\x00nick')
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#words.insert(0, msg.nick)
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else:
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words = msg.args[1].split()
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isFirst = True
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for (first, second, follower) in window(words, 3):
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if isFirst:
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self.db.addFirstPair(channel, first, second)
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isFirst = False
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self.db.addPair(channel, first, second, follower)
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if not isFirst: # i.e., if the loop iterated at all.
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self.db.addPair(channel, second, follower, '\x00')
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_maxMarkovLength = 80
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_minMarkovLength = 7
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def markov(self, irc, msg, args):
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"""[<channel>]
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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).
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"""
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channel = privmsgs.getChannel(msg, args)
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try:
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pair = self.db.getFirstPair(channel)
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except ValueError:
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irc.error('I have no records for this channel.')
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return
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words = [pair[0], pair[1]]
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while len(words) < self._maxMarkovLength:
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follower = self.db.getFollower(channel, words[-2], words[-1])
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if follower == '\x00':
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if len(words) < self._minMarkovLength:
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pair = self.db.getFirstPair(channel)
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words = [pair[0], pair[1]]
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else:
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break
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else:
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words.append(follower)
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if words[0] == '\x00nick':
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words[0] = choice(irc.state.channels[channel].users)
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irc.reply(' '.join(words))
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def pairs(self, irc, msg, args):
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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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channel = privmsgs.getChannel(msg, args)
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n = self.db.getNumberOfPairs(channel)
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s = 'There are %s pairs in my Markov database for %s' % (n, channel)
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irc.reply(s)
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def firsts(self, irc, msg, args):
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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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channel = privmsgs.getChannel(msg, args)
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n = self.db.getNumberOfFirstPairs(channel)
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s = 'There are %s first pairs in my Markov database for %s'%(n,channel)
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irc.reply(s)
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# def follows(self, irc, msg, args):
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# """[<channel>]
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#
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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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# channel = privmsgs.getChannel(msg, args)
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# db = self._getDb(channel)
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# cursor = db.cursor()
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# cursor.execute("""SELECT COUNT(*) FROM follows""")
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# n = int(cursor.fetchone()[0])
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# s = 'There are %s follows in my Markov database for %s' % (n, channel)
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# irc.reply(s)
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# def lasts(self, irc, msg, args):
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# """[<channel>]
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#
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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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# channel = privmsgs.getChannel(msg, args)
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# db = self._getDb(channel)
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# cursor = db.cursor()
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# cursor.execute("""SELECT COUNT(*) FROM follows WHERE word ISNULL""")
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# n = int(cursor.fetchone()[0])
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# s = 'There are %s lasts in my Markov database for %s' % (n, channel)
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# irc.reply(s)
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Class = Markov
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# vim:set shiftwidth=4 tabstop=8 expandtab textwidth=78:
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