Merge pull request #435 from watson-developer-cloud/develop

Merge develop to master for patch Version 1.2.2

Author: germanattanasio

.gitignore

@@ -64,3 +64,4 @@ test/__init__.py
 *~
 
 .sfdx/tools/apex.db
+.pytest_cache/

examples/microphone-speech-to-text.py

@@ -1,6 +1,9 @@
 # You need to install pyaudio to run this example
 # pip install pyaudio
 
+# Note that you need to record just once. You will not be able to send
+# more audio after the initial recording.
+
 from __future__ import print_function
 import pyaudio
 import tempfile

examples/natural_language_classifier_v1.py

@@ -1,10 +1,10 @@
 from __future__ import print_function
 import json
 import os
+
 # from os.path import join, dirname
 from watson_developer_cloud import NaturalLanguageClassifierV1
 
-
 natural_language_classifier = NaturalLanguageClassifierV1(
     username='YOUR SERVICE USERNAME',
     password='YOUR SERVICE PASSWORD')
@@ -31,6 +31,12 @@
                                                    'tomorrow?')
     print(json.dumps(classes, indent=2))
 
+if status['status'] == 'Available':
+    collection = ['{"text":"How hot will it be today?"}', '{"text":"Is it hot outside?"}']
+    classes = natural_language_classifier.classify_collection(
+        classifier_id, collection)
+    print(json.dumps(classes, indent=2))
+
 delete = natural_language_classifier.delete_classifier(classifier_id)
 print(json.dumps(delete, indent=2))
 

examples/visual_recognition_v3.py

@@ -1,12 +1,13 @@
 from __future__ import print_function
 import json
 from os.path import join, dirname
-from watson_developer_cloud import VisualRecognitionV3
+from watson_developer_cloud import VisualRecognitionV3, WatsonApiException
 
 test_url = 'https://www.ibm.com/ibm/ginni/images' \
            '/ginni_bio_780x981_v4_03162016.jpg'
 
 visual_recognition = VisualRecognitionV3('2016-05-20', api_key='YOUR API KEY')
+classifier_id = 'CarsvsTrucksxDO_NOT_DELETE_771019274'
 
 # with open(join(dirname(__file__), '../resources/cars.zip'), 'rb') as cars, \
 #        open(join(dirname(__file__), '../resources/trucks.zip'), 'rb') as
@@ -18,11 +19,22 @@
 
 car_path = join(dirname(__file__), '../resources/cars.zip')
 with open(car_path, 'rb') as images_file:
-    parameters = json.dumps({'threshold': 0.1, 'classifier_ids': ['CarsvsTrucks_931077904', 'default']})
+    parameters = json.dumps({'threshold': 0.1, 'classifier_ids': [classifier_id, 'default']})
     car_results = visual_recognition.classify(images_file=images_file,
                                               parameters=parameters)
     print(json.dumps(car_results, indent=2))
 
+# Example with no deprecated
+try:
+    with open(car_path, 'rb') as images_file:
+        car_results = visual_recognition.classify(
+            images_file=images_file,
+            threshold='0.1',
+            classifier_ids=[classifier_id, 'default'])
+        print(json.dumps(car_results, indent=2))
+except WatsonApiException as ex:
+    print(ex.httpResponse.json())
+
 # print(json.dumps(visual_recognition.get_classifier('YOUR CLASSIFIER ID'),
 # indent=2))
 
@@ -53,3 +65,9 @@
 with open(face_path, 'rb') as image_file:
     face_result = visual_recognition.detect_faces(images_file=image_file)
     print(json.dumps(face_result, indent=2))
+
+#Core ml model example
+# model_name = '{0}.mlmodel'.format(classifier_id)
+# core_ml_model = visual_recognition.get_core_ml_model(classifier_id)
+# with open('/tmp/{0}'.format(model_name), 'wb') as fp:
+#     fp.write(core_ml_model.content)

test/integration/test_natural_language_classifier_v1.py

@@ -0,0 +1,56 @@
+# coding: utf-8
+from unittest import TestCase
+import os
+import watson_developer_cloud
+import pytest
+import json
+import time
+
+FIVE_SECONDS = 5
+
+@pytest.mark.skipif(os.getenv('VCAP_SERVICES') is None, reason='requires VCAP_SERVICES')
+class TestNaturalLanguageClassifierV1(TestCase):
+    def setUp(self):
+        self.natural_language_classifier = watson_developer_cloud.NaturalLanguageClassifierV1(
+            username='YOUR SERVICE USERNAME',
+            password='YOUR SERVICE PASSWORD')
+        self.natural_language_classifier.set_default_headers({
+            'X-Watson-Learning-Opt-Out': '1',
+            'X-Watson-Test': '1'
+        })
+
+        # Create a classifier
+        with open(os.path.join(os.path.dirname(__file__), '../../resources/weather_data_train.csv'), 'rb') as training_data:
+            metadata = json.dumps({'name': 'my-classifier', 'language': 'en'})
+            classifier = self.natural_language_classifier.create_classifier(
+                metadata=metadata,
+                training_data=training_data
+            )
+            self.classifier_id = classifier['classifier_id']
+
+    def tearDown(self):
+        self.natural_language_classifier.delete_classifier(self.classifier_id)
+
+    def test_list_classifier(self):
+        list_classifiers = self.natural_language_classifier.list_classifiers()
+        assert list_classifiers is not None
+
+    @pytest.mark.skip(reason="The classifier takes more than a minute")
+    def test_classify_text(self):
+        iterations = 0
+        while iterations < 15:
+            status = self.natural_language_classifier.get_classifier(self.classifier_id)
+            iterations += 1
+            if status['status'] != 'Available':
+                time.sleep(FIVE_SECONDS)
+
+        if status['status'] != 'Available':
+            assert False, 'Classifier is not available'
+
+        classes = self.natural_language_classifier.classify(self.classifier_id, 'How hot will it be tomorrow?')
+        assert classes is not None
+
+        collection = ['{"text":"How hot will it be today?"}', '{"text":"Is it hot outside?"}']
+        classes = self.natural_language_classifier.classify_collection(
+            self.classifier_id, collection)
+        assert classes is not None

test/integration/test_visual_recognition.py

@@ -19,14 +19,15 @@ def setUp(self):
             'X-Watson-Test':
             '1'
         })
+        self.classifier_id = 'CarsvsTrucksxDO_NOT_DELETE_771019274'
 
     def test_classify(self):
         car_path = join(dirname(__file__), '../../resources/cars.zip')
         with open(car_path, 'rb') as images_file:
             parameters = json.dumps({
                 'threshold':
                 0.1,
-                'classifier_ids': ['CarsvsTrucks_931077904', 'default']
+                'classifier_ids': [self.classifier_id, 'default']
             })
             car_results = self.visual_recognition.classify(
                 images_file=images_file, parameters=parameters)
@@ -46,7 +47,8 @@ def test_custom_classifier(self):
             classifier = self.visual_recognition.create_classifier(
                 'Cars vs Trucks',
                 cars_positive_examples=cars,
-                negative_examples=trucks)
+                negative_examples=trucks,
+                )
 
         assert classifier is not None
 
@@ -58,3 +60,7 @@ def test_custom_classifier(self):
         assert classifiers is not None
 
         output = self.visual_recognition.delete_classifier(classifier_id)
+
+    def test_core_ml_model(self):
+        core_ml_model = self.visual_recognition.get_core_ml_model(self.classifier_id)
+        assert core_ml_model.ok

test/unit/test_natural_language_classifier_v1.py

@@ -82,3 +82,53 @@ def test_success():
     assert responses.calls[4].response.text == remove_response
 
     assert len(responses.calls) == 5
+
+@responses.activate
+def test_classify_collection():
+    natural_language_classifier = watson_developer_cloud.NaturalLanguageClassifierV1(username="username",
+                                                                                     password="password")
+    classify_collection_url = 'https://gateway.watsonplatform.net/natural-language-classifier/api/v1/classifiers/497EF2-nlc-00/classify_collection'
+    classify_collection_response = '{ \
+            "classifier_id": "497EF2-nlc-00", \
+            "url": "https://gateway.watsonplatform.net/natural-language-classifier/api/v1/classifiers/10D41B-nlc-1", \
+            "collection": [ \
+                { \
+                    "text": "How hot will it be today?", \
+                    "top_class": "temperature", \
+                    "classes": [ \
+                        { \
+                            "class_name": "temperature", \
+                            "confidence": 0.9930558798985937 \
+                        }, \
+                        { \
+                            "class_name": "conditions", \
+                            "confidence": 0.006944120101406304 \
+                        } \
+                    ] \
+                }, \
+                { \
+                    "text": "Is it hot outside?", \
+                    "top_class": "temperature", \
+                    "classes": [ \
+                        { \
+                            "class_name": "temperature", \
+                            "confidence": 1 \
+                        }, \
+                        { \
+                            "class_name": "conditions", \
+                            "confidence": 0 \
+                        } \
+                    ] \
+                } \
+            ] \
+            }'
+    responses.add(responses.POST, classify_collection_url,
+                  body=classify_collection_response, status=200,
+                  content_type='application/json')
+
+    classifier_id = '497EF2-nlc-00'
+    collection = ['{"text":"How hot will it be today?"}', '{"text":"Is it hot outside?"}']
+    natural_language_classifier.classify_collection(classifier_id, collection)
+
+    assert responses.calls[0].request.url == classify_collection_url
+    assert responses.calls[0].response.text == classify_collection_response