class TestClassifyApi(unittest.TestCase):
def setUp(self):
self.client = FullClient(apiKey=conf.API_KEY,
apiServer=conf.BASE_PATH,
retinaName=conf.RETINA_NAME)
def testCreateCategoryFilter(self):
filterName = "filter1"
filter1 = self.client.createCategoryFilter(filterName,
positiveExamples,
negativeExamples)
self.assertGreater(len(filter1.positions), 50)
self.assertEqual(filter1.categoryName, filterName)
def testErrors(self):
expectedException = False
try:
self.client.createCategoryFilter(None, positiveExamples,
negativeExamples)
except CorticalioException:
expectedException = True
self.assertTrue(expectedException)
expectedException = False
try:
self.client.createCategoryFilter("filterName", [],
negativeExamples)
except CorticalioException:
expectedException = True
self.assertTrue(expectedException)
class TestClassifyApi(unittest.TestCase):
def setUp(self):
self.client = FullClient(apiKey=conf.API_KEY, apiServer=conf.BASE_PATH, retinaName=conf.RETINA_NAME)
def testCreateCategoryFilter(self):
filterName = "filter1"
filter1 = self.client.createCategoryFilter(filterName, positiveExamples, negativeExamples)
self.assertGreater(len(filter1.positions), 50)
self.assertEqual(filter1.categoryName, filterName)
def testErrors(self):
expectedException = False
try:
self.client.createCategoryFilter(None, positiveExamples, negativeExamples)
except CorticalioException:
expectedException = True
self.assertTrue(expectedException)
expectedException = False
try:
self.client.createCategoryFilter("filterName", [], negativeExamples)
except CorticalioException:
expectedException = True
self.assertTrue(expectedException)
class LiteClient(object):
"""Minimalistic client for accessing core features of Cortical.io's Retina API in a simple way."""
def __init__(self, apiKey):
self._fullClient = FullClient(apiKey, apiServer="http://api.cortical.io/rest", retinaName="en_associative")
def _createDictionary(self, textOrFingerprint):
if type(textOrFingerprint) == str:
return {"text": textOrFingerprint}
elif type(textOrFingerprint) == list:
return {"positions": textOrFingerprint}
else:
raise CorticalioException("Invalid argument, cannot create input from: '%s'" % (str(textOrFingerprint)))
def getSimilarTerms(self, textOrFingerprint):
"""Get the similar terms for a given text or fingerprint
Args:
textOrFingerprint, str OR list of integers
Returns:
list of str: the 20 most similar terms
Raises:
CorticalioException: if the request was not successful
"""
expression = self._createDictionary(textOrFingerprint)
terms = self._fullClient.getSimilarTermsForExpression(json.dumps(expression), maxResults=20)
return [t.term for t in terms]
def getKeywords(self, text):
"""Get a list of keywords from the text
Args:
text, str: The input document
Returns:
list of str
Raises:
CorticalioException: if the request was not successful
"""
terms = self._fullClient.getKeywordsForText(text)
return terms
def getFingerprint(self, text):
"""Get the semantic fingerprint of the input text.
Args:
text, str: The text to be evaluated
Returns:
list of str: the positions of the semantic fingerprint
Raises:
CorticalioException: if the request was not successful
"""
fp = self._fullClient.getFingerprintForText(text)
return fp.positions
def compare(self, textOrFingerprint1, textOrFingerprint2):
"""Returns the semantic similarity of texts or fingerprints. Each argument can be eiter a text or a fingerprint.
Args:
textOrFingerprint1, str OR list of integers
textOrFingerprint2, str OR list of integers
Returns:
float: the semantic similarity in the range [0;1]
Raises:
CorticalioException: if the request was not successful
"""
compareList = [self._createDictionary(textOrFingerprint1), self._createDictionary(textOrFingerprint2)]
metric = self._fullClient.compare(json.dumps(compareList))
return metric.cosineSimilarity
def createCategoryFilter(self, positiveExamples):
"""Creates a filter fingerprint.
Args:
positiveExamples, list(str): The list of positive example texts.
Returns:
list of int: the positions representing the filter representing the texts
Raises:
CorticalioException: if the request was not successful
"""
categoryFilter = self._fullClient.createCategoryFilter("CategoryFilter", positiveExamples)
return categoryFilter.positions
class LiteClient(object):
"""Minimalistic client for accessing core features of Cortical.io's Retina API in a simple way."""
def __init__(self, apiKey):
self._fullClient = FullClient(apiKey,
apiServer="http://api.cortical.io/rest",
retinaName="en_associative")
def _createDictionary(self, textOrFingerprint):
if type(textOrFingerprint) == str:
return {"text": textOrFingerprint}
elif type(textOrFingerprint) == list:
return {"positions": textOrFingerprint}
else:
raise CorticalioException(
"Invalid argument, cannot create input from: '%s'" %
(str(textOrFingerprint)))
def getSimilarTerms(self, textOrFingerprint):
"""Get the similar terms for a given text or fingerprint
Args:
textOrFingerprint, str OR list of integers
Returns:
list of str: the 20 most similar terms
Raises:
CorticalioException: if the request was not successful
"""
expression = self._createDictionary(textOrFingerprint)
terms = self._fullClient.getSimilarTermsForExpression(
json.dumps(expression), maxResults=20)
return [t.term for t in terms]
def getKeywords(self, text):
"""Get a list of keywords from the text
Args:
text, str: The input document
Returns:
list of str
Raises:
CorticalioException: if the request was not successful
"""
terms = self._fullClient.getKeywordsForText(text)
return terms
def getFingerprint(self, text):
"""Get the semantic fingerprint of the input text.
Args:
text, str: The text to be evaluated
Returns:
list of str: the positions of the semantic fingerprint
Raises:
CorticalioException: if the request was not successful
"""
fp = self._fullClient.getFingerprintForText(text)
return fp.positions
def compare(self, textOrFingerprint1, textOrFingerprint2):
"""Returns the semantic similarity of texts or fingerprints. Each argument can be eiter a text or a fingerprint.
Args:
textOrFingerprint1, str OR list of integers
textOrFingerprint2, str OR list of integers
Returns:
float: the semantic similarity in the range [0;1]
Raises:
CorticalioException: if the request was not successful
"""
compareList = [
self._createDictionary(textOrFingerprint1),
self._createDictionary(textOrFingerprint2)
]
metric = self._fullClient.compare(json.dumps(compareList))
return metric.cosineSimilarity
def createCategoryFilter(self, positiveExamples):
"""Creates a filter fingerprint.
Args:
positiveExamples, list(str): The list of positive example texts.
Returns:
list of int: the positions representing the filter representing the texts
Raises:
CorticalioException: if the request was not successful
"""
categoryFilter = self._fullClient.createCategoryFilter(
"CategoryFilter", positiveExamples)
return categoryFilter.positions
