Analyzes :text in the given map data and returns eight values: syllable count, word count, sentence count, complex-word count, a list of complex words and their syllables, a list of words and their syllables, the Flesch-Kincaid Readability Score, and the original text.

main accepts one parameter, data, a map that must include the key :text and the associated value "string".

main will then analyze "string" and return seven new key/value pairs: :complex, :complex_count, :flesch_kincaid, :sent_count, :syl_count, :word_count, and :words.

Here is an overview of the types and values that main returns:

• :complex : A list of lists: every complex word and its syllable count. A complex word in English is any word with three or more syllables.
• :complex_count : the total number of complex words
• :flesch_kincaid : the Flesch-Kincaid readability score. This is a widely used metric for gauging the difficulty of an English-language text.
• :sent_count : the total number of sentences
• :syl_count : the total number of syllables
• :text : the original string
• :word_count : the total number of words
• :words : A list of four-element tuples: {"word1", "word1-parsed", "word1-syllabified", word1-syl-count}

A Note on the Flesch-Kincaid Readability Score: The score has an upper boundary of 121.22. The higher the score, the more readable the text. Scores from 100.0-90.0 are very easy to read. 70.0-60.0 is the "plain english" sweet spot. Scores from 10.0-0 are extremely difficult to read and often professional scholarship. Technically, the scale has no lower boundary. The string "inspecting multitudes of unadulterated ungulates" returns a valid score of -102.79.

A Flesch-Kincaid Score of 60 or higher is an ideal goal for general web content.

A Note on large files: When parsing large amounts of text, the values for :complex, :words, and :text can become large and cumbersome. When testing large datasets, it can be useful to drop these three key/value pairs. Piping your results into Map.drop([:text, :words, :complex]) works well.

Examples

iex> Parsy.main(%{text: "the cat sat on the mat. drat"})
%{
  complex: [],
  complex_count: 0,
  flesch_kincaid: 118.6825,
  sent_count: 2,
  syl_count: 7,
  text: "the cat sat on the mat. drat",
  word_count: 7,
  words: [
    {"the", "th", ["th"], 1},
    {"cat", "cat", ["c", "a", "t"], 1},
    {"sat", "sat", ["s", "a", "t"], 1},
    {"on", "on", ["o", "n"], 1},
    {"the", "th", ["th"], 1},
    {"mat", "mat", ["m", "a", "t"], 1},
    {"drat", "drat", ["dr", "a", "t"], 1}
  ]
}

iex> data = %{text: "inspecting multitudes of unadulterated ungulates"}
%{
  text: "inspecting multitudes of unadulterated ungulates"
}

iex> Parsy.main(data)
%{
  complex: [
    ["inspecting", 3],
    ["multitudes", 4],
    ["unadulterated", 6],
    ["ungulates", 4]
  ],
  complex_count: 4,
  flesch_kincaid: -102.79999999999998,
  sent_count: 1,
  syl_count: 18,
  text: "inspecting multitudes of unadulterated ungulates",
  word_count: 5,
  words: [
    {"inspecting", "inspecting", ["i", "nsp", "e", "ct", "i", "ng"], 3},
    {"multitudes", "multitudes", ["m", "u", "lt", "i", "t", "u", "d", "e", "s"],
    4},
    {"of", "of", ["o", "f"], 1},
    {"unadulterated", "unadulterated",
    ["u", "n", "a", "d", "u", "lt", "e", "r", "a", "t", "e", "d"], 6},
    {"ungulates", "ungulates", ["u", "ng", "u", "l", "a", "t", "e", "s"], 4}
  ]
}

iex> Parsy.main(data) |> Map.drop([:complex, :text, :words])
%{
  complex_count: 4,
  flesch_kincaid: -102.79999999999998,
  sent_count: 1,
  syl_count: 18,
  word_count: 5
}