stop including MeCab dictionaries in the package

Former-commit-id: b3dd8479ab
This commit is contained in:
Robyn Speer 2016-08-01 17:37:41 -04:00
parent 875dd5669f
commit 2787bfd647
18 changed files with 62 additions and 6914 deletions

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@ -16,42 +16,70 @@ or by getting the repository and running its setup.py:
python3 setup.py install python3 setup.py install
### Additional CJK setup
Chinese, Japanese, and Korean have additional external dependencies so that they can be ## Additional CJK installation
tokenized correctly.
Chinese, Japanese, and Korean have additional external dependencies so that
they can be tokenized correctly. Here we'll explain how to set them up,
in increasing order of difficulty.
### Chinese
To be able to look up word frequencies in Chinese, you need Jieba, a To be able to look up word frequencies in Chinese, you need Jieba, a
pure-Python Chinese tokenizer: pure-Python Chinese tokenizer:
pip3 install jieba pip3 install jieba
To be able to look up word frequencies in Japanese or Korean, you need to additionally
install mecab-python3, which itself depends on libmecab-dev.
These commands will install them on Ubuntu:
sudo apt-get install libmecab-dev ### Japanese
pip3 install mecab-python3
If you installed wordfreq from Git, this should be all you need, because the We use MeCab, by Taku Kudo, to tokenize Japanese. To use this in wordfreq, three
dictionary files are included. Otherwise, read on. things need to be installed:
### Getting dictionary files for the PyPI version * The MeCab development library (called `libmecab-dev` on Ubuntu)
* The UTF-8 version of the `ipadic` Japanese dictionary
(called `mecab-ipadic-utf8` on Ubuntu)
* The `mecab-python3` Python interface
If you installed wordfreq from PyPI (for example, using pip), and you want to To install these three things on Ubuntu, you can run:
handle Japanese and Korean, you need to get their MeCab dictionary files
separately. We would prefer to include them in the package, but PyPI has a size
limit.
The Japanese dictionary is called 'mecab-ipadic-utf8', and is available as an Ubuntu ```sh
package by that name: sudo apt-get install libmecab-dev mecab-ipadic-utf8
pip3 install mecab-python3
```
sudo apt-get install mecab-ipadic-utf8 If you choose to install `ipadic` from somewhere else or from its source code,
be sure it's configured to use UTF-8. By default it will use EUC-JP, which will
give you nonsense results.
The Korean dictionary does not have an Ubuntu package. One option, besides getting it
from wordfreq's Git repository, is to install it from source from:
https://bitbucket.org/eunjeon/mecab-ko-dic ### Korean
Korean also uses MeCab, with a Korean dictionary package by Yongwoon Lee and
Yungho Yu. This dictionary is not available as an Ubuntu package.
Here's a process you can use to install the Korean dictionary and the other
MeCab dependencies:
```sh
sudo apt-get install libmecab-dev mecab-utils
pip3 install mecab-python3
wget https://bitbucket.org/eunjeon/mecab-ko-dic/downloads/mecab-ko-dic-2.0.1-20150920.tar.gz
tar xvf mecab-ko-dic-2.0.1-20150920.tar.gz
cd mecab-ko-dic-2.0.1-20150920
./autogen.sh
make
sudo make install
```
If wordfreq cannot find the Japanese or Korean data for MeCab when asked to
tokenize those languages, it will raise an error and show you the list of
paths it searched.
Sorry that this is difficult. We tried to just package the data files we need
with wordfreq, like we do for Chinese, but PyPI would reject the package for
being too large.
## Usage ## Usage
@ -306,10 +334,6 @@ The terms of use of this data are:
acknowledgement of Google Books Ngram Viewer as the source, and inclusion acknowledgement of Google Books Ngram Viewer as the source, and inclusion
of a link to http://books.google.com/ngrams, would be appreciated. of a link to http://books.google.com/ngrams, would be appreciated.
`wordfreq` uses MeCab, by Taku Kudo, plus Korean data files by Yongwoon Lee and
Yungho Yu. The Korean data is under an Apache 2 license, a copy of which
appears in wordfreq/data/mecab-ko-dic/COPYING.
`wordfreq` also contains data derived from the following Creative Commons-licensed `wordfreq` also contains data derived from the following Creative Commons-licensed
sources: sources:

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@ -1,29 +0,0 @@
;
; Configuration file of IPADIC
;
; $Id: dicrc,v 1.4 2006/04/08 06:41:36 taku-ku Exp $;
;
cost-factor = 800
bos-feature = BOS/EOS,*,*,*,*,*,*,*,*
eval-size = 8
unk-eval-size = 4
config-charset = UTF-8
; yomi
node-format-yomi = %pS%f[7]
unk-format-yomi = %M
eos-format-yomi = \n
; simple
node-format-simple = %m\t%F-[0,1,2,3]\n
eos-format-simple = EOS\n
; ChaSen
node-format-chasen = %m\t%f[7]\t%f[6]\t%F-[0,1,2,3]\t%f[4]\t%f[5]\n
unk-format-chasen = %m\t%m\t%m\t%F-[0,1,2,3]\t\t\n
eos-format-chasen = EOS\n
; ChaSen (include spaces)
node-format-chasen2 = %M\t%f[7]\t%f[6]\t%F-[0,1,2,3]\t%f[4]\t%f[5]\n
unk-format-chasen2 = %M\t%m\t%m\t%F-[0,1,2,3]\t\t\n
eos-format-chasen2 = EOS\n

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@ -1 +0,0 @@
c926154d533ccaef1515af6883056d69c34ca239

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@ -1,201 +0,0 @@
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@ -1,25 +0,0 @@
;
; Configuration file of mecab-ko-dic
;
# 비용 값으로 변환할 때 배율 팩터입니다. 700에서 800에서 문제가 없습니다.
cost-factor = 800
# 문장의 시작, 문장 끝에 대한 소성(素性)입니다. CSV로 표현합니다.
bos-feature = BOS/EOS,*,*,*,*,*,*,*,*
# 알려진 단어의 경우 소성(素性)의 처음부터 몇 개까지 일치하면 정답으로
# 인정하는지를 지정합니다. 일반적으로 알려진 단어는 품사 활용 등의 정보만
# 맞추면 되기 때문에, "읽기", "발음" 소성(素性)은 무시하도록 합니다.
# 여기에서는 3가지가 평가됩니다.
eval-size = 4
# 알 수 없는 단어의 경우
# 소성의 처음부터 몇 개까지 일치하면 정답으로 인정할지를 지정합니다.
unk-eval-size = 2
# dicrc, char.def, unk.def, pos-id.def 파일의 문자 코드셋입니다.
config-charset = UTF-8
# 좌측에 공백을 포함하는 품사의 연접 비용을 늘리기 위한 설정입니다.
# mecab-ko에서만 사용되는 설정입니다. 다음과 같은 형식을 가집니다.
# <posid 1>,<posid 1 penalty cost>,<posid 2>,<posid 2 penalty cost>...
#
# 예) 120,6000 => posid가 120인 품사(조사)의 좌측에 공백을 포함할 경우
# 연접 비용을 6000만큼 늘림
left-space-penalty-factor = 100,3000,120,6000,172,3000,183,3000,184,3000,185,3000,200,3000,210,6000,220,3000,221,3000,222,3000,230,3000

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2dbb57fe707d7dddd2392526aad7cbac77378bb3

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58619494b4f81190218b76d9d2090607830e51ec

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@ -1,66 +0,0 @@
UNKNOWN,*,*,*,*,*,*,*,* 0
*,*,*,*,Compound,*,*,*,* 1
*,*,*,*,Inflect,EC,*,*,* 200
*,*,*,*,Inflect,EF,*,*,* 200
*,*,*,*,Inflect,EP,*,*,* 200
*,*,*,*,Inflect,ETM,*,*,* 200
*,*,*,*,Inflect,ETN,*,*,* 200
*,*,*,*,Inflect,JC,*,*,* 210
*,*,*,*,Inflect,JKB,*,*,* 210
*,*,*,*,Inflect,JKC,*,*,* 210
*,*,*,*,Inflect,JKG,*,*,* 210
*,*,*,*,Inflect,JKO,*,*,* 210
*,*,*,*,Inflect,JKQ,*,*,* 210
*,*,*,*,Inflect,JKS,*,*,* 210
*,*,*,*,Inflect,JKV,*,*,* 210
*,*,*,*,Inflect,JX,*,*,* 210
*,*,*,*,Inflect,XSA,*,*,* 220
*,*,*,*,Inflect,XSN,*,*,* 221
*,*,*,*,Inflect,XSV,*,*,* 222
*,*,*,*,Inflect,VCP,*,*,* 230
*,*,*,*,Inflect,*,*,*,* 2
*,*,*,*,Preanalysis,*,*,*,* 3
EC,*,*,*,*,*,*,*,* 100
EF,*,*,*,*,*,*,*,* 100
EP,*,*,*,*,*,*,*,* 100
ETM,*,*,*,*,*,*,*,* 100
ETN,*,*,*,*,*,*,*,* 100
IC,*,*,*,*,*,*,*,* 110
JC,*,*,*,*,*,*,*,* 120
JKB,*,*,*,*,*,*,*,* 120
JKC,*,*,*,*,*,*,*,* 120
JKG,*,*,*,*,*,*,*,* 120
JKO,*,*,*,*,*,*,*,* 120
JKQ,*,*,*,*,*,*,*,* 120
JKS,*,*,*,*,*,*,*,* 120
JKV,*,*,*,*,*,*,*,* 120
JX,*,*,*,*,*,*,*,* 120
MAG,*,*,*,*,*,*,*,* 130
MAJ,*,*,*,*,*,*,*,* 131
MM,*,*,*,*,*,*,*,* 140
NNG,*,*,*,*,*,*,*,* 150
NNP,*,*,*,*,*,*,*,* 150
NNB,*,*,*,*,*,*,*,* 150
NNBC,*,*,*,*,*,*,*,* 150
NP,*,*,*,*,*,*,*,* 150
NR,*,*,*,*,*,*,*,* 150
SF,*,*,*,*,*,*,*,* 160
SH,*,*,*,*,*,*,*,* 161
SL,*,*,*,*,*,*,*,* 162
SN,*,*,*,*,*,*,*,* 163
SP,*,*,*,*,*,*,*,* 164
SSC,*,*,*,*,*,*,*,* 165
SSO,*,*,*,*,*,*,*,* 166
SC,*,*,*,*,*,*,*,* 167
SY,*,*,*,*,*,*,*,* 168
SE,*,*,*,*,*,*,*,* 169
VA,*,*,*,*,*,*,*,* 170
VCN,*,*,*,*,*,*,*,* 171
VCP,*,*,*,*,*,*,*,* 172
VV,*,*,*,*,*,*,*,* 173
VX,*,*,*,*,*,*,*,* 174
XPN,*,*,*,*,*,*,*,* 181
XR,*,*,*,*,*,*,*,* 182
XSA,*,*,*,*,*,*,*,* 183
XSN,*,*,*,*,*,*,*,* 184
XSV,*,*,*,*,*,*,*,* 185

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@ -1,51 +0,0 @@
# Feature(POS) to Internal State mapping
#
# () () .
#
# CRF는 unigram, bigram, bigram의 3
#
#
# .
#
# ()
#
# .
#
# * :
# (AB|CD|EF) : AB CD EF
# AB : AB에만
#
# () $1 $2, $3.. ()
# (CSV로 ) .
#
# ,,,,,,
#
# Unigram
[unigram rewrite]
*,*,*,*,*,*,*,*,* $1,$2,$3,$4,$5,$6,$7,$8,$9
# bigram
# ($2) .
# ,,($1,$2,*,$4) .
# /NNG,T,*,*,*,*,* + /J,*,,*,*,*,*
#
[left rewrite]
BOS/EOS,*,*,*,*,*,*,*,* $1,$2,$3,$4,$5,$6,$7,$8,BOS/EOS
SF,*,*,*,*,*,*,*,* $1,$2,$3,$4,$5,$6,$7,$8,BOS/EOS
*,*,*,*,Inflect,(JC|JKB|JKC|JKG|JKO|JKQ|JKS|JKV|JX|NNB|NNBC|VCP|ETM|XSN),*,*,* $6,$2,*,$4,*,*,*,*,*
*,*,*,*,(Inflect|Preanalysis),*,*,*,* $6,$2,*,*,*,*,*,*,*
(JC|JKB|JKC|JKG|JKO|JKQ|JKS|JKV|JX|NNB|NNBC|VCP|ETM|XSN),*,*,*,*,*,*,*,* $1,$2,*,$4,*,*,*,*,*
*,*,*,*,*,*,*,*,* $1,$2,*,*,*,*,*,*,*
# bigram
# ($3) .
# ,,,($1,$2,$3,$4) .
# ex) /NN,T,*,*,*,*,* + /J,T,,*,*,*,*
[right rewrite]
BOS/EOS,*,*,*,*,*,*,*,* $1,$2,$3,$4,$5,$6,$7,$8,BOS/EOS
SF,*,*,*,*,*,*,*,* $1,$2,$3,$4,$5,$6,$7,$8,BOS/EOS
SL,*,*,*,*,*,*,*,* NNG,$2,$3,*,*,*,*,*,*
*,*,*,*,Inflect,*,(JC|JKB|JKC|JKG|JKO|JKQ|JKS|JKV|JX|NNB|NNBC|XSN),*,* $7,$2,$3,$4,*,*,*,*,*
*,*,*,*,(Inflect|Preanalysis),*,*,*,* $7,$2,$3,*,*,*,*,*,*
(JC|JKB|JKC|JKG|JKO|JKQ|JKS|JKV|JX|NNB|NNBC|XSN),*,*,*,*,*,*,*,* $1,$2,$3,$4,*,*,*,*,*
*,*,*,*,*,*,*,*,* $1,$2,$3,*,*,*,*,*,*

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9655d23c3a0900764cbcdb8d8395d0f09ec098ed

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@ -4,6 +4,10 @@ import unicodedata
import os import os
# MeCab has fixed-sized buffers for many things, including the dictionary path
MAX_PATH_LENGTH = 58
def find_mecab_dictionary(names): def find_mecab_dictionary(names):
""" """
Find a MeCab dictionary with a given name. The dictionary might come as Find a MeCab dictionary with a given name. The dictionary might come as
@ -15,7 +19,6 @@ def find_mecab_dictionary(names):
""" """
suggested_pkg = names[0] suggested_pkg = names[0]
paths = [ paths = [
resource_filename('wordfreq', 'data'),
os.path.expanduser('~/.local/lib/mecab/dic'), os.path.expanduser('~/.local/lib/mecab/dic'),
'/var/lib/mecab/dic', '/var/lib/mecab/dic',
'/var/local/lib/mecab/dic', '/var/local/lib/mecab/dic',
@ -24,7 +27,7 @@ def find_mecab_dictionary(names):
] ]
full_paths = [os.path.join(path, name) for path in paths for name in names] full_paths = [os.path.join(path, name) for path in paths for name in names]
for path in full_paths: for path in full_paths:
if os.path.exists(path): if os.path.exists(path) and len(path) <= MAX_PATH_LENGTH:
return path return path
error_lines = [ error_lines = [
@ -33,7 +36,13 @@ def find_mecab_dictionary(names):
"the %r package." % suggested_pkg, "the %r package." % suggested_pkg,
"", "",
"We looked in the following locations:" "We looked in the following locations:"
] + ["\t%s" % path for path in full_paths] ] + ["\t%s" % path for path in full_paths if len(path) <= MAX_PATH_LENGTH]
skipped_paths = [path for path in full_paths if len(path) > MAX_PATH_LENGTH]
if skipped_paths:
error_lines += [
"We had to skip these paths that are too long for MeCab to find:",
] + ["\t%s" % path for path in skipped_paths]
raise OSError('\n'.join(error_lines)) raise OSError('\n'.join(error_lines))
@ -50,7 +59,7 @@ def make_mecab_analyzer(names):
# Instantiate the MeCab analyzers for each language. # Instantiate the MeCab analyzers for each language.
MECAB_ANALYZERS = { MECAB_ANALYZERS = {
'ja': make_mecab_analyzer(['mecab-ipadic-utf8', 'mecab-ja-ipadic', 'ipadic-utf8']), 'ja': make_mecab_analyzer(['mecab-ipadic-utf8', 'mecab-ja-ipadic', 'ipadic-utf8']),
'ko': make_mecab_analyzer(['mecab-ko-dic', 'ko-dic']) 'ko': make_mecab_analyzer(['mecab-ko-dic', 'ko-dic', 'mecab-ko-dic-2.0.1-20150920'])
} }