#Textastic readability score python full#

Additionally, in the process of preparing it for distribution, I may have made errors that cause the figures in the paper that motivated Textatistic not to match up precisely with those returned by Textatistic. Textatistic is very much an alpha release-use at your own risk!-and has only been tested on Python 3.4. To transparently handle these issues and eliminate ambiguity, I wrote Textatistic and released it as open source software subject to an Apache 2 license.

#Textastic readability score python full#

Moreover, features of the text-particularly full stops used in abbreviations and decimals in numbers-frequently underestimate average words per sentence and syllables per word.

Compounding that fact, many programs that calculate these scores rely on unclear, inconsistent and possibly inaccurate algorithms to count words, sentences and syllables and determine whether a word is on Dale-Chall's easy word list (for a discussion, see Sirco, 2007).

The readability scores I use in my analysis correlate with reading difficulty but they are noisy (see, e.g., Begeny and Greene, 2014 or DuBay, 2004). To do so, I evaluated the readability of about 10,000 abstracts published in four of the top economics journals between 1950–2015. I recently investigated whether academic journals demand clearer, more concise writing from women than they do men.

Textatistic also contains functions to count the number of sentences, characters, syllables, words, words with three or more syllables and words on an expanded Dale-Chall list of easy words. Python package to calculate the Flesch Reading Ease, Flesch-Kincaid, Gunning Fog, Simple Measure of Gobbledygook (SMOG) and Dale-Chall readability indices.