I _almost_ got the description and long_description right for 2.0.1. I
even checked it on the test server. But I didn't notice that I was
handling the first line of README.md specially, and ended up setting the
project description to "wordfreq is a Python library for looking up the
frequencies of words in many".
It'll be right in the next version.
This is the result of re-running exquisite-corpus via wordfreq 2. The
frequencies for most languages were identical. Small changes that move
words by a few places in the list appeared in Chinese, Japanese, and
Korean. There are also even smaller changes in Bengali and Hindi.
The source of the CJK change is that Roman letters are case-folded
_before_ Jieba or MeCab tokenization, which changes their output in a
few cases.
In Hindi, one word changed frequency in the top 500. In Bengali, none of
those words changed frequency, but the data file is still different.
I'm not sure I have such a solid explanation here, except that these
languages use the regex tokenizer, and we just updated the regex
dependency, which could affect some edge cases of these languages.
This citation was generated from our GitHub repository by Zenodo. Their
defaults indicate that anyone who's ever accepted a PR for the code
should go on the author line, and that sounds fine to me.
This changes the version from 1.4.2 to 1.5. Things done in this update include:
* include Common Crawl; support 11 more languages
* new frequency-merging strategy
* New sources: Chinese from Wikipedia (mostly Trad.), Dutch big list
* Remove kinda bad sources, i.e. Greek Twitter (too often kaomoji are detected as Greek) and Ukrainian Common Crawl. This results in dropping Ukrainian as an available language, and causing Greek to not be a 'large' language after all.
* Add Korean tokenization, and include MeCab files in data
* Remove marks from more languages
* Deal with commas and cedillas in Turkish and Romanian
Former-commit-id: e6a8f028e3
* Remove marks from more languages
* Add Korean tokenization, and include MeCab files in data
* add a Hebrew tokenization test
* fix terminology in docstrings about abjad scripts
* combine Japanese and Korean tokenization into the same function
Former-commit-id: fec6eddcc3
In German and Greek, SUBTLEX and Hermit Dave turn out to have been
working from the same source data. I looked at the quality of how they
processed the data, and chose SUBTLEX for German, and Dave's wordlist
for Greek.
Former-commit-id: 77c60c29b0
