本文整理汇总了Python中alchemyapi.AlchemyAPI.language方法的典型用法代码示例。如果您正苦于以下问题：Python AlchemyAPI.language方法的具体用法？Python AlchemyAPI.language怎么用？Python AlchemyAPI.language使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类alchemyapi.AlchemyAPI的用法示例。
在下文中一共展示了AlchemyAPI.language方法的4个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: print
# 需要导入模块: from alchemyapi import AlchemyAPI [as 别名]
# 或者: from alchemyapi.AlchemyAPI import language [as 别名]
print('')
print('')
print('')
print('############################################')
print('# Language Detection Example #')
print('############################################')
print('')
print('')
print('Processing text: ', demo_text)
print('')
response = alchemyapi.language('text',demo_text)
if response['status'] == 'OK':
print('## Response Object ##')
print(json.dumps(response, indent=4))
print('')
print('## Language ##')
print('language: ', response['language'])
print('iso-639-1: ', response['iso-639-1'])
print('native speakers: ', response['native-speakers'])
print('')
else:
print('Error in language detection call: ', response['statusInfo'])
示例2: print
# 需要导入模块: from alchemyapi import AlchemyAPI [as 别名]
# 或者: from alchemyapi.AlchemyAPI import language [as 别名]
print("Error in author extraction call: ", response["statusInfo"])
print("")
print("")
print("")
print("############################################")
print("# Language Detection Example #")
print("############################################")
print("")
print("")
print("Processing text: ", demo_text)
print("")
response = alchemyapi.language("text", demo_text)
if response["status"] == "OK":
print("## Response Object ##")
print(json.dumps(response, indent=4))
print("")
print("## Language ##")
print("language: ", response["language"])
print("iso-639-1: ", response["iso-639-1"])
print("native speakers: ", response["native-speakers"])
print("")
else:
print("Error in language detection call: ", response["statusInfo"])
示例3: print
# 需要导入模块: from alchemyapi import AlchemyAPI [as 别名]
# 或者: from alchemyapi.AlchemyAPI import language [as 别名]
#Author
print('Checking author . . . ')
response = alchemyapi.author('text', test_text);
assert(response['status'] == 'ERROR') #only works for html and url content
response = alchemyapi.author('html', test_html);
assert(response['status'] == 'ERROR') #there's no author in the test HTML
response = alchemyapi.author('url', test_url);
assert(response['status'] == 'OK')
print('Author tests complete!')
print('')
#Language
print('Checking language . . . ')
response = alchemyapi.language('text', test_text);
assert(response['status'] == 'OK')
response = alchemyapi.language('html', test_html);
assert(response['status'] == 'OK')
response = alchemyapi.language('url', test_url);
assert(response['status'] == 'OK')
response = alchemyapi.language('random', test_url);
assert(response['status'] == 'ERROR') #invalid flavor
print('Language tests complete!')
print('')
#Title
print('Checking title . . . ')
response = alchemyapi.title('text', test_text);示例4: user_analysis_sentiments
# 需要导入模块: from alchemyapi import AlchemyAPI [as 别名]
# 或者: from alchemyapi.AlchemyAPI import language [as 别名]
def user_analysis_sentiments(request):
if request.method == 'GET':
print request.GET.get('user', '')
user = request.GET.get('user', '')
messages = []
message = Message.objects.filter(user_send=user.decode("utf8"))
for m in message:
messages.append(m.message_text)
text = ",".join(messages)
alchemyapi = AlchemyAPI()
#keywords
response = alchemyapi.keywords('text', text, {'sentiment': 1})
if response['status'] == 'OK':
keywords = []
for keyword in response['keywords']:
keyword_text = keyword['text'].encode('utf-8')
keyword_relevance = keyword['relevance']
keyword_sentiment = keyword['sentiment']['type']
key_word = {'keyword_text': keyword_text, 'keyword_relevance': keyword_relevance,
'keyword_sentiment': keyword_sentiment}
keywords.append(key_word)
else:
print('Error in keyword extaction call: ', response['statusInfo'])
response = alchemyapi.concepts('text', text)
if response['status'] == 'OK':
concepts = []
for concept in response['concepts']:
concept_text = concept['text']
concept_relevance = concept['relevance']
concept_entity = {'concept_text': concept_text, 'concept_relevance': concept_relevance}
concepts.append(concept_entity)
else:
print('Error in concept tagging call: ', response['statusInfo'])
response = alchemyapi.language('text', text)
if response['status'] == 'OK':
print(response['wikipedia'])
language = response['language']
iso_639_1 = response['iso-639-1']
native_speakers = response['native-speakers']
wikipedia = response['wikipedia']
language_id = {'language': language, 'iso_639_1': iso_639_1, 'native_speakers': native_speakers, 'wikipedia': wikipedia}
else:
print('Error in language detection call: ', response['statusInfo'])
response = alchemyapi.relations('text', text)
if response['status'] == 'OK':
relations = []
for relation in response['relations']:
if 'subject' in relation:
relation_subject_text = relation['subject']['text'].encode('utf-8')
if 'action' in relation:
relation_action_text = relation['action']['text'].encode('utf-8')
if 'object' in relation:
relation_object_text = relation['object']['text'].encode('utf-8')
relation_entity = {'relation_subject_text': relation_subject_text,
'relation_action_text': relation_action_text,
'relation_object_text': relation_object_text}
relations.append(relation_entity)
else:
print('Error in relation extaction call: ', response['statusInfo'])
response = alchemyapi.category('text', text)
if response['status'] == 'OK':
print('text: ', response['category'])
category = response['category']
print('score: ', response['score'])
score = response['score']
categories = {'category': category, 'score': score}
else:
print('Error in text categorization call: ', response['statusInfo'])
response = alchemyapi.taxonomy('text', text)
if response['status'] == 'OK':
taxonomies = []
for category in response['taxonomy']:
taxonomy_label = category['label']
taxonomy_score = category['score']
taxonomy = {'taxonomy_label': taxonomy_label, 'taxonomy_score': taxonomy_score}
taxonomies.append(taxonomy)
else:
print('Error in taxonomy call: ', response['statusInfo'])
response = alchemyapi.combined('text', text)
if response['status'] == 'OK':
print('## Response Object ##')
print(json.dumps(response, indent=4))
print('')
user = {'user_name': 'LOL', 'keywords': keywords, 'concepts': concepts, 'language_id': language_id,
'relations': relations, 'categories': categories, 'taxonomies': taxonomies}
return HttpResponse(json.dumps(user), content_type="application/json")