%global _empty_manifest_terminate_build 0
Name:		python-ArticutAPI
Version:	1.3.0
Release:	1
Summary:	Articut NLP system provides not only finest results on Chinese word segmentaion (CWS), Part-of-Speech tagging (POS) and Named Entity Recogintion tagging (NER), but also the fastest online API service in the NLP industry.
License:	MIT License
URL:		https://github.com/Droidtown/ArticutAPI
Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/aa/e7/118ab68c228c9f95cdaf4d63bf25eea4c065d9ce4295a8510eba0895aac4/ArticutAPI-1.3.0.tar.gz
BuildArch:	noarch

Requires:	python3-requests
Requires:	python3-emoji
Requires:	python3-graphene

%description
# ArticutAPI
## 安裝方法
```sh
pip3 install ArticutAPI
```
## 說明文件
函數說明請參閱 Docs/index.html
## 使用方法
### Articut CWS (Chinese word segmentation)
```
from ArticutAPI import Articut
from pprint import pprint
username = "" #這裡填入您在 https://api.droidtown.co 使用的帳號 email。若使用空字串，則預設使用每小時 2000 字的公用額度。
apikey   = "" #這裡填入您在 https://api.droidtown.co 登入後取得的 api Key。若使用空字串，則預設使用每小時 2000 字的公用額度。
articut = Articut(username, apikey)
inputSTR = "會被大家盯上，才證明你有實力。"
resultDICT = articut.parse(inputSTR)
pprint(resultDICT)
```
### 回傳結果
```
{"exec_time": 0.06723856925964355,
 "level": "lv2",
 "msg": "Success!",
 "result_pos": ["<MODAL>會</MODAL><ACTION_lightVerb>被</ACTION_lightVerb><ENTITY_nouny>大家</ENTITY_nouny><ACTION_verb>盯上</ACTION_verb>",
                "，",
                "<MODAL>才</MODAL><ACTION_verb>證明</ACTION_verb><ENTITY_pronoun>你</ENTITY_pronoun><ACTION_verb>有</ACTION_verb><ENTITY_noun>實力</ENTITY_noun>",
                "。"],
 "result_segmentation": "會/被/大家/盯上/，/才/證明/你/有/實力/。/",
 "status": True,
 "version": "v118",
 "word_count_balance": 9985,
 "product": "https://api.droidtown.co/product/",
 "document": "https://api.droidtown.co/document/"
}
```
### 列出斷詞結果所有詞性標記的內容詞 ###
可以依需求找出「名詞」、「動詞」或是「形容詞」…等詞彙語意本身已經完整的詞彙。
```
inputSTR = "你計劃過地球人類補完計劃"
resultDICT = articut.parse(inputSTR, level="lv1")
pprint(resultDICT["result_pos"])
#列出所有的 content word.
contentWordLIST = articut.getContentWordLIST(resultDICT)
pprint(contentWordLIST)
#列出所有的 verb word. (動詞)
verbStemLIST = articut.getVerbStemLIST(resultDICT)
pprint(verbStemLIST)
#列出所有的 noun word. (名詞)
nounStemLIST = articut.getNounStemLIST(resultDICT)
pprint(nounStemLIST)
#列出所有的 location word. (地方名稱)
locationStemLIST = articut.getLocationStemLIST(resultDICT)
pprint(locationStemLIST)
```
### 回傳結果 ###
```
#resultDICT["result_pos"]
["<ENTITY_pronoun>你</ENTITY_pronoun><ACTION_verb>計劃</ACTION_verb><ASPECT>過</ASPECT><LOCATION>地球</LOCATION><ENTITY_oov>人類</ENTITY_oov><ACTION_verb>補完</ACTION_verb><ENTITY_nounHead>計劃</ENTITY_nounHead>"]
#列出所有的 content word.
[[(177, 179, "計劃"), (144, 145, "補"), (116, 118, "人類"), (47, 49, "計劃")]]
#列出所有的 verb word. (動詞)
[[(41, 43, '計劃'), (111, 112, '補')]]
#列出所有的 noun word. (名詞)
[[(88, 90, '人類'), (138, 140, '計劃')]]
#列出所有的 location word. (地方名稱)
[[(62, 64, "地球")]]
```
### 取得 Articut 版本列表
```
resultDICT = articut.versions()
pprint(resultDICT)
```
### 回傳結果
```
{"msg": "Success!",
 "status": True,
 "versions": [{"level": ["lv1", "lv2"],
               "release_date": "2019-04-25",
               "version": "latest"},
              {"level": ["lv1", "lv2"],
               "release_date": "2019-04-25",
               "version": "v118"},
              {"level": ["lv1", "lv2"],
               "release_date": "2019-04-24",
               "version": "v117"},...
}

%package -n python3-ArticutAPI
Summary:	Articut NLP system provides not only finest results on Chinese word segmentaion (CWS), Part-of-Speech tagging (POS) and Named Entity Recogintion tagging (NER), but also the fastest online API service in the NLP industry.
Provides:	python-ArticutAPI
BuildRequires:	python3-devel
BuildRequires:	python3-setuptools
BuildRequires:	python3-pip
%description -n python3-ArticutAPI
# ArticutAPI
## 安裝方法
```sh
pip3 install ArticutAPI
```
## 說明文件
函數說明請參閱 Docs/index.html
## 使用方法
### Articut CWS (Chinese word segmentation)
```
from ArticutAPI import Articut
from pprint import pprint
username = "" #這裡填入您在 https://api.droidtown.co 使用的帳號 email。若使用空字串，則預設使用每小時 2000 字的公用額度。
apikey   = "" #這裡填入您在 https://api.droidtown.co 登入後取得的 api Key。若使用空字串，則預設使用每小時 2000 字的公用額度。
articut = Articut(username, apikey)
inputSTR = "會被大家盯上，才證明你有實力。"
resultDICT = articut.parse(inputSTR)
pprint(resultDICT)
```
### 回傳結果
```
{"exec_time": 0.06723856925964355,
 "level": "lv2",
 "msg": "Success!",
 "result_pos": ["<MODAL>會</MODAL><ACTION_lightVerb>被</ACTION_lightVerb><ENTITY_nouny>大家</ENTITY_nouny><ACTION_verb>盯上</ACTION_verb>",
                "，",
                "<MODAL>才</MODAL><ACTION_verb>證明</ACTION_verb><ENTITY_pronoun>你</ENTITY_pronoun><ACTION_verb>有</ACTION_verb><ENTITY_noun>實力</ENTITY_noun>",
                "。"],
 "result_segmentation": "會/被/大家/盯上/，/才/證明/你/有/實力/。/",
 "status": True,
 "version": "v118",
 "word_count_balance": 9985,
 "product": "https://api.droidtown.co/product/",
 "document": "https://api.droidtown.co/document/"
}
```
### 列出斷詞結果所有詞性標記的內容詞 ###
可以依需求找出「名詞」、「動詞」或是「形容詞」…等詞彙語意本身已經完整的詞彙。
```
inputSTR = "你計劃過地球人類補完計劃"
resultDICT = articut.parse(inputSTR, level="lv1")
pprint(resultDICT["result_pos"])
#列出所有的 content word.
contentWordLIST = articut.getContentWordLIST(resultDICT)
pprint(contentWordLIST)
#列出所有的 verb word. (動詞)
verbStemLIST = articut.getVerbStemLIST(resultDICT)
pprint(verbStemLIST)
#列出所有的 noun word. (名詞)
nounStemLIST = articut.getNounStemLIST(resultDICT)
pprint(nounStemLIST)
#列出所有的 location word. (地方名稱)
locationStemLIST = articut.getLocationStemLIST(resultDICT)
pprint(locationStemLIST)
```
### 回傳結果 ###
```
#resultDICT["result_pos"]
["<ENTITY_pronoun>你</ENTITY_pronoun><ACTION_verb>計劃</ACTION_verb><ASPECT>過</ASPECT><LOCATION>地球</LOCATION><ENTITY_oov>人類</ENTITY_oov><ACTION_verb>補完</ACTION_verb><ENTITY_nounHead>計劃</ENTITY_nounHead>"]
#列出所有的 content word.
[[(177, 179, "計劃"), (144, 145, "補"), (116, 118, "人類"), (47, 49, "計劃")]]
#列出所有的 verb word. (動詞)
[[(41, 43, '計劃'), (111, 112, '補')]]
#列出所有的 noun word. (名詞)
[[(88, 90, '人類'), (138, 140, '計劃')]]
#列出所有的 location word. (地方名稱)
[[(62, 64, "地球")]]
```
### 取得 Articut 版本列表
```
resultDICT = articut.versions()
pprint(resultDICT)
```
### 回傳結果
```
{"msg": "Success!",
 "status": True,
 "versions": [{"level": ["lv1", "lv2"],
               "release_date": "2019-04-25",
               "version": "latest"},
              {"level": ["lv1", "lv2"],
               "release_date": "2019-04-25",
               "version": "v118"},
              {"level": ["lv1", "lv2"],
               "release_date": "2019-04-24",
               "version": "v117"},...
}

%package help
Summary:	Development documents and examples for ArticutAPI
Provides:	python3-ArticutAPI-doc
%description help
# ArticutAPI
## 安裝方法
```sh
pip3 install ArticutAPI
```
## 說明文件
函數說明請參閱 Docs/index.html
## 使用方法
### Articut CWS (Chinese word segmentation)
```
from ArticutAPI import Articut
from pprint import pprint
username = "" #這裡填入您在 https://api.droidtown.co 使用的帳號 email。若使用空字串，則預設使用每小時 2000 字的公用額度。
apikey   = "" #這裡填入您在 https://api.droidtown.co 登入後取得的 api Key。若使用空字串，則預設使用每小時 2000 字的公用額度。
articut = Articut(username, apikey)
inputSTR = "會被大家盯上，才證明你有實力。"
resultDICT = articut.parse(inputSTR)
pprint(resultDICT)
```
### 回傳結果
```
{"exec_time": 0.06723856925964355,
 "level": "lv2",
 "msg": "Success!",
 "result_pos": ["<MODAL>會</MODAL><ACTION_lightVerb>被</ACTION_lightVerb><ENTITY_nouny>大家</ENTITY_nouny><ACTION_verb>盯上</ACTION_verb>",
                "，",
                "<MODAL>才</MODAL><ACTION_verb>證明</ACTION_verb><ENTITY_pronoun>你</ENTITY_pronoun><ACTION_verb>有</ACTION_verb><ENTITY_noun>實力</ENTITY_noun>",
                "。"],
 "result_segmentation": "會/被/大家/盯上/，/才/證明/你/有/實力/。/",
 "status": True,
 "version": "v118",
 "word_count_balance": 9985,
 "product": "https://api.droidtown.co/product/",
 "document": "https://api.droidtown.co/document/"
}
```
### 列出斷詞結果所有詞性標記的內容詞 ###
可以依需求找出「名詞」、「動詞」或是「形容詞」…等詞彙語意本身已經完整的詞彙。
```
inputSTR = "你計劃過地球人類補完計劃"
resultDICT = articut.parse(inputSTR, level="lv1")
pprint(resultDICT["result_pos"])
#列出所有的 content word.
contentWordLIST = articut.getContentWordLIST(resultDICT)
pprint(contentWordLIST)
#列出所有的 verb word. (動詞)
verbStemLIST = articut.getVerbStemLIST(resultDICT)
pprint(verbStemLIST)
#列出所有的 noun word. (名詞)
nounStemLIST = articut.getNounStemLIST(resultDICT)
pprint(nounStemLIST)
#列出所有的 location word. (地方名稱)
locationStemLIST = articut.getLocationStemLIST(resultDICT)
pprint(locationStemLIST)
```
### 回傳結果 ###
```
#resultDICT["result_pos"]
["<ENTITY_pronoun>你</ENTITY_pronoun><ACTION_verb>計劃</ACTION_verb><ASPECT>過</ASPECT><LOCATION>地球</LOCATION><ENTITY_oov>人類</ENTITY_oov><ACTION_verb>補完</ACTION_verb><ENTITY_nounHead>計劃</ENTITY_nounHead>"]
#列出所有的 content word.
[[(177, 179, "計劃"), (144, 145, "補"), (116, 118, "人類"), (47, 49, "計劃")]]
#列出所有的 verb word. (動詞)
[[(41, 43, '計劃'), (111, 112, '補')]]
#列出所有的 noun word. (名詞)
[[(88, 90, '人類'), (138, 140, '計劃')]]
#列出所有的 location word. (地方名稱)
[[(62, 64, "地球")]]
```
### 取得 Articut 版本列表
```
resultDICT = articut.versions()
pprint(resultDICT)
```
### 回傳結果
```
{"msg": "Success!",
 "status": True,
 "versions": [{"level": ["lv1", "lv2"],
               "release_date": "2019-04-25",
               "version": "latest"},
              {"level": ["lv1", "lv2"],
               "release_date": "2019-04-25",
               "version": "v118"},
              {"level": ["lv1", "lv2"],
               "release_date": "2019-04-24",
               "version": "v117"},...
}

%prep
%autosetup -n ArticutAPI-1.3.0

%build
%py3_build

%install
%py3_install
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}
if [ -d usr/lib ]; then
	find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
	find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
	find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
	find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst
fi
touch doclist.lst
if [ -d usr/share/man ]; then
	find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .

%files -n python3-ArticutAPI -f filelist.lst
%dir %{python3_sitelib}/*

%files help -f doclist.lst
%{_docdir}/*

%changelog
* Tue May 30 2023 Python_Bot <Python_Bot@openeuler.org> - 1.3.0-1
- Package Spec generated