def generator():
#sched = scheduler.Scheduler()
#sched.schedule()
u = LoadUserData(conf_path)
table, footer = readReplyTable.read(exec_path + "/common/replyTable.json")
dbSession = model.startSession(u)
if False:
#if( sched.has_schedule() ):
str = doSchedule(sched)
else:
rep = dbSession.query(model.RetQueue)
if (rep.count() > 0):
sentence, reply_id = reply.do(table, rep, dbSession)
else:
#try:
# 予定もreplyもないならhotでも取り出してマルコフ連鎖する
# str,sl = CreateMarkovSentenceWithHot(dbSession)
#except:
# print "Unexpected error:", sys.exc_info()[0]
str, sl = vsearch.depthFirstSearch2("yystart", "yyend", 15)
print_d(str)
print_d(len(sl))
asl = afterEffect(sl, footer)
sentence = ""
reply_id = -1
for i in asl:
sentence += i
sendMessage(sentence, reply_id)
def main():
# twitterから発言を取ってきてDBに格納する
userdata = getAuthData(conf_path)
tw = auth_api.connect(userdata["consumer_token"],
userdata["consumer_secret"], exec_path + "/common/")
dbSession = model.startSession(userdata)
page_number = 0
update_flag = True
while update_flag:
update_flag = False
l = tw.home_timeline(page=page_number)
page_number += 1
if page_number > 10: break
for s in l:
#if s.author.screen_name == userdata["user"]:continue
jTime = s.created_at + datetime.timedelta(hours=9)
name = unicode(s.user.screen_name)
query = dbSession.query(model.Tweet).filter(
and_(model.Tweet.datetime == jTime, model.Tweet.user == name))
if (query.count() > 0): continue
if (isNGUser(name)): continue
update_flag = True
t = model.Tweet()
t.user = name
t.text = s.text
t.datetime = jTime
t.replyID = s.in_reply_to_status_id
t.tweetID = s.id
#print "id:",s.id,
dbSession.add(t)
dbSession.commit()
def quickAnalyze():
# dbからデータを読み込む
u = LoadUserData(conf_path)
dbSession = model.startSession(u)
table, footer = readReplyTable.read(exec_path + "/common/replyTable.json")
regexes = makeRegexes(table)
# 前回の更新時間から現在までのデータを入手する
q = dbSession.query(model.Tweet)
tq = q.filter(model.Tweet.isAnalyze == 0)[:10000]
for t in tq:
#1発言毎
t.text = RemoveCharacter(t.text)
#print_d2(t.text)
analyzeReply2(t,dbSession,table,regexes)
t.isAnalyze = 1
t_enc = t.text.encode(g_mecabencode,'ignore')
sarray = mecab.sparse_all(t_enc,mecabPath).split("\n")
sarray2 = connectUnderScore(sarray)
markovWordList,topNWordList = TakeWordList(sarray)
#最近出た名詞貯める
for tn in topNWordList:
hot = model.Hot()
hot.word = unicode(tn,g_systemencode)
dbSession.add(hot)
dbSession.add(t)
dbSession.commit()
def generator():
#sched = scheduler.Scheduler()
#sched.schedule()
u = LoadUserData(conf_path)
table, footer= readReplyTable.read(exec_path+"/common/replyTable.json")
dbSession = model.startSession(u)
if False:
#if( sched.has_schedule() ):
str = doSchedule(sched)
else:
rep = dbSession.query(model.RetQueue)
if( rep.count() > 0 ):
sentence, reply_id = reply.do(table, rep, dbSession)
else:
#try:
# 予定もreplyもないならhotでも取り出してマルコフ連鎖する
# str,sl = CreateMarkovSentenceWithHot(dbSession)
#except:
# print "Unexpected error:", sys.exc_info()[0]
str,sl = vsearch.depthFirstSearch2("yystart","yyend",15)
print_d(str)
print_d(len(sl))
asl = afterEffect(sl,footer)
sentence = ""
reply_id = -1
for i in asl:
sentence += i
sendMessage(sentence, reply_id)
def main():
#sys.stdout = codecs.getwriter('utf_8')(sys.stdout)
user = getAuthData(conf_path)
session = model.startSession(user)
api = auth_api.connect(user["consumer_token"], user["consumer_secret"])
#api = tweepy_connect.connect()
remove_at(session)
def quickGenerate():
#sched = scheduler.Scheduler()
#sched.schedule()
u = LoadUserData(conf_path)
table, footer= readReplyTable.read(exec_path+"/common/replyTable.json")
dbSession = model.startSession(u)
if False:
if( sched.has_schedule() ):
str = doSchedule(sched)
else:
rep = dbSession.query(model.RetQueue)
if( rep.count() > 0 ):
str, reply_id = reply.do(table, rep,dbSession)
sendMessage(str,reply_id)
def main(str, newSession=None):
global session
sys.stdout = codecs.getwriter('utf_8')(sys.stdout)
#print "conf_path", conf_path
user = getAuthData(conf_path)
if session == None:
if newSession == None:
session = model.startSession(user)
else:
session = newSession
api = auth_api.connect(user["consumer_token"], user["consumer_secret"],\
common_path)
#api = tweepy_connect.connect()
return pickup_reply(str)
def main(str, newSession=None):
global session
sys.stdout = codecs.getwriter('utf_8')(sys.stdout)
#print "conf_path", conf_path
user = getAuthData(conf_path)
if session == None:
if newSession == None:
session = model.startSession(user)
else:
session = newSession
api = auth_api.connect(user["consumer_token"], user["consumer_secret"],\
common_path)
#api = tweepy_connect.connect()
return pickup_reply(str)
def quickGenerate():
#sched = scheduler.Scheduler()
#sched.schedule()
u = LoadUserData(conf_path)
table, footer= readReplyTable.read(exec_path+"/common/replyTable.json")
dbSession = model.startSession(u)
if False:
if( sched.has_schedule() ):
str = doSchedule(sched)
else:
rep = dbSession.query(model.RetQueue)
if( rep.count() > 0 ):
str, reply_id = reply.do(table, rep,dbSession)
sendMessage(str,reply_id)
def main():
# twitterから発言を取ってきてDBに格納する
userdata = read_json(conf_path)
g_ng_char = read_json(ng_char_path)
tw = auth_api.connect(userdata["consumer_token"],
userdata["consumer_secret"], exec_path + "/common/")
#print tw.rate_limit_status()
dbSession = model.startSession(userdata)
page_number = 0
update_flag = True
while update_flag:
update_flag = False
page_number += 1
if page_number > 1: break
#l = tw.home_timeline(page = page_number, count=10)
#Toyko座標ベタ打ち
woeid = tw.trends_closest(35.652832, 139.839478)[0]['woeid']
trends_place = tw.trends_place(woeid)
l = trends_place[0]['trends']
for s in l:
trend = s['name']
if trend.startswith("#"): trend = trend[1:]
#print(trend)
update_flag = check_text(trend, dbSession)
if (not (update_flag)): continue
if (random.randint(0, 1)):
text = "な、なによ……! ニコだって" + trend +\
"くらいできるんだから！！"
else:
text = trend + "と言えば？\nニコニー♪\nかわいい" +\
trend +"と言えば？\nニコニー♪"
try:
tw.update_status(text)
print("trend " + trend)
except tweepy.TweepError:
pass
#print("flag: ", update_flag)
if update_flag: break
dbSession.commit()
def analyze():
# dbからデータを読み込む
userdata = getAuthData(conf_path)
dbSession = model.startSession(userdata)
# 前回の更新時間から現在までのデータを入手する
q = dbSession.query(model.Tweet)
# ToDo:ここ、1000件ずつ取って、一定件数溜まったらDBに書き込むように変えられないか？
insertData = defaultdict(int)
while True:
tq = q.filter(model.Tweet.isAnalyze == 1)[:1000]
i = 0
if len(tq) == 0:
break
for t in tq:
# 1発言毎
t.text = removeCharacter(t.text)
t.isAnalyze = 2
t_enc = t.text.encode(g_mecabencode, "ignore")
sarray = mecab.sparse_all(t_enc, mecabPath).split("\n")
sarray2 = connectUnderScore(sarray)
markovWordList, topNWordList = takeWordList(sarray2)
print len(markovWordList)
# 最近出た名詞貯める
dbSession.add(t)
appendMarkov(markovWordList, dbSession, insertData)
# appendCollocation(markovWordList,dbSession)
i += 1
if i >= 1000:
insertMarkovData2DB(dbSession, insertData)
dbSession.commit()
insertData = defaultdict(int)
i = 0
if len(insertData) > 0:
insertMarkovData2DB(dbSession, insertData)
dbSession.commit()
def analyze():
# dbからデータを読み込む
userdata = getAuthData(conf_path)
dbSession = model.startSession(userdata)
# 前回の更新時間から現在までのデータを入手する
q = dbSession.query(model.Tweet)
# ToDo:ここ、1000件ずつ取って、一定件数溜まったらDBに書き込むように変えられないか？
insertData = defaultdict(int)
while (True):
tq = q.filter(model.Tweet.isAnalyze == 1)[:1000]
i = 0
if len(tq) == 0: break
for t in tq:
#1発言毎
t.text = removeCharacter(t.text)
t.isAnalyze = 2
t_enc = t.text.encode(g_mecabencode, 'ignore')
sarray = mecab.sparse_all(t_enc, mecabPath).split("\n")
sarray2 = connectUnderScore(sarray)
markovWordList, topNWordList = takeWordList(sarray2)
print len(markovWordList)
#最近出た名詞貯める
dbSession.add(t)
appendMarkov(markovWordList, dbSession, insertData)
#appendCollocation(markovWordList,dbSession)
i += 1
if i >= 1000:
insertMarkovData2DB(dbSession, insertData)
dbSession.commit()
insertData = defaultdict(int)
i = 0
if len(insertData) > 0:
insertMarkovData2DB(dbSession, insertData)
dbSession.commit()
def main():
# twitterから発言を取ってきてDBに格納する
userdata = getAuthData(conf_path)
tw = auth_api.connect(userdata["consumer_token"],
userdata["consumer_secret"], exec_path+"/common/")
dbSession = model.startSession(userdata)
page_number = 0
update_flag = True
while update_flag:
update_flag = False
l = tw.home_timeline(page = page_number, count=200)
page_number += 1
if page_number > 10: break
for s in l:
#if s.author.screen_name == userdata["user"]:continue
jTime = s.created_at + datetime.timedelta(hours = 9)
name = unicode(s.user.screen_name)
query = dbSession.query(model.Tweet).filter(
and_(model.Tweet.datetime== jTime,
model.Tweet.user==name ))
if( query.count() > 0 ): continue
if( isNGUser(name) ): continue
update_flag = True
t = model.Tweet()
t.user = name
t.text = s.text
t.datetime = jTime
t.replyID = s.in_reply_to_status_id
t.tweetID = s.id
#print "id:",s.id,
dbSession.add(t)
dbSession.commit()
dbSession.close()
