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How to use contains_entry method in assertpy
Best Python code snippet using assertpy_python
iwnlp_wrapper.py
Source:iwnlp_wrapper.py 
...26 if key in self.lemmatizer:27 wrong_entry = {"POS": pos, "Form": form, "Lemma": lemma}28 if wrong_entry in self.lemmatizer[key]:29 self.lemmatizer[key].remove(wrong_entry)30 def contains_entry(self, word, pos=None, ignore_case=False):31 key = word.lower().strip()32 if not pos:33 if ignore_case:34 return key in self.lemmatizer35 else:36 return key in self.lemmatizer and any(filter(lambda x: x["Form"] == word, self.lemmatizer[key]))37 elif not isinstance(pos, list):38 if ignore_case:39 return key in self.lemmatizer and any(filter(lambda x: x["POS"] == pos, self.lemmatizer[key]))40 else:41 return key in self.lemmatizer and any(42 filter(lambda x: x["POS"] == pos and x["Form"] == word, self.lemmatizer[key]))43 else:44 for pos_entry in pos:45 if self.contains_entry(word, pos_entry, ignore_case):46 return True47 return False48 def get_entries(self, word, pos=None, ignore_case=False):49 entries = []50 key = word.lower().strip()51 if not pos:52 if ignore_case:53 entries = self.lemmatizer[key]54 else:55 entries = list(filter(lambda x: x["Form"] == word, self.lemmatizer[key]))56 elif not isinstance(pos, list):57 if ignore_case:58 entries = list(filter(lambda x: x["POS"] == pos, self.lemmatizer[key]))59 else:60 entries = list(filter(lambda x: x["POS"] == pos and x["Form"] == word, self.lemmatizer[key]))61 else:62 for pos_entry in pos:63 if self.contains_entry(word, pos=pos_entry, ignore_case=ignore_case):64 entries.extend(self.get_entries(word, pos_entry, ignore_case))65 return entries66 def get_lemmas(self, word, pos=None, ignore_case=False):67 """68 Return all lemmas for a given word. This method assumes that the specified word is present in the dictionary69 :param word: Word that is present in the IWNLP lemmatizer70 """71 entries = self.get_entries(word, pos, ignore_case)72 lemmas = list(set([entry["Lemma"] for entry in entries]))73 return sorted(lemmas)74 def lemmatize_plain(self, word, ignore_case=False):75 if self.contains_entry(word, ignore_case=ignore_case):76 return self.get_lemmas(word, ignore_case=ignore_case)77 else:78 return None79 def lemmatize(self, word, pos_universal_google):80 """81 Python port of the lemmatize method, see https://github.com/Liebeck/IWNLP.Lemmatizer/blob/master/IWNLP.Lemmatizer.Predictor/IWNLPSentenceProcessor.cs82 """83 if pos_universal_google == "NOUN":84 if self.contains_entry(word, "Noun"):85 return self.get_lemmas(word, "Noun")86 elif self.contains_entry(word, "X"):87 return self.get_lemmas(word, "X")88 elif self.contains_entry(word, "AdjectivalDeclension"):89 return self.get_lemmas(word, "AdjectivalDeclension")90 elif self.contains_entry(word, ["Noun", "X"], ignore_case=True):91 return self.get_lemmas(word, ["Noun", "X"], ignore_case=True)92 else:93 return None94 elif pos_universal_google == "ADJ":95 if self.contains_entry(word, "Adjective"):96 return self.get_lemmas(word, "Adjective")97 elif self.contains_entry(word, "Adjective", ignore_case=True):98 return self.get_lemmas(word, "Adjective", ignore_case=True)99 # Account for possible errors in the POS tagger. This order was fine-tuned in terms of accuracy100 elif self.contains_entry(word, "Noun", ignore_case=True):101 return self.get_lemmas(word, "Noun", ignore_case=True)102 elif self.contains_entry(word, "X", ignore_case=True):103 return self.get_lemmas(word, "X", ignore_case=True)104 elif self.contains_entry(word, "Verb", ignore_case=True):105 return self.get_lemmas(word, "Verb", ignore_case=True)106 else:107 return None108 elif pos_universal_google in ["VERB", "AUX"]:109 if self.contains_entry(word, "Verb", ignore_case=True):110 return self.get_lemmas(word, "Verb", ignore_case=True)111 else:112 return None113 else:...
customIWNLPLemmatizer.py
Source:customIWNLPLemmatizer.py
...17 if key in self.lemmatizer:18 wrong_entry = {"POS": pos, "Form": form, "Lemma": lemma}19 if wrong_entry in self.lemmatizer[key]:20 self.lemmatizer[key].remove(wrong_entry)21 def contains_entry(self, word, pos=None, ignore_case=False):22 key = word.lower().strip()23 if not pos:24 if ignore_case:25 return key in self.lemmatizer26 else:27 return key in self.lemmatizer and any(filter(lambda x: x["Form"] == word, self.lemmatizer[key]))28 elif not isinstance(pos, list):29 if ignore_case:30 return key in self.lemmatizer and any(filter(lambda x: x["POS"] == pos, self.lemmatizer[key]))31 else:32 return key in self.lemmatizer and any(33 filter(lambda x: x["POS"] == pos and x["Form"] == word, self.lemmatizer[key]))34 else:35 for pos_entry in pos:36 if self.contains_entry(word, pos_entry, ignore_case):37 return True38 return False39 def get_entries(self, word, pos=None, ignore_case=False):40 entries = []41 key = word.lower().strip()42 if not pos:43 if ignore_case:44 entries = self.lemmatizer[key]45 else:46 entries = list(filter(lambda x: x["Form"] == word, self.lemmatizer[key]))47 elif not isinstance(pos, list):48 if ignore_case:49 entries = list(filter(lambda x: x["POS"] == pos, self.lemmatizer[key]))50 else:51 entries = list(filter(lambda x: x["POS"] == pos and x["Form"] == word, self.lemmatizer[key]))52 else:53 for pos_entry in pos:54 if self.contains_entry(word, pos=pos_entry, ignore_case=ignore_case):55 entries.extend(self.get_entries(word, pos_entry, ignore_case))56 return entries57 def get_lemmas(self, word, pos=None, ignore_case=False):58 """59 Return all lemmas for a given word. This method assumes that the specified word is present in the dictionary60 :param word: Word that is present in the IWNLP lemmatizer61 """62 entries = self.get_entries(word, pos, ignore_case)63 lemmas = list(set([entry["Lemma"] for entry in entries]))64 return sorted(lemmas)65 def lemmatize_plain(self, word, ignore_case=False):66 if self.contains_entry(word, ignore_case=ignore_case):67 return self.get_lemmas(word, ignore_case=ignore_case)68 else:69 return None70 def lemmatize(self, word, udPos):71 """72 Python port of the lemmatize method, see https://github.com/Liebeck/IWNLP.Lemmatizer/blob/master/IWNLP.Lemmatizer.Predictor/IWNLPSentenceProcessor.cs73 """74 # do not process empty strings75 if(not(word)):76 raise ValueError("Empty String!")77 # valid pos = N,V,ADJ,ADV78 elif(not(udPos in ["NOUN","VERB","ADJ","ADV","AUX"])):79 return word80 if udPos == 'NOUN':81 if len(word) > 1 and word[0].islower():82 word = word[0].upper() + word[1:]83 else:84 word = word.lower()85 if udPos == "NOUN":86 if self.contains_entry(word, "Noun"):87 return self.get_lemmas(word, "Noun")88 elif self.contains_entry(word, "X"):89 return self.get_lemmas(word, "X")90 elif self.contains_entry(word, "AdjectivalDeclension"):91 return self.get_lemmas(word, "AdjectivalDeclension")92 elif self.contains_entry(word, ["Noun", "X"], ignore_case=True):93 return self.get_lemmas(word, ["Noun", "X"], ignore_case=True)94 else:95 return None96 elif udPos in ["ADJ", "ADV"]:97 if self.contains_entry(word, "Adjective"):98 return self.get_lemmas(word, "Adjective")99 elif self.contains_entry(word, "Adjective", ignore_case=True):100 return self.get_lemmas(word, "Adjective", ignore_case=True)101 # Account for possible errors in the POS tagger. This order was fine-tuned in terms of accuracy102 elif self.contains_entry(word, "Noun", ignore_case=True):103 return self.get_lemmas(word, "Noun", ignore_case=True)104 elif self.contains_entry(word, "X", ignore_case=True):105 return self.get_lemmas(word, "X", ignore_case=True)106 elif self.contains_entry(word, "Verb", ignore_case=True):107 return self.get_lemmas(word, "Verb", ignore_case=True)108 else:109 return None110 elif udPos in ["VERB", "AUX"]:111 if self.contains_entry(word, "Verb", ignore_case=True):112 return self.get_lemmas(word, "Verb", ignore_case=True)113 else:114 return None115 else:...
test_iwnlp_wrapper.py
Source:test_iwnlp_wrapper.py
...28 def test_lemmatize_plain_example8(self):29 predicted = self.iwnlp.lemmatize_plain('ein')30 self.assertEqual(predicted, ['ein', 'einen'])31 def test_contains_entry_example1(self):32 self.assertEqual(self.iwnlp.contains_entry('Birne'), True)33 def test_contains_entry_example2(self):34 self.assertEqual(self.iwnlp.contains_entry('birne', ignore_case=False), False)35 def test_contains_entry_example3(self):36 self.assertEqual(self.iwnlp.contains_entry('birne', ignore_case=True), True)37 def test_contains_entry_example4(self):38 self.assertEqual(self.iwnlp.contains_entry('groko'), False)39 def test_contains_entry_example5(self):40 self.assertEqual(self.iwnlp.contains_entry('GroKo'), True)41 def test_contains_entry_example6(self):42 self.assertEqual(self.iwnlp.contains_entry('groko', ignore_case=True), True)43 def test_contains_entry_example7(self):44 self.assertEqual(self.iwnlp.contains_entry('groko', pos='Noun'), False)45 def test_contains_entry_example8(self):46 self.assertEqual(self.iwnlp.contains_entry('groko', pos='X'), False)47 def test_contains_entry_example9(self):48 self.assertEqual(self.iwnlp.contains_entry('groko', pos='AdjectivalDeclension'), False)49 def test_contains_entry_example10(self):50 self.assertEqual(self.iwnlp.contains_entry('groko', pos=["Noun", "X"], ignore_case=True), True)51 def test_lemmatize_example1(self):52 predicted = self.iwnlp.lemmatize('Lkws', pos_universal_google='NOUN')53 self.assertEqual(predicted, ['Lkw'])54 def test_lemmatize_example2(self):55 predicted = self.iwnlp.lemmatize('gespielt', pos_universal_google='VERB')56 self.assertEqual(predicted, ['spielen'])57 def test_get_lemmas_example1(self):58 predicted = self.iwnlp.get_lemmas('groko', pos=["Noun", "X"], ignore_case=True)...
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