Ready to use!

Author: RUGyron

textAnalizier/kivy_interface/kivy_interface.py

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+from kivy.app import App
+from kivy.uix.label import Label
+from kivy.uix.button import Button
+from kivy.uix.gridlayout import GridLayout
+from kivy.uix.layout import Layout
+
+
+class Interface(App):
+    def build(self):
+        return Button(text='Button')
+
+
+if __name__ == '__main__':
+    app = Interface().run()

textAnalizier/run.py

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+from word2vec import word2vec
+
+
+def run():
+    pass
+
+
+if __name__ == '__main__':
+    run()

textAnalizier/word2vec/config/__pycache__/__init__.cpython-36.pyc

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+types = {
+    'NOUN': 'NOUN',
+    'VERB': 'VERB',
+    'NPRO': 'PROPN',
+    'ADVB': 'ADV',
+    'ADJF': 'ADJ',
+    'NUMR': 'NUM',
+    'PREP': '',
+    'CONJ': '',
+    'PRCL': 'ADV',
+    'INTJ': 'ADV',
+    'COMP': 'COMP',
+    'UNKN': 'UNKN',
+    'INFN': 'INFN',
+    'ADJS': 'ADJS',
+    'NUMB': 'NUMB'
+}

textAnalizier/word2vec/config/__pycache__/__init__.cpython-37.pyc

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+import gensim
+import pymorphy2
+from config import config
+
+
+class Comparer:
+    def __init__(self):
+        self.model = gensim.models.KeyedVectors.load_word2vec_format('binaries/ruwikiruscorpora_upos_skipgram_300_2_2019.bin',
+                                                                     binary=True)
+        self.model.init_sims(replace=True)
+        # print(set(map(lambda x: x.split('_')[1], self.model.vocab.keys())))
+        self.morph = pymorphy2.MorphAnalyzer()
+
+    def get_neighbours(self, _word: str):
+        return self.model.most_similar(_word)
+
+    def get_lemma(self, _word: str) -> tuple:
+        result = self.morph.parse(_word)
+        return result[0].normal_form, self.get_type_for_model(str(result[0].tag)[:4])
+
+    @staticmethod
+    def get_type_for_model(_type: str) -> str:
+        return config.types[_type]
+
+
+if __name__ == '__main__':
+    comparer = Comparer()
+    # for word in ['сестры', 'сделали', 'него', 'красиво', 'красивого',
+    #              'каждый', 'себя', 'он',
+    #              'три',
+    #              'от', 'а', 'не', 'более', 'еще', 'менее',
+    #              'увы']:
+    for word in input().split():
+        lemma = comparer.get_lemma(word)
+        if lemma[1]:
+            lemma = '_'.join(lemma)
+            try:
+                print(comparer.get_neighbours(lemma))
+            except KeyError:
+                print(f'No suggestions to word {lemma.split("_")[0]}')
+        else:
+            lemma = lemma[0]
+            print(f'No suggestions to word {lemma}')
+        print(lemma)
+        # print([x for x in comparer.model.vocab.keys() if x.startswith(lemma.split('_')[0])])
+        print('-------------------------------------')