Limnoria/plugins/Markov.py

###
# Copyright (c) 2002-2004, Jeremiah Fincher
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# modification, are permitted provided that the following conditions are met:
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#     derived from this software without specific prior written consent.
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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.
"""

__revision__ = "$Id$"

import supybot.plugins as plugins

import sets
import Queue
import anydbm
import random
import os.path
import threading

import supybot.world as world
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

    def firsts(self, channel):
        pass

    def lasts(self, channel):
        pass

    def pairs(self, channel):
        pass

    def follows(self, channel):
        pass

class SqliteMarkovDB(object):
    def __init__(self, filename):
        self.dbs = ircutils.IrcDict()
        self.filename = filename

    def close(self):
        for db in self.dbs.values():
            db.close()

    def _getDb(self, channel):
        try:
            import sqlite
        except ImportError:
            raise callbacks.Error, 'You need to have PySQLite installed to '\
                                   'use this plugin.  Download it at '\
                                   '<http://pysqlite.sf.net/>'
        if channel not in self.dbs:
            filename = plugins.makeChannelFilename(self.filename, channel)
            if os.path.exists(filename):
                self.dbs[channel] = sqlite.connect(filename)
                return self.dbs[channel]
            #else:
            self.dbs[channel] = sqlite.connect(filename)
            cursor = self.dbs[channel].cursor()
            # TODO Finish the rest of the implementation
        return self.dbs[channel]

    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

    def firsts(self, channel):
        pass

    def lasts(self, channel):
        pass

    def pairs(self, channel):
        pass

    def follows(self, channel):
        pass


class DbmMarkovDB(object):
    def __init__(self, filename):
        self.dbs = ircutils.IrcDict()
        ## Stupid anydbm seems to append .db to the end of this.
        #self.filename = filename.replace('.db', '')
        self.filename = filename

    def close(self):
        for db in self.dbs.values():
            db.close()

    def _getDb(self, channel):
        if channel not in self.dbs:
            filename = plugins.makeChannelFilename(self.filename, 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.
            self.dbs[channel] = anydbm.open(filename, 'c')
        return self.dbs[channel]

    def _flush(self, db):
        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!
            db[combined] = ' '.join([db[combined], follower])
        else:
            db[combined] = follower
        if follower == '\n':
            if db.has_key('\n'):
                db['\n'] = ' '.join([db['\n'], second])
            else:
                db['\n'] = second
        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)

    def getFollower(self, channel, first, second):
        db = self._getDb(channel)
        followers = db[self._combine(first, second)]
        follower = random.choice(followers.split(' '))
        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:
            return 0

    def lasts(self, channel):
        db = self._getDb(channel)
        if db.has_key('\n'):
            return len(sets.Set(db['\n'].split()))
        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)

MarkovDB = plugins.DB('Markov',
                      {'anydbm': DbmMarkovDB})

class MarkovWorkQueue(threading.Thread):
    def __init__(self, *args, **kwargs):
        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
        self.setDaemon(True)
        self.start()

    def die(self):
        self.killed = True
        self.q.put(None)

    def enqueue(self, f):
        self.q.put(f)

    def run(self):
        while not self.killed:
            f = self.q.get()
            if f is not None:
                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, m):
        if ircmsgs.isAction(m):
            return ircmsgs.unAction(m).split()
        elif ircmsgs.isCtcp(m):
            return []
        else:
            return m.args[1].split()

    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
            def doPrivmsg(db):
                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>] [word1 word2]

        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.
        """
        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
            follower = words[-1]
            last = False
            resp = []
            while not last:
                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)

    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)


Class = Markov

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