def __init__(self, name):
from curtana.lib.parser_aliases import RE, R
B.Base.__init__(self, ApiMod.from_name(name))
vocab.Vocabulary.__init__(self)
self.screen_name = name
self.talked = []
self.assoc_table = Counter()
self.markov_table = G.Table()
self.load(B.PATH)
self.pattern = (RE("もしゃもしゃ|モシャモシャ|もふもふ|モフモフ") >> R(self.response0)
| RE("(^|む|[^く])ぎゅ[っうぅー]?") >> R(self.response1)
| RE("なでなで|ナデナデ") >> R(self.response2)
| RE("ぺろぺろ|ペロペロ|ちゅっちゅ｜チュッチュ") >> R(self.response3)
)
self.voluntary = (RE("((^|[^ァ-ヾ])リサ|(^|[^ぁ-ゞ])りさ)(ちゃん|チャン)")
>> R(compose(star(OP.rshift), fanout(self.chan_ha_fuyou, self.favorite)))
#|RE("((^|[^ァ-ヾ])リサ|^りさ)") >> R(self.favorite)
)
import cPickle
import re
import datetime
import operator as OP
import random
from itertools import imap
from functools import partial
from collections import Counter
import lisabot3.lisa.generator as G
import lisabot3.responder as B
from lisabot3.lisa import vocab
GROUPER = BufferBy(compose(partial(OP.lt, 140 - 6), compose(sum, Map(len))))
ENTITIES = re.compile("[QR]T @\w+.*|\.(@\w+ )+|http:\/\/(\w+|\.|\/)*|@\w+")
class ResponderLisa(B.Base, B.Storable, vocab.Vocabulary):
store_attributes = ["impression", "talked", "markov_table", "assoc_table"]
def __init__(self, name):
from curtana.lib.parser_aliases import RE, R
B.Base.__init__(self, ApiMod.from_name(name))
vocab.Vocabulary.__init__(self)
self.screen_name = name
self.talked = []
self.assoc_table = Counter()
self.markov_table = G.Table()
self.load(B.PATH)