Well, you do now.
' image_url = 'http://demo1.alchemyapi.com/images/vision/football.jpg' print('') print('') print( ' , ') print( ' .I7777~ ') print( ' .I7777777 ') print( ' +. 77777777 ') print( ' =???, I7777777= ') print( '=?????? 7777777? ,:::===? ') print( '=???????. 777777777777777777~ .77: ?? :7 =$, :$$$$$$+ =$? ') print( ' ????????: .777777777777777777 II77 ?? :7 $$7 :$? 7$7 =$? ') print( ' .???????= +7777777777777777 .7 =7: ?? :7777+ :7:I777? ?777I= 77~777? ,777I I7 77 +$?$: :$? $$ =$? ') print( ' ???????+ ~777???+===::: :7+ ~7 ?? .77 +7 :7?. II 7~ ,I7 77+ I77 ~7 ?7 =7: .$, =$ :$? ,$$? =$? ') print( ' ,???????~ 77 7: ?? ?I. 7 :7 :7 ~7 7 77 =7: 7 7 7~ 7$ $= :$$$$$$~ =$? ') print( ' .??????? ,???I77777777777~ :77777777~ ?? 7: :7 :7 777777777:77 =7 7 +7 ~7 $$$$$$$$I :$? =$? ') print( ' .??????? ,7777777777777777 7= 77 ?? I+ 7 :7 :7 ?? 7,77 =7 7 7~ 7, =$7 $$, :$? =$? ') print( ' .???????. I77777777777777777 +7 ,7??? 77 I7 :7 :7 7~ .?7 77 =7 7 ,77I $+ 7$ :$? =$? ') print( ' ,???????= :77777777777777777~ 7= ~7?? ~I77777 :7 :7 ,777777. 77 =7 7 77, +$ .$::$? =$? ') print( ',??????? :7777777 77 ') print( ' =????? ,7777777 77= ') print( ' +?+ 7777777? ') print( ' + ~7777777 ') print( ' I777777 ') print( ' :~ ') # Create the AlchemyAPI Object alchemyapi = AlchemyAPI() print('') print('') print('############################################') print('# Entity Extraction Example #') print('############################################') print('') print('') print('Processing text: ', demo_text) print('') response = alchemyapi.entities('text', demo_text, {'sentiment': 1}) if response['status'] == 'OK': print('## Response Object ##') print(json.dumps(response, indent=4)) print('') print('## Entities ##') for entity in response['entities']: print('text: ', entity['text'].encode('utf-8')) print('type: ', entity['type']) print('relevance: ', entity['relevance']) print('sentiment: ', entity['sentiment']['type']) if 'score' in entity['sentiment']: print('sentiment score: ' + entity['sentiment']['score']) print('') else: print('Error in entity extraction call: ', response['statusInfo']) print('') print('') print('') print('############################################') print('# Keyword Extraction Example #') print('############################################') print('') print('') print('Processing text: ', demo_text) print('') response = alchemyapi.keywords('text', demo_text, {'sentiment': 1}) if response['status'] == 'OK': print('## Response Object ##') print(json.dumps(response, indent=4)) print('') print('## Keywords ##') for keyword in response['keywords']: print('text: ', keyword['text'].encode('utf-8')) print('relevance: ', keyword['relevance']) print('sentiment: ', keyword['sentiment']['type']) if 'score' in keyword['sentiment']: print('sentiment score: ' + keyword['sentiment']['score']) print('') else: print('Error in keyword extaction call: ', response['statusInfo']) print('') print('') print('') print('############################################') print('# Concept Tagging Example #') print('############################################') print('') print('') print('Processing text: ', demo_text) print('') response = alchemyapi.concepts('text', demo_text) if response['status'] == 'OK': print('## Object ##') print(json.dumps(response, indent=4)) print('') print('## Concepts ##') for concept in response['concepts']: print('text: ', concept['text']) print('relevance: ', concept['relevance']) print('') else: print('Error in concept tagging call: ', response['statusInfo']) print('') print('') print('') print('############################################') print('# Sentiment Analysis Example #') print('############################################') print('') print('') print('Processing html: ', demo_html) print('') response = alchemyapi.sentiment('html', demo_html) if response['status'] == 'OK': print('## Response Object ##') print(json.dumps(response, indent=4)) print('') print('## Document Sentiment ##') print('type: ', response['docSentiment']['type']) if 'score' in response['docSentiment']: print('score: ', response['docSentiment']['score']) else: print('Error in sentiment analysis call: ', response['statusInfo']) print('') print('') print('') print('############################################') print('# Targeted Sentiment Analysis Example #') print('############################################') print('') print('') print('Processing text: ', demo_text) print('') response = alchemyapi.sentiment_targeted('text', demo_text, 'Denver') if response['status'] == 'OK': print('## Response Object ##') print(json.dumps(response, indent=4)) print('') print('## Targeted Sentiment ##') print('type: ', response['docSentiment']['type']) if 'score' in response['docSentiment']: print('score: ', response['docSentiment']['score']) else: print('Error in targeted sentiment analysis call: ', response['statusInfo']) print('') print('') print('') print('############################################') print('# Text Extraction Example #') print('############################################') print('') print('') print('Processing url: ', demo_url) print('') response = alchemyapi.text('url', demo_url) if response['status'] == 'OK': print('## Response Object ##') print(json.dumps(response, indent=4)) print('') print('## Text ##') print('text: ', response['text'].encode('utf-8')) print('') else: print('Error in text extraction call: ', response['statusInfo']) print('') print('') print('') print('############################################') print('# Author Extraction Example #') print('############################################') print('') print('') print('Processing url: ', demo_url) print('') response = alchemyapi.author('url', demo_url) if response['status'] == 'OK': print('## Response Object ##') print(json.dumps(response, indent=4)) print('') print('## Author ##') print('author: ', response['author'].encode('utf-8')) print('') else: 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']) print('') print('') print('') print('############################################') print('# Title Extraction Example #') print('############################################') print('') print('') print('Processing url: ', demo_url) print('') response = alchemyapi.title('url', demo_url) if response['status'] == 'OK': print('## Response Object ##') print(json.dumps(response, indent=4)) print('') print('## Title ##') print('title: ', response['title'].encode('utf-8')) print('') else: print('Error in title extraction call: ', response['statusInfo']) print('') print('') print('') print('############################################') print('# Relation Extraction Example #') print('############################################') print('') print('') print('Processing text: ', demo_text) print('') response = alchemyapi.relations('text', demo_text) if response['status'] == 'OK': print('## Object ##') print(json.dumps(response, indent=4)) print('') print('## Relations ##') for relation in response['relations']: if 'subject' in relation: print('Subject: ', relation['subject']['text'].encode('utf-8')) if 'action' in relation: print('Action: ', relation['action']['text'].encode('utf-8')) if 'object' in relation: print('Object: ', relation['object']['text'].encode('utf-8')) print('') else: print('Error in relation extaction call: ', response['statusInfo']) print('') print('') print('') print('############################################') print('# Text Categorization Example #') print('############################################') print('') print('') print('Processing text: ', demo_text) print('') response = alchemyapi.category('text', demo_text) if response['status'] == 'OK': print('## Response Object ##') print(json.dumps(response, indent=4)) print('') print('## Category ##') print('text: ', response['category']) print('score: ', response['score']) print('') else: print('Error in text categorization call: ', response['statusInfo']) print('') print('') print('') print('############################################') print('# Feed Detection Example #') print('############################################') print('') print('') print('Processing url: ', demo_url) print('') response = alchemyapi.feeds('url', demo_url) if response['status'] == 'OK': print('## Response Object ##') print(json.dumps(response, indent=4)) print('') print('## Feeds ##') for feed in response['feeds']: print('feed: ', feed['feed']) else: print('Error in feed detection call: ', response['statusInfo']) print('') print('') print('') print('') print('') print('############################################') print('# Microformats Parsing Example #') print('############################################') print('') print('') print('Processing url: ', demo_url) print('') response = alchemyapi.microformats('url', demo_url) if response['status'] == 'OK': print('## Response Object ##') print(json.dumps(response, indent=4)) print('') print('## Microformats ##') for microformat in response['microformats']: print('Field: ', microformat['field'].encode('utf-8')) print('Data: ', microformat['data']) print('') else: print('Error in microformats parsing call: ', response['statusInfo']) print('') print('') print('') print('') print('') print('############################################') print('# Image Extraction Example #') print('############################################') print('') print('') print('Processing url: ', demo_url) print('') response = alchemyapi.imageExtraction('url', demo_url) if response['status'] == 'OK': print('## Response Object ##') print(json.dumps(response, indent=4)) print('') print('## Image ##') print('Image: ', response['image']) print('') else: print('Error in image extraction call: ', response['statusInfo']) print('') print('') print('') print('') print('') print('############################################') print('# Image tagging Example #') print('############################################') print('') print('') print('Processing url: ', image_url) print('') response = alchemyapi.imageTagging('url', image_url) if response['status'] == 'OK': print('## Response Object ##') print(json.dumps(response, indent=4)) print('') print('## Keywords ##') for keyword in response['imageKeywords']: print(keyword['text'], ' : ', keyword['score']) print('') else: print('Error in image tagging call: ', response['statusInfo']) print('') print('') print('') print('') print('') print('############################################') print('# Taxonomy Example #') print('############################################') print('') print('') print('Processing text: ', demo_text) print('') response = alchemyapi.taxonomy('text', demo_text) if response['status'] == 'OK': print('## Response Object ##') print(json.dumps(response, indent=4)) print('') print('## Categories ##') for category in response['taxonomy']: print(category['label'], ' : ', category['score']) print('') else: print('Error in taxonomy call: ', response['statusInfo']) print('') print('') print('') print('') print('') print('############################################') print('# Combined Example #') print('############################################') print('') print('') print('Processing text: ', demo_text) print('') response = alchemyapi.combined('text', demo_text) if response['status'] == 'OK': print('## Response Object ##') print(json.dumps(response, indent=4)) print('') print('## Keywords ##') for keyword in response['keywords']: print(keyword['text'], ' : ', keyword['relevance']) print('') print('## Concepts ##') for concept in response['concepts']: print(concept['text'], ' : ', concept['relevance']) print('') print('## Entities ##') for entity in response['entities']: print(entity['type'], ' : ', entity['text'], ', ', entity['relevance']) print(' ') else: print('Error in combined call: ', response['statusInfo']) print('') print('')