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- # -*- coding: utf-8 -*-
- # Adadpted from here: http://acdx.net/calculating-the-flesch-kincaid-level-in-python/
- # See here for details: http://en.wikipedia.org/wiki/Flesch%E2%80%93Kincaid_readability_test
- from __future__ import division
- import re
- def mean(seq):
- return sum(seq) / len(seq)
- def syllables(word):
- if len(word) <= 3:
- return 1
- word = re.sub(r"(es|ed|(?<!l)e)$", "", word)
- return len(re.findall(r"[aeiouy]+", word))
- def normalize(text):
- terminators = ".!?:;"
- term = re.escape(terminators)
- text = re.sub(r"[^%s\sA-Za-z]+" % term, "", text)
- text = re.sub(r"\s*([%s]+\s*)+" % term, ". ", text)
- return re.sub(r"\s+", " ", text)
- def text_stats(text, wc):
- text = normalize(text)
- stcs = [s.split(" ") for s in text.split(". ")]
- stcs = filter(lambda s: len(s) >= 2, stcs)
- if wc:
- words = wc
- else:
- words = sum(len(s) for s in stcs)
- sbls = sum(syllables(w) for s in stcs for w in s)
- return len(stcs), words, sbls
- def flesch_index(stats):
- stcs, words, sbls = stats
- if stcs == 0 or words == 0:
- return 0
- return 206.835 - 1.015 * (words / stcs) - 84.6 * (sbls / words)
- def flesch_kincaid_level(stats):
- stcs, words, sbls = stats
- if stcs == 0 or words == 0:
- return 0
- return 0.39 * (words / stcs) + 11.8 * (sbls / words) - 15.59
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