def post(self):
params = {x: request.form[x] for x in request.form}
StandardNLP.process(params)
FeatureExtractor.process(params)
Classifier.process(params)
Executor.process(params)
return params
def post(self):
params = {x: request.form[x] for x in request.form}
StandardNLP.process(params)
FeatureExtractor.process(params)
Classifier.process(params)
Executor.process(params)
return params
def process(cls, params):
Validator.process(params)
if 'error' in params:
cls.LOGGER.error(message=params['error'])
abort(404, message=params['error'])
StandardNLP.process(params)
FeatureExtractor.process(params)
Classifier.process(params)
Executor.process(params)
Logger.process(params)
Sanitizer.process(params)
def test_question_type():
for test in test_cases:
sent, tokens, exp_features = test
processed = StandardNLP.process(sent)
features = FeatureExtractor.extract_features(processed)
assert features['questionType'] == exp_features['questionType']
def test_nouns():
for test in test_cases:
sent, tokens, exp_features = test
processed = StandardNLP.process(sent)
features = FeatureExtractor.extract_features(processed)
assert features['nouns'] == exp_features['nouns']
def test_question_type():
for test in test_cases:
sent, tokens, exp_features = test
processed = StandardNLP.process(sent)
features = FeatureExtractor.extract_features(processed)
assert features['questionType'] == exp_features['questionType']
def test_nouns():
for test in test_cases:
sent, tokens, exp_features = test
processed = StandardNLP.process(sent)
features = FeatureExtractor.extract_features(processed)
assert features['nouns'] == exp_features['nouns']
