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example.rb
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example.rb
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# Copyright 2013 AlchemyAPI
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
require './alchemyapi'
demo_text = 'Yesterday dumb Bob destroyed my fancy iPhone in beautiful Denver, Colorado. I guess I will have to head over to the Apple Store and buy a new one.'
demo_url= 'http://www.npr.org/2013/11/26/247336038/dont-stuff-the-turkey-and-other-tips-from-americas-test-kitchen'
demo_html = '<html><head><title>Python Demo | alchemyapi</title></head><body><h1>Did you know that alchemyapi works on HTML?</h1><p>Well, you do now.</p></body></html>'
alchemyapi = AlchemyAPI.new()
puts ''
puts ''
puts '############################################'
puts '# Entity Extraction Example #'
puts '############################################'
puts ''
puts ''
puts 'Processing text: ' + demo_text
puts ''
response = alchemyapi.entities('text', demo_text, { 'sentiment'=>1 })
if response['status'] == 'OK'
puts '## Response Object ##'
puts JSON.pretty_generate(response)
puts ''
puts '## Entities ##'
for entity in response['entities']
puts 'text: ' + entity['text']
puts 'type: ' + entity['type']
puts 'relevance: ' + entity['relevance']
print 'sentiment: ' + entity['sentiment']['type']
#Make sure score exists (it's not returned for neutral sentiment
if entity['sentiment'].key?('score')
print ' (' + entity['sentiment']['score'] + ')'
end
puts ''
end
else
puts 'Error in entity extraction call: ' + response['statusInfo']
end
puts ''
puts ''
puts ''
puts '############################################'
puts '# Keyword Extration Example #'
puts '############################################'
puts ''
puts ''
puts 'Processing text: ' + demo_text
puts ''
response = alchemyapi.keywords('text', demo_text, { 'sentiment'=>1 })
if response['status'] == 'OK'
puts '## Response Object ##'
puts JSON.pretty_generate(response)
puts ''
puts '## Keywords ##'
for keyword in response['keywords']
puts 'text: ' + keyword['text']
puts 'relevance: ' + keyword['relevance']
print 'sentiment: ' + keyword['sentiment']['type']
#Make sure score exists (it's not returned for neutral sentiment
if keyword['sentiment'].key?('score')
print ' (' + keyword['sentiment']['score'] + ')'
end
puts ''
end
else
puts 'Error in keyword extraction call: ' + response['statusInfo']
end
puts ''
puts ''
puts ''
puts '############################################'
puts '# Concept Tagging Example #'
puts '############################################'
puts ''
puts ''
puts 'Processing text: ' + demo_text
puts ''
response = alchemyapi.concepts('text', demo_text)
if response['status'] == 'OK'
puts '## Response Object ##'
puts JSON.pretty_generate(response)
puts ''
puts '## Concepts ##'
for concept in response['concepts']
puts 'text: ' + concept['text']
puts 'relevance: ' + concept['relevance']
puts ''
end
else
puts 'Error in concept tagging call: ' + response['statusInfo']
end
puts ''
puts ''
puts ''
puts '############################################'
puts '# Sentiment Analysis Example #'
puts '############################################'
puts ''
puts ''
puts 'Processing html: ' + demo_html
puts ''
response = alchemyapi.sentiment('html', demo_html)
if response['status'] == 'OK'
puts '## Response Object ##'
puts JSON.pretty_generate(response)
puts ''
puts '## Document Sentiment ##'
puts 'type: ' + response['docSentiment']['type']
#Make sure score exists (it's not returned for neutral sentiment
if response['docSentiment'].key?('score')
puts 'score: ' + response['docSentiment']['score']
end
else
puts 'Error in sentiment analysis call: ' + response['statusInfo']
end
puts ''
puts ''
puts ''
puts '############################################'
puts '# Targeted Sentiment Analysis Example #'
puts '############################################'
puts ''
puts ''
puts 'Processing text: ' + demo_text
puts ''
response = alchemyapi.sentiment_targeted('text', demo_text, 'Denver')
if response['status'] == 'OK'
puts '## Response Object ##'
puts JSON.pretty_generate(response)
puts ''
puts '## Targeted Sentiment ##'
puts 'type: ' + response['docSentiment']['type']
#Make sure score exists (it's not returned for neutral sentiment
if response['docSentiment'].key?('score')
puts 'score: ' + response['docSentiment']['score']
end
else
puts 'Error in targeted sentiment analysis call: ' + response['statusInfo']
end
puts ''
puts ''
puts ''
puts '############################################'
puts '# Text Extraction Example #'
puts '############################################'
puts ''
puts ''
puts 'Processing url: ' + demo_url
puts ''
response = alchemyapi.text('url', demo_url)
if response['status'] == 'OK'
puts '## Response Object ##'
puts JSON.pretty_generate(response)
puts ''
puts '## Extracted Text ##'
puts 'text: ' + response['text']
puts ''
else
puts 'Error in text extraction call: ' + response['statusInfo']
end
puts ''
puts ''
puts ''
puts '############################################'
puts '# Author Extraction Example #'
puts '############################################'
puts ''
puts ''
puts 'Processing url: ' + demo_url
puts ''
response = alchemyapi.author('url', demo_url)
if response['status'] == 'OK'
puts '## Response Object ##'
puts JSON.pretty_generate(response)
puts ''
puts '## Author ##'
puts 'author: ' + response['author']
else
puts 'Error in author extraction call: ' + response['statusInfo']
end
puts ''
puts ''
puts ''
puts '############################################'
puts '# Language Detection Example #'
puts '############################################'
puts ''
puts ''
puts 'Processing text: ' + demo_text
puts ''
response = alchemyapi.language('text', demo_text)
if response['status'] == 'OK'
puts '## Response Object ##'
puts JSON.pretty_generate(response)
puts ''
puts '## Language ##'
puts 'text: ' + response['language']
puts 'iso-639-1: ' + response['iso-639-1']
puts 'native speakers: ' + response['native-speakers']
else
puts 'Error in language detection call: ' + response['statusInfo']
end
puts ''
puts ''
puts ''
puts '############################################'
puts '# Title Extraction Example #'
puts '############################################'
puts ''
puts ''
puts 'Processing url: ' + demo_url
puts ''
response = alchemyapi.title('url', demo_url)
if response['status'] == 'OK'
puts '## Response Object ##'
puts JSON.pretty_generate(response)
puts ''
puts '## Title ##'
puts 'title: ' + response['title']
else
puts 'Error in title extraction call: ' + response['statusInfo']
end
puts ''
puts ''
puts ''
puts '############################################'
puts '# Relation Extraction Example #'
puts '############################################'
puts ''
puts ''
puts 'Processing text: ' + demo_text
puts ''
response = alchemyapi.relations('text', demo_text)
if response['status'] == 'OK'
puts '## Response Object ##'
puts JSON.pretty_generate(response)
puts ''
puts '## Relations ##'
for relation in response['relations']
if relation.key?('subject')
puts 'subject: ' + relation['subject']['text']
end
if relation.key?('action')
puts 'action: ' + relation['action']['text']
end
if relation.key?('object')
puts 'object: ' + relation['object']['text']
end
puts ''
end
else
puts 'Error in relation extraction call: ' + response['statusInfo']
end
puts ''
puts ''
puts ''
puts '############################################'
puts '# Text Categorization Example #'
puts '############################################'
puts ''
puts ''
puts 'Processing text: ' + demo_text
puts ''
response = alchemyapi.category('text', demo_text)
if response['status'] == 'OK'
puts '## Response Object ##'
puts JSON.pretty_generate(response)
puts ''
puts '## Category ##'
puts 'text: ' + response['category']
puts 'score: ' + response['score']
else
puts 'Error in text categorization call: ' + response['statusInfo']
end
puts ''
puts ''
puts ''
puts '############################################'
puts '# Feed Detection Example #'
puts '############################################'
puts ''
puts ''
puts 'Processing url: ' + demo_url
puts ''
response = alchemyapi.feeds('url', demo_url)
if response['status'] == 'OK'
puts '## Response Object ##'
puts JSON.pretty_generate(response)
puts ''
puts '## Feeds ##'
for feed in response['feeds']
puts 'feed: ' + feed['feed']
end
else
puts 'Error in feed detection call: ' + response['statusInfo']
end
puts ''
puts ''
puts ''
puts '############################################'
puts '# Microformats Parsing Example #'
puts '############################################'
puts ''
puts ''
puts 'Processing url: ' + demo_url
puts ''
response = alchemyapi.microformats('url', demo_url)
if response['status'] == 'OK'
puts '## Response Object ##'
puts JSON.pretty_generate(response)
puts ''
puts '## Microformats ##'
for microformat in response['microformats']
puts 'field: ' + microformat['field']
puts 'data: ' + microformat['data']
puts ''
end
else
puts 'Error in microformats parsing call: ' + response['statusInfo']
end
puts ''
puts ''