adding alchemy data news parameters

Author: jsstylos

examples/natural_language_classifier_v1.py

@@ -14,11 +14,11 @@
 # with open('../resources/weather_data_train.csv', 'rb') as training_data:
 #     print(json.dumps(natural_language_classifier.create(training_data=training_data, name='weather2'), indent=2))
 
-# replace 47C164-nlc-243 with your classifier id
-status = natural_language_classifier.status('c7e487x21-nlc-1063')
-print (json.dumps(status, indent=2))
-
-classes = natural_language_classifier.classify('c7e487x21-nlc-1063', 'How hot will it be tomorrow?')
+# replace 4f1704ex55-nlc-2432" with your classifier id
+status = natural_language_classifier.status('f1704ex55-nlc-2432')
+print(json.dumps(status, indent=2))
+#
+classes = natural_language_classifier.classify('f1704ex55-nlc-2432', 'How hot will it be tomorrow?')
 print(json.dumps(classes, indent=2))
 
 # example of raising a WatsonException

watson_developer_cloud/alchemy_data_news_v1.py

@@ -26,15 +26,18 @@ def __init__(self, url=default_url, **kwargs):
         WatsonDeveloperCloudService.__init__(self, 'alchemy_api', url, **kwargs)
 
     def get_news_documents(self, start, end, max_results=10, query_fields=None, return_fields=None, time_slice=None,
-                           next_page=None):
+                           next_page=None, dedup=None, dedup_threshold=None, rank=None):
         if isinstance(return_fields, list):
             return_fields = ','.join(return_fields)
         params = {'start': start,
                   'end': end,
                   'maxResults': max_results,
                   'return': return_fields,
                   'timeSlice': time_slice,
-                  'next': next_page}
+                  'next': next_page,
+                  'dedup': dedup,
+                  'dedupThreshold': dedup_threshold,
+                  'rank': rank}
         if isinstance(query_fields, dict):
             for key in query_fields:
                 params[key if key.startswith('q.') else 'q.' + key] = query_fields[key]