def test_remove_non_alphas_04(self):
warnings.simplefilter('ignore')
expected_output = [['look', 'sentence'],
['sentence', '59', '1', 'numbers'],
['sentence', 'punctuation'],
['sentence', 'john', 'paul', 'emails']]
docs = [
self.test_docs['stopwords_01'],
self.test_docs['numbers_01'],
self.test_docs['punct_01'],
self.test_docs['emails_01'],
]
params = {
'keep_alpha': False,
'keep_alpha_nums': True,
'remove_stops': True,
'remove_oov': False,
'remove_nums': False,
'remove_url': False,
'remove_email': False,
'remove_punct': False
}
t = Tokenizer('nltk')
f = TokenFilter('spacy', **params)
p = Pipeline(t, f)
test_output = p.apply(docs)
self.assertEqual(test_output, expected_output)
def test_nltk_lemmatizer(self):
warnings.simplefilter('ignore')
expected_output = [[
'running', "n't", "n't", 'cry', 'going', 'gone', 'tested'
]]
docs = []
docs.append(self.test_docs['stems_01'])
params = {
'keep_alpha': False,
'keep_alpha_nums': False,
'remove_stops': True,
'remove_oov': False,
'remove_nums': False,
'remove_url': False,
'remove_email': False,
'remove_punct': False
}
t = Tokenizer('spacy')
f = TokenFilter('spacy', **params)
s = Stemmer('nltk', lemmatizer='wordnet')
p = Pipeline(t, f, s)
test_output = p.apply(docs)
self.assertEqual(test_output, expected_output,
'NLTK lemmatiZZZZzer did not lemmatize')
def test_spacy_stops(self):
warnings.simplefilter('ignore')
expected_output = [[':', 'look', 'like', '-', 'sentence']]
docs = []
docs.append(self.test_docs['stopwords_01'])
params = {
'keep_alpha': False,
'keep_alpha_nums': False,
'remove_stops': True,
'remove_oov': False,
'remove_nums': False,
'remove_url': False,
'remove_email': True,
'remove_punct': False
}
t = Tokenizer('spacy')
f = TokenFilter('spacy', **params)
p = Pipeline(t, f)
test_output = p.apply(docs)
self.assertEqual(test_output, expected_output,
'Spacy did not remove stop words')
def test_nltk_oov(self):
warnings.simplefilter('ignore')
expected_output = [['this', 'sentence', 'only']]
docs = []
docs.append(self.test_docs['oov_01'])
params = {
'keep_alpha': False,
'keep_alpha_nums': False,
'remove_stops': False,
'remove_oov': True,
'remove_nums': False,
'remove_url': False,
'remove_email': True,
'remove_punct': False
}
t = Tokenizer('nltk')
f = TokenFilter('nltk', **params)
p = Pipeline(t, f)
test_output = p.apply(docs)
self.assertEqual(test_output, expected_output,
'NLTK did not remove non English words')
def test_spacy_lemma(self):
warnings.simplefilter('ignore')
expected_output = [['run', 'not', 'not', 'cry', 'go', 'go', 'test']]
docs = []
docs.append(self.test_docs['stems_01'])
params = {
'keep_alpha': False,
'keep_alpha_nums': False,
'remove_stops': True,
'remove_oov': False,
'remove_nums': False,
'remove_url': False,
'remove_email': False,
'remove_punct': False
}
t = Tokenizer('spacy')
f = TokenFilter('spacy', **params)
s = Stemmer('spacy')
p = Pipeline(t, f, s)
test_output = p.apply(docs)
self.assertEqual(test_output, expected_output,
'Spacy did not lemmatize')
