Textalytics

Ruby wrapper for the Textalytics APIs. The Textalytics gem provides an easy-to-use wrapper for Textalytics's REST APIs.

Use

You have two options when creating a new client. Create environment variables for each API key:

export SENTIMENT_KEY=<your key>
export CLASSIFICATION_KEY=<...>
export LANGUAGE_KEY=<...>
export TOPICS_KEY=<...>
                                   
t = Textalytics::Client.new

Otherwise you have to pass the keys as arguments:

t = Textalytics::Client.new(sentiment: "insert your sentiment API key", classification: "insert your classification API key", topics: "...")

Using Sentiment API

# You can read about the parameters that you can send in the request here
# https://textalytics.com/core/sentiment-info#doc

movie_sentiment = t.sentiment(txt: 'The movie was terrible, never see a movie of that director. Even the actors are bad.', model: 'en-general')
movie_sentiment.score_tag
movie_sentiment.sd_tag #etc, etc...

Using Text Classification API

# You can read about the parameters that you can send in the request here
# https://textalytics.com/core/class-info#doc

title = 'Computer'
text = <<PARAGRAPH
A computer is a general purpose device that can be programmed to carry out 
a set of arithmetic or logical operations automatically. Since a sequence of 
operations can be readily changed, the computer can solve more than one kind of 
problem.

Conventionally, a computer consists of at least one processing element, typically
a central processing unit (CPU), and some form of memory. The processing element 
carries out arithmetic and logic operations, and a sequencing and control unit can 
change the order of operations in response to stored information. Peripheral devices 
allow information to be retrieved from an external source, and the result of operations 
saved and retrieved.
PARAGRAPH   

t = Textalytics::Client.new
#Model and other parameters can be found in the documentation page of the API
classification = t.classification(title: title, txt: text, model: 'IPTC_en') 
classification.categories  #etc  

Using Topics Extraction API

# You can read about the parameters that you can send in the request here
# https://textalytics.com/core/topics-info#doc

t = Textalytics::Client.new

topics = t.topics(txt: "A computer is a general purpose device that can be programmed to carry out a set of arithmetic or logical operations automatically. Since a sequence of operations can be readily changed, the computer can solve more than one kind of problem.",
         lang: 'en', tt: 'ectmu')

topics.concepts
topics.entities
topics.time_expressions

Using Language Identification API

# You can read about the parameters that you can send in the request here
# https://textalytics.com/core/lang-info#doc

t = Textalytics::Client.new

lang = t.language_list(txt: 'A computer is a general purpose device that can be programmed')
lang.first

TODO: Add some examples

Installation

Add this line to your application's Gemfile:

gem 'textalytics'

And then execute:

$ bundle

Or install it yourself as:

$ gem install textalytics

TODO

• Write more tests
• Write a better documentation

Usage

TODO: Write usage instructions here

Contributing

1. Fork it ( http://github.com//textalytics/fork )
2. Create your feature branch (git checkout -b my-new-feature)
3. Commit your changes (git commit -am 'Add some feature')
4. Push to the branch (git push origin my-new-feature)
5. Create new Pull Request