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import date_parser as dp
import preproc
import category_parser as cp
import sentiment_parser as sp
import word_transformations as wt
# def get_gender(tokens):
# r = [token.feats['Gender'] for sent in tokenizing(text) for token in sent if (token.feats.get('Gender') and token.feats.get('Voice')) ]
# @st.experimental_memo
def analyze(text):
# Разделение текста на датированные куски
diary = dp.date_extractor_for_diary(text)
# Очистка текста дневника
diary = preproc.text_preproc(diary)
# Токенизация текста дневника по предложениям
diary['tokens'] = diary['text'].apply(lambda text: preproc.tokenizing(text))
# # Выделение фактов из текста
diary['locations'] = diary['tokens'].apply(lambda tokens: cp.get_facts(tokens, 'locations'))
diary['activities'] = diary['tokens'].apply(lambda tokens: cp.get_facts(tokens, 'activities'))
# Определение сентимента по записям
diary['sent'] = diary['tokens'].apply(lambda tokens: sp.get_overall_sentiment(tokens))
diary['sent_index'] = diary['sent'].apply(lambda sent: sp.get_sentiment_index(sent))
return diary |