Ruby gem to calculate statistics from text to determine readability, complexity and grade level of a particular corpus.

• Usage
• Installation
• List of Functions
  • Basic Functions
    • Char Count
    • Lexicon Count
    • Syllable Count
    • Sentence Count
    • Average sentence length
    • Average syllables per word
    • Average letters per word
    • Difficult words
  • Advanced Formulas
    • The Flesch Reading Ease formula
    • The Flesch-Kincaid Grade Level
    • The Fog Scale (Gunning FOG Formula)
    • The SMOG Index
    • Automated Readability Index
    • The Coleman-Liau Index
    • Linsear Write Formula
    • Dale-Chall Readability Score
    • Lix Readability Formula
    • FORCAST Readability Formula
    • Powers-Sumner-Kearl Readability Formula
    • SPACHE Readability Formula
    • Readability Consensus based upon all the above tests
• Contributing
• Development setup

require 'textstat'

test_data = %(
         Playing games has always been thought to be important to 
        the development of well-balanced and creative children 
        however, what part, if any, they should play in the lives 
        of adults has never been researched that deeply. I believe 
        that playing games is every bit as important for adults 
        as for children. Not only is taking time out to play games 
        with our children and other adults valuable to building 
        interpersonal relationships but is also a wonderful way 
        to release built up tension.
)


TextStat.char_count(test_data)
TextStat.lexicon_count(test_data)
TextStat.syllable_count(test_data)
TextStat.sentence_count(test_data)
TextStat.avg_sentence_length(test_data)
TextStat.avg_syllables_per_word(test_data)
TextStat.avg_letter_per_word(test_data)
TextStat.avg_sentence_per_word(test_data)
TextStat.difficult_words(test_data)


TextStat.flesch_reading_ease(test_data)
TextStat.flesch_kincaid_grade(test_data)
TextStat.gunning_fog(test_data)
TextStat.smog_index(test_data)
TextStat.automated_readability_index(test_data)
TextStat.coleman_liau_index(test_data)
TextStat.linsear_write_formula(test_data)
TextStat.dale_chall_readability_score(test_data)
TextStat.lix(test_data)
TextStat.forcast(test_data)
TextStat.powers_sumner_kearl(test_data)
TextStat.spache(test_data)

TextStat.text_standard(test_data)

The argument (text) for all the defined functions remains the same - i.e the text for which statistics need to be calculated.

Add this line to your application's Gemfile:

gem 'textstat'

And then execute:

 bundle

Or install it yourself as:

 gem install textstat

TextStat.char_count(text, ignore_spaces = true)

Calculates the number of characters present in the text. Optional ignore_spaces specifies whether we need to take spaces into account while counting chars. Default value is true.

TextStat.lexicon_count(text, remove_punctuation = true)

Calculates the number of words present in the text. Optional remove_punctuation specifies whether we need to take punctuation symbols into account while counting lexicons. Default value is true, which removes the punctuation before counting lexicon items.

TextStat.syllable_count(text, language = 'en_us')

Returns the number of syllables present in the given text.

Uses the Ruby gem text-hyphen for syllable calculation. Optional language specifies which language dictionary to use.

Default is 'en_us'.

TextStat.sentence_count(text)

Returns the number of sentences present in the given text.

TextStat.avg_sentence_length(text)

TextStat.avg_syllables_per_word(text, language = 'en_us')

Returns the average syllables per word in the given text.

TextStat.avg_letter_per_word(text)

Returns the average letters per word in the given text.

TextStat.difficult_words(text, language = 'en_us')

Returns the number of difficult words in the given text. Optional language specifies which language dictionary to use.

Default is 'en_us'

TextStat.flesch_reading_ease(text, language = 'en_us')

Returns the Flesch Reading Ease Score.

The following table can be helpful to assess the ease of readability in a document.

The table is an example of values. While the maximum score is 121.22, there is no limit on how low the score can be. A negative score is valid.

Further reading on Wikipedia

TextStat.flesch_kincaid_grade(text, language = 'en_us')

Returns the Flesch-Kincaid Grade of the given text. This is a grade formula in that a score of 9.3 means that a ninth grader would be able to read the document.

Further reading on Wikipedia

TextStat.gunning_fog(text, language = 'en_us')

Returns the FOG index of the given text. This is a grade formula in that a score of 9.3 means that a ninth grader would be able to read the document.

Further reading on Wikipedia

TextStat.smog_index(text, language = 'en_us')

Returns the SMOG index of the given text. This is a grade formula in that a score of 9.3 means that a ninth grader would be able to read the document.

Texts of fewer than 30 sentences are statistically invalid, because the SMOG formula was normed on 30-sentence samples. textstat requires atleast 3 sentences for a result.

Further reading on Wikipedia

TextStat.automated_readability_index(text)

Returns the ARI (Automated Readability Index) which outputs a number that approximates the grade level needed to comprehend the text.

For example if the ARI is 6.5, then the grade level to comprehend the text is 6th to 7th grade.

Further reading on Wikipedia

TextStat.coleman_liau_index(text)

Returns the grade level of the text using the Coleman-Liau Formula. This is a grade formula in that a score of 9.3 means that a ninth grader would be able to read the document.

Further reading on Wikipedia

TextStat.linsear_write_formula(text, language = 'en_us')

Returns the grade level using the Linsear Write Formula. This is a grade formula in that a score of 9.3 means that a ninth grader would be able to read the document.

Further reading on Wikipedia

TextStat.dale_chall_readability_score(text, language = 'en_us')

Different from other tests, since it uses a lookup table of the most commonly used 3000 English words. Thus it returns the grade level using the New Dale-Chall Formula.

Further reading on Wikipedia

TextStat.lix(text)

Returns the grade level of the text using the Lix Formula.

Further reading on Wikipedia

TextStat.forcast(text, language = 'en_us')

Returns the grade level of the text using the FORCAST Readability Formula.

Further reading on readabilityformulas.com

TextStat.powers_sumner_kearl(text, language = 'en_us')

Returns the grade level of the text using the Powers-Sumner-Kearl Readability Formula.

Further reading on readabilityformulas.com

TextStat.spache(text, language = 'en_us')

Returns the grade level of the text using the Spache Readability Formula.

Further reading on Wikipedia

TextStat.text_standard(text, float_output=False)

Based upon all the above tests, returns the estimated school grade level required to understand the text.

Optional float_output allows the score to be returned as a float. Defaults to False.

Languages supported:

• US English
• UK English
• Catalan
• Czech
• Danish
• Spanish
• Estonian
• Finnish
• French
• Hungarian
• Indonesian
• Icelandic
• Italian
• Latin
• Dutch (Nederlande)
• Bokmål (Norwegian)
• Polish
• Portuguese
• Russian
• Swedish

If you find any problems, you should open an issue.

If you can fix an issue you've found, or another issue, you should open a pull request.

1. Fork this repository on GitHub to start making your changes to the master branch (or branch off of it).
2. Write a test which shows that the bug was fixed or that the feature works as expected.
3. Send a pull request!

git clone https://github.com/kupolak/textstat.git  # Clone the repo from your fork
cd textstat
bundle  # Install all dependencies

# Make changes
rspec spec  # Run tests