def index(request):
context = {}
# History 경로 생성
homepath = os.path.expanduser("~")
abs_chrome_path = os.path.join(homepath, 'AppData', 'Local', 'Google', 'Chrome', 'User Data', 'Default', 'History')
# History 파일 복사
shutil.copyfile(abs_chrome_path, abs_chrome_path+"_sample")
# 복사본 데이터 추출
con = sqlite3.connect(abs_chrome_path+"_sample")
cursor = con.cursor()
cursor.execute("SELECT term FROM keyword_search_terms")
term_data = cursor.fetchall()
# 형태소 분석
kiwi = Kiwi()
kiwi.prepare()
word_list = []
for term in term_data:
for word, tag, _, _ in kiwi.analyze(term[0], top_n=1)[0][0]:
if tag in ['NNG','NNP','NNB','SL']:
word_list.append(word)
# count
counts = Counter(word_list)
tags = counts.most_common()
# wordcloud
mask = plt.imread("./static/images/mask.jpg")
wc = WordCloud(font_path='./static/webfonts/NanumBarunGothicBold.ttf',
background_color='white',
width=800,
height=800,
mask=mask)
cloud = wc.generate_from_frequencies(dict(tags))
plt.figure(figsize=(10, 8))
plt.axis('off')
plt.imshow(cloud, interpolation="bilinear")
plt.savefig("./static/images/wordcloud_keyword.png", dpi=300, bbox_inches='tight')
# 상위 9개 단어
top9_list = []
for rank in range(9):
top9 = {}
top9['rank'] = rank+1
top9['word'] = tags[rank][0]
top9['count'] = tags[rank][1]
top9_list.append(top9)
context['top9'] = top9_list
return render(request, 'mainapp/index.html', context)
def test_kiwi(environ):
_, tagger = environ
kiwi = Kiwi()
kiwi.prepare()
for _, line in EXAMPLES:
res1 = tagger.tagSentence(line)[0]
res2 = kiwi.analyze(line)
res1 = [(m.surface, m.originalTag) for w in res1 for m in w]
res2 = [m[:2] for m in res2[0][0]]
assert res1 == res2
def prepare_kiwi(train_file):
"""
input: train file i.e. corpora
output: kiwi model
"""
numThread = 4
kiwi = Kiwi(numThread)
reader = ReaderExam(train_file)
minCount = 5
maxWordLength = 6
minScore = 0.25
kiwi.extractWords(reader.read, minCount, maxWordLength, minScore)
kiwi.prepare()
return kiwi
class kiwi_dictionary_n_fuction:
def __init__(self, path):
self.kiwi = Kiwi(options=Option.LOAD_DEFAULT_DICTIONARY
| Option.INTEGRATE_ALLOMORPH)
self.kiwi.load_user_dictionary(path)
self.kiwi.prepare()
self.josa = [
'JK', 'JKS', 'JKC', 'JKG', 'JKO', 'JKB', 'JKV', 'JKQ', 'JX', 'JC'
]
def get_noun(self, sen):
_, self.nn_list, _, _ = self.generate_morp_word(sen, 1)
return self.nn_list
# 문장 전체를 리스트형태로 띄어쓰기만 해서 리턴
def get_all_token(self, sen):
morp_list, _, _, _ = self.generate_morp_word(sen, 1)
return morp_list
# 문장 전체를 토큰화 후 문자열 리턴
def get_token_str(self, sen):
morp_list, _, _, _ = self.generate_morp_word(sen, 1)
string = ''.join(morp_list)
# if '\\' in self.string:
# self.string = self.string.translate({ord('\\'):'\\\\'})
return string
def get_vv(self, sen):
_, _, vv_list, _ = self.generate_morp_word(sen, 1)
return vv_list
def get_nn_list(self, sen):
_, nn_list, _, _ = self.generate_morp_word(sen, 1)
return nn_list
# 조사 없애고 나머지부분 문자열형태로 리턴.
def get_no_josa_token(
self, sen
): # EX) 관찰 가능 하 고 처리 가능 하 ᆫ 범위 내 문장 입력 받 어 정해진 형태 출력 제한 되 ᆫ 시간 내 출력 하 어야 하 ᆫ다는 제약 적 용도 고려 하 ᆫ 관점 이 다 .
_, _, _, nosa_list = self.generate_morp_word(sen, 1)
string = ''.join(nosa_list)
return string
# 튜플 리스트 리턴
def k_pos(
self, sentence
): # [('관찰', 'NNG'), ('가능', 'NNG'), ('하', 'XSA'), ('고', 'EC'), ('처리', 'NNG'), ('가능', 'NNG'), ('하', 'XSA'), ('ᆫ', 'ETM'), ('범위', 'NNG')]
tuple_list = []
result = self.kiwi.analyze(sentence, 1)
for i in result[0][0]:
word, pos = i[0], i[1]
new_tuple = (word, pos)
tuple_list.append(new_tuple)
return tuple_list
def k_analyze(self, sentence):
return self.kiwi.analyze(sentence, 1)
# 단순 단어만 리스트형태로 리턴
def k_morphs(self, sen): # ['관찰', '가능', '하', '고', '처리', '가능', '하' ... ..]
token_list = []
result = self.kiwi.analyze(sen, 1)
for i in result[0][0]:
token_list.append(i[0])
return token_list
# 문장에서 형태소를 뽑아냄
def generate_morp_word(self, sentence, analyze_num):
try:
result = self.kiwi.analyze(sentence, analyze_num)
morp_word_list = []
morp_nn_list = []
morp_vv_list = []
morp_not_josa_list = []
for i in range(0, analyze_num):
morp_word = ''
morp_nn = ''
morp_vv = ''
morp_not_josa = ''
nn = []
for word in result[i][0]:
morp_word += word[0]
morp_word += ' '
if word[1] not in self.josa:
morp_not_josa += word[0]
morp_not_josa += ' '
if word[1] in ['NNG', 'NNP', 'NNB', 'NP', 'NR', 'SL']:
morp_nn += word[0]
morp_nn += ' '
nn.append(word[0])
elif word[1] in ['VV', 'VA', 'VX', 'VCP', 'VCN']:
morp_vv += word[0]
morp_vv += ' '
else:
pass
morp_word_list.append(morp_word)
morp_nn_list.append(morp_nn)
morp_vv_list.append(morp_vv)
morp_not_josa_list.append(morp_not_josa)
return morp_word_list, morp_nn_list, morp_vv_list, morp_not_josa_list
except Exception as e:
print(e)
print("### ERROR 형태소 분석기 부분 에 뭐가 잘못된게 있는듯 ERROR ### ")
def __del__(self):
print("EXIT kiwi")
class Changer(object):
def __init__(self):
try:
self.kiwi = Kiwi()
self.kiwi.prepare()
except:
print("[INFO] please install kiwipiepy ")
self.replace = formaldic()
self.utils = Utils()
def dechanger(self, stc):
"""
change formal speech to informal
Args : str
"""
pattern = r'하세요|이예요|이에요|에요|예요|시겠어요|죠|합니까|습니까'
pattern = re.compile(pattern)
result = []
stc = self.utils._remove_blank(stc)
stc = self.utils._clean_up_tokenization(stc)
if len(re.findall(pattern, stc)) > 0:
tokens = self.kiwi.analyze(stc.replace(" ","|"))
key = informaldic().keys()
lk = list(key)
key2 = abnormaldic().keys()
ak = list(key2)
tmp = []
for token in tokens[0][0]:
if token[:2] in lk:
#key로 value
token = informaldic().get(token[:2])
if token[:2] in ak:
token = abnormaldic().get(token[:2])
tmp.append(token)
changed = ''
for t in tmp:
if isinstance(t[0], tuple):
for i in range(len(t[0])):
changed += hgtk.text.decompose(t[i][0])
else:
changed += hgtk.text.decompose(t[0])
one_char = re.compile('ᴥ[ㅂㄴㄹ]ᴥ')
if one_char.search(changed):
words = changed.split('ᴥ')
for idx in range(1,len(words)):
# 앞 글자가 종성이 없음
if len(words[idx]) == 1 and len(words[idx-1].replace('|',"")) == 2:
#앞 글자에 합침
words[idx - 1] = words[idx-1]+words[idx]
words[idx] = ""
# 있음
elif len(words[idx]) == 1 and len(words[idx-1].replace('|',"")) == 3:
shp = ['ㅆ','ㅍ','ㄱ','ㅄ','ㄶ']
ep = ['ㄹ']
if words[idx] == 'ㅂ' and len(words[idx - 1].replace('|', "")) == 3 :
if words[idx - 1][-1] in shp :
if words[idx].count("|") > 0:
words[idx] = "|습"
else:
words[idx ] = "습"
continue
else :
if words[idx].count("|") > 0:
words[idx] = "|입"
else:
words[idx] = "입"
# words[idx] = ""
elif words[idx] =='ㄴ' and len(words[idx-1].replace('|',"")) == 3 and words[idx - 1].endswith('ㄹ'):
if words[idx-1].count("|") >0 :
words[idx - 1] = "|" + words[idx - 1].replace("|","")[:2] + words[idx]
else :
words[idx - 1] = words[idx - 1][:2] + words[idx]
# 지움
words[idx] = ""
elif words[idx] =='ㄹ':
if words[idx].count("|") > 0:
words[idx] = "|일"
else:
words[idx] = "일"
changed = "ᴥ".join([x for x in words if x is not ""])+"ᴥ"
# For cases which wasn't covered,
changed = self._makePretty(changed)
changed = hgtk.text.compose(changed).replace("|"," ")
# excetion 처리
try:
if changed[-1] == '요':
changed = re.sub('요', '', changed)
changed = re.sub('그렇죠', '', changed)
except:
pass
result.append(changed)
else:
try:
result.append(stc)
except:
pass
return result[0]
def _makePretty(self, line):
"""
Convert the jaso orderings which wasn't properly covered by
Jaso restructuring process of function Mal_Gillge_Haeraing
:param line: jaso orderings which wasn't properly covered
:return: Converted jaso ordering
"""
test = line
test = test.replace("ᴥㅎㅏᴥㅇㅏᴥ", "ᴥㅎㅐᴥ")
test = test.replace("ㅎㅏᴥㅇㅏᴥㅇㅛᴥ", "ᴥㅎㅐᴥ")
test = test.replace("ㅎㅏᴥㄴㅣᴥㄷㅏᴥ", "ㅎㅏㅂᴥㄴㅣᴥㄷㅏᴥ")
test = test.replace("ㅎㅏᴥㅇㅏㅆᴥ", "ᴥㅎㅐㅆᴥ")
test = test.replace("ㄴㅏᴥㅇㅏㅆᴥ", "ᴥㅎㅐㅆᴥ")
test = test.replace("ㄱㅏᴥㅇㅏㅆᴥ", "ᴥㄱㅏㅆᴥ")
test = test.replace("ㅇㅣᴥㄴㅣᴥ", "ᴥㄴㅣᴥ")
test = test.replace("ㄴㅓㄹㄴᴥ","ㄴㅓㄴᴥ")
test = test.replace("ㄱㅡᴥㄹㅓㅎᴥㅇㅓᴥ","ㄱㅡᴥㄹㅐᴥ")
test = test.replace("ㅡᴥㅇㅏᴥ","ㅏᴥ")
test = test.replace("ㄱㅓㄹᴥㄴㅏᴥㅇㅛᴥ", "ㄱㅓㄴᴥㄱㅏᴥㅇㅛᴥ")
return test
def changer(self, text):
"""
change informal speech to formal speech
Args : str
"""
tokens = self.kiwi.analyze(text.replace(" ","|"))
key = formaldic().keys()
key2 = abnormaldic().keys()
lk = list(key)
ak = list(key2)
num = len(tokens[0][0])
result = []
for idx, token in enumerate(tokens[0][0]):
if idx > int(num*0.8):
if token[:2] in lk:
#key로 value
token = formaldic().get(token[:2])
result.append(token)
else:
if token[:2] in ak:
token = abnormaldic().get(token[:2])
result.append(token)
else:
result.append(token[:2])
else:
if token[:2] in ak:
token = abnormaldic().get(token[:2])
result.append(token)
else:
result.append(token[:2])
# change tuple to text
changed = ''
for t in result:
if isinstance(t[0], tuple):
for i in range(len(t[0])):
changed += hgtk.text.decompose(t[i][0])
else:
changed += hgtk.text.decompose(t[0])
# Restructuring sentence from jaso ordering.
one_char = re.compile('ᴥ[ㅂㄴㄹ]ᴥ')
if one_char.search(changed):
words = changed.split('ᴥ')
for idx in range(1,len(words)):
# 앞 글자가 종성이 없음
if len(words[idx]) == 1 and len(words[idx-1].replace('|',"")) == 2:
#앞 글자에 합침
words[idx - 1] = words[idx-1]+words[idx]
words[idx] = ""
# 있음
elif len(words[idx]) == 1 and len(words[idx-1].replace('|',"")) == 3:
shp = ['ㅆ','ㅍ','ㄱ','ㅄ','ㄶ']
ep = ['ㄹ']
if words[idx] == 'ㅂ' and len(words[idx - 1].replace('|', "")) == 3 :
if words[idx - 1][-1] in shp :
if words[idx].count("|") > 0:
words[idx] = "|습"
else:
words[idx ] = "습"
continue
else :
if words[idx].count("|") > 0:
words[idx] = "|입"
else:
words[idx] = "입"
# words[idx] = ""
elif words[idx] =='ㄴ' and len(words[idx-1].replace('|',"")) == 3 and words[idx - 1].endswith('ㄹ'):
if words[idx-1].count("|") >0 :
words[idx - 1] = "|" + words[idx - 1].replace("|","")[:2] + words[idx]
else :
words[idx - 1] = words[idx - 1][:2] + words[idx]
# 지움
words[idx] = ""
elif words[idx] =='ㄹ':
if words[idx].count("|") > 0:
words[idx] = "|일"
else:
words[idx] = "일"
changed = "ᴥ".join([x for x in words if x is not ""])+"ᴥ"
# For cases which wasn't covered,
changed = self._makePretty(changed)
changed = hgtk.text.compose(changed).replace("|"," ")
return changed
def addData(self, key, val):
"""
Add new data to dictionary, changer dictionary update
:param key: key to be added into Dictionary self.replace
:param val: Value to be added into Dictionary self.replace
:return: None
"""
with open('dictionary.py', 'r', encoding='utf-8') as f:
data = f.read()
lines = data.split("\n")
lines[-2] += ','
lines[-1] = " " + str(key) + ": " + str(val)
with open('dictionary.py', 'w', encoding='utf-8') as f:
for i in range(len(lines)):
f.write(lines[i] + "\n")
f.write(" }")
def checker(self, result):
"""
Check the abnormal setnecnes and remove them.
Args : result, updated, idx : list
"""
updated = []
idxes = []
normal = ['요', '까', '다', '죠', '가']
for idx, stc in enumerate(result):
try:
if stc[-1] not in normal:
print(f"[INFO] Abnormal Sentence, remove {idx}....")
idxes.append(idx)
else:
updated.append(stc)
except:
idxes.append(idx)
return updated, idxes
data['token'].isnull().sum()
# overview에서 Null 값을 가진 경우에는 값 제거
data['token'] = data['token'].fillna('')
#%% 형태소 분석이 끝난 후의 질문들로 학습 벡터 생성
from sklearn.feature_extraction.text import TfidfVectorizer
tfidf = TfidfVectorizer()
tfidf_matrix = tfidf.fit_transform(data['token'])
# overview에 대해서 tf-idf 수행
print(tfidf_matrix.shape)
# %%
from kiwipiepy import Kiwi
kiwi = Kiwi()
kiwi.load_user_dictionary(r'./userDict.txt')
kiwi.prepare()
def generate_morp_word(sentence,analyze_num):
try:
result = kiwi.analyze(sentence, analyze_num)
print(result)
morp_word_list =[]
morp_nn_list=[]
morp_vv_list=[]
for i in range(0, analyze_num):
morp_word = ''
morp_nn=''
morp_vv=''
#print(i)
for word in result[i][0]:
morp_word += word[0]
from kiwipiepy import Kiwi, Option
from wordcloud import WordCloud
import matplotlib.pyplot as plt
from collections import Counter, defaultdict
import codecs
tagger = Kiwi()
tagger.prepare()
# def flat(content):
# return ["{}/{}".format(word,tag) for word, tag in tagger.pos(content)
rsc = r'E:\Programming\python\창회선배스터디\Morpheme_Cloud\자료\토지2.txt'
target_corpus = codecs.open(rsc, 'r', encoding='utf-8')
#텍스트 태깅 작업
tagged_temp = []
# with open(rsc, 'r', encoding="utf8") as kr_f:
# for line in kr_f:
# line = line.strip()
# tagged_temp += flat(line)
for i in target_corpus:
i = i.strip()
temp_tagging = [x[0] for x in tagger.analyze(i, top_n=1)]
inner_temp = ["{}/{}".format(word, tag) for word, tag, score1, score2 in temp_tagging[0]]
tagged_temp.append(tuple(inner_temp))
print(tagged_temp[:3])
