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@@ -0,0 +1 @@ +/konoha-5.4.0.tar.gz diff --git a/python-konoha.spec b/python-konoha.spec new file mode 100644 index 0000000..fd2eab9 --- /dev/null +++ b/python-konoha.spec @@ -0,0 +1,652 @@ +%global _empty_manifest_terminate_build 0 +Name: python-konoha +Version: 5.4.0 +Release: 1 +Summary: A tiny sentence/word tokenizer for Japanese text written in Python +License: MIT +URL: https://pypi.org/project/konoha/ +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/f3/f1/a83f55d8e7e824d483bccce3902335d130b572b5a17bde8b282acd13d504/konoha-5.4.0.tar.gz +BuildArch: noarch + +Requires: python3-importlib-metadata +Requires: python3-overrides +Requires: python3-janome +Requires: python3-natto-py +Requires: python3-kytea +Requires: python3-sentencepiece +Requires: python3-sudachipy +Requires: python3-boto3 +Requires: python3-fastapi +Requires: python3-uvicorn +Requires: python3-sudachidict-core +Requires: python3-sphinx +Requires: python3-pydata-sphinx-theme +Requires: python3-nagisa +Requires: python3-rich +Requires: python3-requests + +%description +# ๐ฟ Konoha: Simple wrapper of Japanese Tokenizers + +[](https://colab.research.google.com/github/himkt/konoha/blob/main/example/Konoha_Example.ipynb) +<p align="center"><img src="https://user-images.githubusercontent.com/5164000/120913279-e7d62380-c6d0-11eb-8d17-6571277cdf27.gif" width="95%"></p> + +[](https://github.com/himkt/konoha/stargazers) + +[](https://pepy.tech/project/konoha) +[](https://pepy.tech/project/konoha/month) +[](https://pepy.tech/project/konoha/week) + +[](https://github.com/himkt/konoha/actions) +[](https://konoha.readthedocs.io/en/latest/?badge=latest) + +[](https://pypi.python.org/pypi/konoha) +[](https://github.com/himkt/konoha/issues) +[](https://github.com/himkt/konoha/issues) + +`Konoha` is a Python library for providing easy-to-use integrated interface of various Japanese tokenizers, +which enables you to switch a tokenizer and boost your pre-processing. + +## Supported tokenizers + +<a href="https://github.com/buruzaemon/natto-py"><img src="https://img.shields.io/badge/MeCab-natto--py-ff69b4"></a> +<a href="https://github.com/chezou/Mykytea-python"><img src="https://img.shields.io/badge/KyTea-Mykytea--python-ff69b4"></a> +<a href="https://github.com/mocobeta/janome"><img src="https://img.shields.io/badge/Janome-janome-ff69b4"></a> +<a href="https://github.com/WorksApplications/SudachiPy"><img src="https://img.shields.io/badge/Sudachi-sudachipy-ff69b4"></a> +<a href="https://github.com/google/sentencepiece"><img src="https://img.shields.io/badge/Sentencepiece-sentencepiece-ff69b4"></a> +<a href="https://github.com/taishi-i/nagisa"><img src="https://img.shields.io/badge/nagisa-nagisa-ff69b4"></a> + +Also, `konoha` provides rule-based tokenizers (whitespace, character) and a rule-based sentence splitter. + + +## Quick Start with Docker + +Simply run followings on your computer: + +```bash +docker run --rm -p 8000:8000 -t himkt/konoha # from DockerHub +``` + +Or you can build image on your machine: + +```bash +git clone https://github.com/himkt/konoha # download konoha +cd konoha && docker-compose up --build # build and launch container +``` + +Tokenization is done by posting a json object to `localhost:8000/api/v1/tokenize`. +You can also batch tokenize by passing `texts: ["๏ผใค็ฎใฎๅ
ฅๅ", "๏ผใค็ฎใฎๅ
ฅๅ"]` to `localhost:8000/api/v1/batch_tokenize`. + +(API documentation is available on `localhost:8000/redoc`, you can check it using your web browser) + +Send a request using `curl` on your terminal. +Note that a path to an endpoint is changed in v4.6.4. +Please check our release note (https://github.com/himkt/konoha/releases/tag/v4.6.4). + +```json +$ curl localhost:8000/api/v1/tokenize -X POST -H "Content-Type: application/json" \ + -d '{"tokenizer": "mecab", "text": "ใใใฏใใณใงใ"}' + +{ + "tokens": [ + [ + { + "surface": "ใใ", + "part_of_speech": "ๅ่ฉ" + }, + { + "surface": "ใฏ", + "part_of_speech": "ๅฉ่ฉ" + }, + { + "surface": "ใใณ", + "part_of_speech": "ๅ่ฉ" + }, + { + "surface": "ใงใ", + "part_of_speech": "ๅฉๅ่ฉ" + } + ] + ] +} +``` + + +## Installation + + +I recommend you to install konoha by `pip install 'konoha[all]'`. + +- Install konoha with a specific tokenizer: `pip install 'konoha[(tokenizer_name)]`. +- Install konoha with a specific tokenizer and remote file support: `pip install 'konoha[(tokenizer_name),remote]'` + +If you want to install konoha with a tokenizer, please install konoha with a specific tokenizer +(e.g. `konoha[mecab]`, `konoha[sudachi]`, ...etc) or install tokenizers individually. + + +## Example + +### Word level tokenization + +```python +from konoha import WordTokenizer + +sentence = '่ช็ถ่จ่ชๅฆ็ใๅๅผทใใฆใใพใ' + +tokenizer = WordTokenizer('MeCab') +print(tokenizer.tokenize(sentence)) +# => [่ช็ถ, ่จ่ช, ๅฆ็, ใ, ๅๅผท, ใ, ใฆ, ใ, ใพใ] + +tokenizer = WordTokenizer('Sentencepiece', model_path="data/model.spm") +print(tokenizer.tokenize(sentence)) +# => [โ, ่ช็ถ, ่จ่ช, ๅฆ็, ใ, ๅๅผท, ใ, ใฆใใพใ] +``` + +For more detail, please see the `example/` directory. + +### Remote files + +Konoha supports dictionary and model on cloud storage (currently supports Amazon S3). +It requires installing konoha with the `remote` option, see [Installation](#installation). + +```python +# download user dictionary from S3 +word_tokenizer = WordTokenizer("mecab", user_dictionary_path="s3://abc/xxx.dic") +print(word_tokenizer.tokenize(sentence)) + +# download system dictionary from S3 +word_tokenizer = WordTokenizer("mecab", system_dictionary_path="s3://abc/yyy") +print(word_tokenizer.tokenize(sentence)) + +# download model file from S3 +word_tokenizer = WordTokenizer("sentencepiece", model_path="s3://abc/zzz.model") +print(word_tokenizer.tokenize(sentence)) +``` + +### Sentence level tokenization + +```python +from konoha import SentenceTokenizer + +sentence = "็งใฏ็ซใ ใๅๅใชใใฆใใฎใฏใชใใใ ใ๏ผใใใใใใใใใงๅๅใ ใใใใ" + +tokenizer = SentenceTokenizer() +print(tokenizer.tokenize(sentence)) +# => ['็งใฏ็ซใ ใ', 'ๅๅใชใใฆใใฎใฏใชใใ', 'ใ ใ๏ผใใใใใใใใใงๅๅใ ใใใใ'] +``` + +You can change symbols for a sentence splitter and bracket expression. + +1. sentence splitter + +```python +sentence = "็งใฏ็ซใ ใๅๅใชใใฆใใฎใฏใชใ๏ผใ ใ๏ผใใใใใใใใใงๅๅใ ใใใใ" + +tokenizer = SentenceTokenizer(period="๏ผ") +print(tokenizer.tokenize(sentence)) +# => ['็งใฏ็ซใ ใๅๅใชใใฆใใฎใฏใชใ๏ผ', 'ใ ใ๏ผใใใใใใใใใงๅๅใ ใใใใ'] +``` + +2. bracket expression + +```python +sentence = "็งใฏ็ซใ ใๅๅใชใใฆใใฎใฏใชใใใ ใ๏ผใใใใใใใใใงๅๅใ ใใใใ" + +tokenizer = SentenceTokenizer( + patterns=SentenceTokenizer.PATTERNS + [re.compile(r"ใ.*?ใ")], +) +print(tokenizer.tokenize(sentence)) +# => ['็งใฏ็ซใ ใ', 'ๅๅใชใใฆใใฎใฏใชใใ', 'ใ ใ๏ผใใใใใใใใใงๅๅใ ใใใใ'] +``` + + +## Test + +``` +python -m pytest +``` + +## Article + +- [ใใผใฏใใคใถใใใๆใใซๅใๆฟใใใฉใคใใฉใช konoha ใไฝใฃใ](https://qiita.com/klis/items/bb9ffa4d9c886af0f531) +- [ๆฅๆฌ่ช่งฃๆใใผใซ Konoha ใซ AllenNLP ้ฃๆบๆฉ่ฝใๅฎ่ฃ
ใใ](https://qiita.com/klis/items/f1d29cb431d1bf879898) + +## Acknowledgement + +Sentencepiece model used in test is provided by @yoheikikuta. Thanks! + + +%package -n python3-konoha +Summary: A tiny sentence/word tokenizer for Japanese text written in Python +Provides: python-konoha +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-konoha +# ๐ฟ Konoha: Simple wrapper of Japanese Tokenizers + +[](https://colab.research.google.com/github/himkt/konoha/blob/main/example/Konoha_Example.ipynb) +<p align="center"><img src="https://user-images.githubusercontent.com/5164000/120913279-e7d62380-c6d0-11eb-8d17-6571277cdf27.gif" width="95%"></p> + +[](https://github.com/himkt/konoha/stargazers) + +[](https://pepy.tech/project/konoha) +[](https://pepy.tech/project/konoha/month) +[](https://pepy.tech/project/konoha/week) + +[](https://github.com/himkt/konoha/actions) +[](https://konoha.readthedocs.io/en/latest/?badge=latest) + +[](https://pypi.python.org/pypi/konoha) +[](https://github.com/himkt/konoha/issues) +[](https://github.com/himkt/konoha/issues) + +`Konoha` is a Python library for providing easy-to-use integrated interface of various Japanese tokenizers, +which enables you to switch a tokenizer and boost your pre-processing. + +## Supported tokenizers + +<a href="https://github.com/buruzaemon/natto-py"><img src="https://img.shields.io/badge/MeCab-natto--py-ff69b4"></a> +<a href="https://github.com/chezou/Mykytea-python"><img src="https://img.shields.io/badge/KyTea-Mykytea--python-ff69b4"></a> +<a href="https://github.com/mocobeta/janome"><img src="https://img.shields.io/badge/Janome-janome-ff69b4"></a> +<a href="https://github.com/WorksApplications/SudachiPy"><img src="https://img.shields.io/badge/Sudachi-sudachipy-ff69b4"></a> +<a href="https://github.com/google/sentencepiece"><img src="https://img.shields.io/badge/Sentencepiece-sentencepiece-ff69b4"></a> +<a href="https://github.com/taishi-i/nagisa"><img src="https://img.shields.io/badge/nagisa-nagisa-ff69b4"></a> + +Also, `konoha` provides rule-based tokenizers (whitespace, character) and a rule-based sentence splitter. + + +## Quick Start with Docker + +Simply run followings on your computer: + +```bash +docker run --rm -p 8000:8000 -t himkt/konoha # from DockerHub +``` + +Or you can build image on your machine: + +```bash +git clone https://github.com/himkt/konoha # download konoha +cd konoha && docker-compose up --build # build and launch container +``` + +Tokenization is done by posting a json object to `localhost:8000/api/v1/tokenize`. +You can also batch tokenize by passing `texts: ["๏ผใค็ฎใฎๅ
ฅๅ", "๏ผใค็ฎใฎๅ
ฅๅ"]` to `localhost:8000/api/v1/batch_tokenize`. + +(API documentation is available on `localhost:8000/redoc`, you can check it using your web browser) + +Send a request using `curl` on your terminal. +Note that a path to an endpoint is changed in v4.6.4. +Please check our release note (https://github.com/himkt/konoha/releases/tag/v4.6.4). + +```json +$ curl localhost:8000/api/v1/tokenize -X POST -H "Content-Type: application/json" \ + -d '{"tokenizer": "mecab", "text": "ใใใฏใใณใงใ"}' + +{ + "tokens": [ + [ + { + "surface": "ใใ", + "part_of_speech": "ๅ่ฉ" + }, + { + "surface": "ใฏ", + "part_of_speech": "ๅฉ่ฉ" + }, + { + "surface": "ใใณ", + "part_of_speech": "ๅ่ฉ" + }, + { + "surface": "ใงใ", + "part_of_speech": "ๅฉๅ่ฉ" + } + ] + ] +} +``` + + +## Installation + + +I recommend you to install konoha by `pip install 'konoha[all]'`. + +- Install konoha with a specific tokenizer: `pip install 'konoha[(tokenizer_name)]`. +- Install konoha with a specific tokenizer and remote file support: `pip install 'konoha[(tokenizer_name),remote]'` + +If you want to install konoha with a tokenizer, please install konoha with a specific tokenizer +(e.g. `konoha[mecab]`, `konoha[sudachi]`, ...etc) or install tokenizers individually. + + +## Example + +### Word level tokenization + +```python +from konoha import WordTokenizer + +sentence = '่ช็ถ่จ่ชๅฆ็ใๅๅผทใใฆใใพใ' + +tokenizer = WordTokenizer('MeCab') +print(tokenizer.tokenize(sentence)) +# => [่ช็ถ, ่จ่ช, ๅฆ็, ใ, ๅๅผท, ใ, ใฆ, ใ, ใพใ] + +tokenizer = WordTokenizer('Sentencepiece', model_path="data/model.spm") +print(tokenizer.tokenize(sentence)) +# => [โ, ่ช็ถ, ่จ่ช, ๅฆ็, ใ, ๅๅผท, ใ, ใฆใใพใ] +``` + +For more detail, please see the `example/` directory. + +### Remote files + +Konoha supports dictionary and model on cloud storage (currently supports Amazon S3). +It requires installing konoha with the `remote` option, see [Installation](#installation). + +```python +# download user dictionary from S3 +word_tokenizer = WordTokenizer("mecab", user_dictionary_path="s3://abc/xxx.dic") +print(word_tokenizer.tokenize(sentence)) + +# download system dictionary from S3 +word_tokenizer = WordTokenizer("mecab", system_dictionary_path="s3://abc/yyy") +print(word_tokenizer.tokenize(sentence)) + +# download model file from S3 +word_tokenizer = WordTokenizer("sentencepiece", model_path="s3://abc/zzz.model") +print(word_tokenizer.tokenize(sentence)) +``` + +### Sentence level tokenization + +```python +from konoha import SentenceTokenizer + +sentence = "็งใฏ็ซใ ใๅๅใชใใฆใใฎใฏใชใใใ ใ๏ผใใใใใใใใใงๅๅใ ใใใใ" + +tokenizer = SentenceTokenizer() +print(tokenizer.tokenize(sentence)) +# => ['็งใฏ็ซใ ใ', 'ๅๅใชใใฆใใฎใฏใชใใ', 'ใ ใ๏ผใใใใใใใใใงๅๅใ ใใใใ'] +``` + +You can change symbols for a sentence splitter and bracket expression. + +1. sentence splitter + +```python +sentence = "็งใฏ็ซใ ใๅๅใชใใฆใใฎใฏใชใ๏ผใ ใ๏ผใใใใใใใใใงๅๅใ ใใใใ" + +tokenizer = SentenceTokenizer(period="๏ผ") +print(tokenizer.tokenize(sentence)) +# => ['็งใฏ็ซใ ใๅๅใชใใฆใใฎใฏใชใ๏ผ', 'ใ ใ๏ผใใใใใใใใใงๅๅใ ใใใใ'] +``` + +2. bracket expression + +```python +sentence = "็งใฏ็ซใ ใๅๅใชใใฆใใฎใฏใชใใใ ใ๏ผใใใใใใใใใงๅๅใ ใใใใ" + +tokenizer = SentenceTokenizer( + patterns=SentenceTokenizer.PATTERNS + [re.compile(r"ใ.*?ใ")], +) +print(tokenizer.tokenize(sentence)) +# => ['็งใฏ็ซใ ใ', 'ๅๅใชใใฆใใฎใฏใชใใ', 'ใ ใ๏ผใใใใใใใใใงๅๅใ ใใใใ'] +``` + + +## Test + +``` +python -m pytest +``` + +## Article + +- [ใใผใฏใใคใถใใใๆใใซๅใๆฟใใใฉใคใใฉใช konoha ใไฝใฃใ](https://qiita.com/klis/items/bb9ffa4d9c886af0f531) +- [ๆฅๆฌ่ช่งฃๆใใผใซ Konoha ใซ AllenNLP ้ฃๆบๆฉ่ฝใๅฎ่ฃ
ใใ](https://qiita.com/klis/items/f1d29cb431d1bf879898) + +## Acknowledgement + +Sentencepiece model used in test is provided by @yoheikikuta. Thanks! + + +%package help +Summary: Development documents and examples for konoha +Provides: python3-konoha-doc +%description help +# ๐ฟ Konoha: Simple wrapper of Japanese Tokenizers + +[](https://colab.research.google.com/github/himkt/konoha/blob/main/example/Konoha_Example.ipynb) +<p align="center"><img src="https://user-images.githubusercontent.com/5164000/120913279-e7d62380-c6d0-11eb-8d17-6571277cdf27.gif" width="95%"></p> + +[](https://github.com/himkt/konoha/stargazers) + +[](https://pepy.tech/project/konoha) +[](https://pepy.tech/project/konoha/month) +[](https://pepy.tech/project/konoha/week) + +[](https://github.com/himkt/konoha/actions) +[](https://konoha.readthedocs.io/en/latest/?badge=latest) + +[](https://pypi.python.org/pypi/konoha) +[](https://github.com/himkt/konoha/issues) +[](https://github.com/himkt/konoha/issues) + +`Konoha` is a Python library for providing easy-to-use integrated interface of various Japanese tokenizers, +which enables you to switch a tokenizer and boost your pre-processing. + +## Supported tokenizers + +<a href="https://github.com/buruzaemon/natto-py"><img src="https://img.shields.io/badge/MeCab-natto--py-ff69b4"></a> +<a href="https://github.com/chezou/Mykytea-python"><img src="https://img.shields.io/badge/KyTea-Mykytea--python-ff69b4"></a> +<a href="https://github.com/mocobeta/janome"><img src="https://img.shields.io/badge/Janome-janome-ff69b4"></a> +<a href="https://github.com/WorksApplications/SudachiPy"><img src="https://img.shields.io/badge/Sudachi-sudachipy-ff69b4"></a> +<a href="https://github.com/google/sentencepiece"><img src="https://img.shields.io/badge/Sentencepiece-sentencepiece-ff69b4"></a> +<a href="https://github.com/taishi-i/nagisa"><img src="https://img.shields.io/badge/nagisa-nagisa-ff69b4"></a> + +Also, `konoha` provides rule-based tokenizers (whitespace, character) and a rule-based sentence splitter. + + +## Quick Start with Docker + +Simply run followings on your computer: + +```bash +docker run --rm -p 8000:8000 -t himkt/konoha # from DockerHub +``` + +Or you can build image on your machine: + +```bash +git clone https://github.com/himkt/konoha # download konoha +cd konoha && docker-compose up --build # build and launch container +``` + +Tokenization is done by posting a json object to `localhost:8000/api/v1/tokenize`. +You can also batch tokenize by passing `texts: ["๏ผใค็ฎใฎๅ
ฅๅ", "๏ผใค็ฎใฎๅ
ฅๅ"]` to `localhost:8000/api/v1/batch_tokenize`. + +(API documentation is available on `localhost:8000/redoc`, you can check it using your web browser) + +Send a request using `curl` on your terminal. +Note that a path to an endpoint is changed in v4.6.4. +Please check our release note (https://github.com/himkt/konoha/releases/tag/v4.6.4). + +```json +$ curl localhost:8000/api/v1/tokenize -X POST -H "Content-Type: application/json" \ + -d '{"tokenizer": "mecab", "text": "ใใใฏใใณใงใ"}' + +{ + "tokens": [ + [ + { + "surface": "ใใ", + "part_of_speech": "ๅ่ฉ" + }, + { + "surface": "ใฏ", + "part_of_speech": "ๅฉ่ฉ" + }, + { + "surface": "ใใณ", + "part_of_speech": "ๅ่ฉ" + }, + { + "surface": "ใงใ", + "part_of_speech": "ๅฉๅ่ฉ" + } + ] + ] +} +``` + + +## Installation + + +I recommend you to install konoha by `pip install 'konoha[all]'`. + +- Install konoha with a specific tokenizer: `pip install 'konoha[(tokenizer_name)]`. +- Install konoha with a specific tokenizer and remote file support: `pip install 'konoha[(tokenizer_name),remote]'` + +If you want to install konoha with a tokenizer, please install konoha with a specific tokenizer +(e.g. `konoha[mecab]`, `konoha[sudachi]`, ...etc) or install tokenizers individually. + + +## Example + +### Word level tokenization + +```python +from konoha import WordTokenizer + +sentence = '่ช็ถ่จ่ชๅฆ็ใๅๅผทใใฆใใพใ' + +tokenizer = WordTokenizer('MeCab') +print(tokenizer.tokenize(sentence)) +# => [่ช็ถ, ่จ่ช, ๅฆ็, ใ, ๅๅผท, ใ, ใฆ, ใ, ใพใ] + +tokenizer = WordTokenizer('Sentencepiece', model_path="data/model.spm") +print(tokenizer.tokenize(sentence)) +# => [โ, ่ช็ถ, ่จ่ช, ๅฆ็, ใ, ๅๅผท, ใ, ใฆใใพใ] +``` + +For more detail, please see the `example/` directory. + +### Remote files + +Konoha supports dictionary and model on cloud storage (currently supports Amazon S3). +It requires installing konoha with the `remote` option, see [Installation](#installation). + +```python +# download user dictionary from S3 +word_tokenizer = WordTokenizer("mecab", user_dictionary_path="s3://abc/xxx.dic") +print(word_tokenizer.tokenize(sentence)) + +# download system dictionary from S3 +word_tokenizer = WordTokenizer("mecab", system_dictionary_path="s3://abc/yyy") +print(word_tokenizer.tokenize(sentence)) + +# download model file from S3 +word_tokenizer = WordTokenizer("sentencepiece", model_path="s3://abc/zzz.model") +print(word_tokenizer.tokenize(sentence)) +``` + +### Sentence level tokenization + +```python +from konoha import SentenceTokenizer + +sentence = "็งใฏ็ซใ ใๅๅใชใใฆใใฎใฏใชใใใ ใ๏ผใใใใใใใใใงๅๅใ ใใใใ" + +tokenizer = SentenceTokenizer() +print(tokenizer.tokenize(sentence)) +# => ['็งใฏ็ซใ ใ', 'ๅๅใชใใฆใใฎใฏใชใใ', 'ใ ใ๏ผใใใใใใใใใงๅๅใ ใใใใ'] +``` + +You can change symbols for a sentence splitter and bracket expression. + +1. sentence splitter + +```python +sentence = "็งใฏ็ซใ ใๅๅใชใใฆใใฎใฏใชใ๏ผใ ใ๏ผใใใใใใใใใงๅๅใ ใใใใ" + +tokenizer = SentenceTokenizer(period="๏ผ") +print(tokenizer.tokenize(sentence)) +# => ['็งใฏ็ซใ ใๅๅใชใใฆใใฎใฏใชใ๏ผ', 'ใ ใ๏ผใใใใใใใใใงๅๅใ ใใใใ'] +``` + +2. bracket expression + +```python +sentence = "็งใฏ็ซใ ใๅๅใชใใฆใใฎใฏใชใใใ ใ๏ผใใใใใใใใใงๅๅใ ใใใใ" + +tokenizer = SentenceTokenizer( + patterns=SentenceTokenizer.PATTERNS + [re.compile(r"ใ.*?ใ")], +) +print(tokenizer.tokenize(sentence)) +# => ['็งใฏ็ซใ ใ', 'ๅๅใชใใฆใใฎใฏใชใใ', 'ใ ใ๏ผใใใใใใใใใงๅๅใ ใใใใ'] +``` + + +## Test + +``` +python -m pytest +``` + +## Article + +- [ใใผใฏใใคใถใใใๆใใซๅใๆฟใใใฉใคใใฉใช konoha ใไฝใฃใ](https://qiita.com/klis/items/bb9ffa4d9c886af0f531) +- [ๆฅๆฌ่ช่งฃๆใใผใซ Konoha ใซ AllenNLP ้ฃๆบๆฉ่ฝใๅฎ่ฃ
ใใ](https://qiita.com/klis/items/f1d29cb431d1bf879898) + +## Acknowledgement + +Sentencepiece model used in test is provided by @yoheikikuta. Thanks! + + +%prep +%autosetup -n konoha-5.4.0 + +%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-konoha -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Mon Apr 10 2023 Python_Bot <Python_Bot@openeuler.org> - 5.4.0-1 +- Package Spec generated @@ -0,0 +1 @@ +4babab57ca6539800f5b959e6a0793d7 konoha-5.4.0.tar.gz |