{
    "info": {
        "author": "278Mt",
        "author_email": "278mt.l.meitner@gmail.com",
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            "License :: OSI Approved :: MIT License",
            "Programming Language :: Python :: 3.7",
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        "description": "\n\nCotohapPy: Cotoha for Python\n=========\n\n[![Downloads](https://pepy.tech/badge/cotohappy)](https://pepy.tech/project/cotohappy)\n[![Downloads](https://pepy.tech/badge/cotohappy/month)](https://pepy.tech/project/cotohappy/month)\n[![Downloads](https://pepy.tech/badge/cotohappy/week)](https://pepy.tech/project/cotohappy/week)\n\nCotohapPy (Japanese: \u30b3\u30c8\u30cf\u30c3\u30d4\u30fc) is for connecting to [Cotoha API](https://api.ce-cotoha.com/contents/), one of the Japanese morphological analysis engines, and is for reshaping the response more readably.\n\nInstallation\n------------\n\nThe easiest way to install the latest version is by using pip/easy_install to pull it from PyPI:\n\n```bash\npip install cotohappy\n```\n\nYou may also use Git to clone the repository from GitHub and install it manually:\n\n```bash\ngit clone https://github.com/278Mt/cotohappy.git\ncd cotohappy\npython setup.py install\n```\n\nPython 3.7 and 3.8 are supported (frequently updated).\n\nRequirements\n------------\n\n* json\n* requests\n\nUsage\n-----\n\nThis is one of the examples.\n\n```bash\n\u251c\u2500\u2500 payload.json\n\u2514\u2500\u2500 sjgyoen.py\n```\n\nJSON preperation (`payload.json`):\n\n```json\n{\n  \"AccessTokenPublishURL\": \"https://api.ce-cotoha.com/v1/oauth/accesstokens\",\n  \"APIBaseURL\"           : \"https://api.ce-cotoha.com/api/dev/\",\n  \"ClientId\"             : \"ABCDEFGHIJKLMNOPQRSTUVWXYZ123456\",\n  \"ClientSecret\"         : \"7890abcdefghijkl\"\n}\n```\n\nProgramme (`sjgyoen.py`)\n\n```python\nimport cotohappy\nimport requests\nfrom bs4 import BeautifulSoup\n\n\ndef get_kotonoha_story():\n\n    url = 'https://www.kotonohanoniwa.jp/page/product.html'\n    res = requests.get(url)\n\n    soup = BeautifulSoup(res.content, 'html.parser')\n    p = soup.find_all('p', class_='mb24')[-1]\n\n    return p.text\n\n\nif __name__ == '__main__':\n\n    coy = cotohappy.API()\n\n    \"\"\" getting parse \"\"\"\n    print('\\n#### parse origin ####')\n    sentence = get_kotonoha_story()\n    kuzure   = False\n    parse_li = coy.parse(sentence, kuzure)\n    for parse in parse_li:\n        print(parse)\n\n    print(parse.key_name)\n\n    \"\"\" getting tokens; it is a little more difficult than MeCab Janome \"\"\"\n    print('\\n#### parse tokens ####')\n    for parse in parse_li:\n        for token in parse.tokens:\n            print(token)\n\n    print(token.key_name)\n\n    \"\"\" if you extract just nouns, you write: \"\"\"\n    print('\\n#### extract nouns ####')\n    nouns: [str] = []\n    for parse in parse_li:\n        for token in parse.tokens:\n            if token.pos == '\u540d\u8a5e':\n                nouns.append(token.form)\n\n    print(nouns)\n\n```\n\nOutput:\n\n```\n#### parse origin ####\n\u9774\u8077\u4eba\u3092\t 0,1,D,1,2\n\u76ee\u6307\u3059\t 1,2,D,0,1\n\u9ad8\u6821\u751f\u30fb\u30bf\u30ab\u30aa\u306f\u3001\t 2,51,D,2,3\n\u96e8\u306e\t 3,4,D,0,1\n\u671d\u306f\t 4,7,D,0,1\n...\n\u4e92\u3044\u306e\t 47,48,D,0,1\n\u601d\u3044\u3092\t 48,51,D,0,1\n\u3088\u305d\u306b\t 49,51,D,0,1\n\u6885\u96e8\u306f\t 50,51,D,0,1\n\u660e\u3051\u3088\u3046\u3068\u3057\u3066\u3044\u305f\u3002\t 51,-1,O,0,6\nform\t id,head,dep,chunk_head,chunk_func\n\n#### parse tokens ####\n\u9774\t 0,\u30af\u30c4,\u9774,\u540d\u8a5e,*,*,*,*,*\n\u8077\u4eba\t 1,\u30b7\u30e7\u30af\u30cb\u30f3,\u8077\u4eba,\u540d\u8a5e,*,*,*,*,*\n\u3092\t 2,\u30f2,\u3092,\u683c\u52a9\u8a5e,\u9023\u7528,*,*,*,*\n\u76ee\u6307\t 3,\u30e1\u30b6,\u76ee\u6307\u3059,\u52d5\u8a5e\u8a9e\u5e79,S,*,*,*,*\n\u3059\t 4,\u30b9,\u3059,\u52d5\u8a5e\u63a5\u5c3e\u8f9e,\u9023\u4f53,*,*,*,*\n...\n\u3057\t 148,\u30b7,\u3057,\u52d5\u8a5e\u6d3b\u7528\u8a9e\u5c3e,*,*,*,*,*\n\u3066\t 149,\u30c6,\u3066,\u52d5\u8a5e\u63a5\u5c3e\u8f9e,\u63a5\u7d9a,\u9023\u7528,*,*,*\n\u3044\t 150,\u30a4,\u3044\u308b,\u52d5\u8a5e\u8a9e\u5e79,A,L\u3066\u9023\u7528,*,*,*\n\u305f\t 151,\u30bf,\u305f,\u52d5\u8a5e\u63a5\u5c3e\u8f9e,\u7d42\u6b62,*,*,*,*\n\u3002\t 152,,\u3002,\u53e5\u70b9,*,*,*,*,*\nform\t id,kana,lemma,pos,features[:5]\n\n#### extract nouns ####\n['\u9774', '\u8077\u4eba', '\u9ad8\u6821\u751f', '\u30bf\u30ab\u30aa', '\u96e8', '\u671d', '\u5b66\u6821', '\u516c\u5712', '\u65e5\u672c', '\u5ead\u5712', '\u9774', '\u30b9\u30b1\u30c3\u30c1', '\u3042\u308b\u65e5', '\u30bf\u30ab\u30aa', '\u3072\u3068\u308a', '\u7f36', '\u30d3\u30fc\u30eb', '\u5e74\u4e0a', '\u5973\u6027', '\u30e6\u30ad\u30ce', '\u3075\u305f\u308a', '\u7d04\u675f', '\u96e8', '\u65e5', '\u9022\u702c', '\u5fc3', '\u5c45\u5834\u6240', '\u30e6\u30ad\u30ce', '\u5f7c\u5973', '\u9774', '\u30bf\u30ab\u30aa', '\u516d\u6708', '\u7a7a', '\u63fa\u308c', '\u4e92\u3044', '\u601d\u3044', '\u3088\u305d', '\u6885\u96e8']\n```\n\nPlease check details on [examples](https://github.com/278Mt/cotohappy/tree/master/examples).\n\nWhats's new?\n------------\n\n### 0.4.1, 0.4.2\n\nPartial errors elimination.\n\n### 0.4.0\n\n`kuzure` and `default` become `kuzure=True` and `kuzure=False` \n\n### 0.3.6, 0.3.7\n\nPartial errors elimination.\n\n### 0.3.5\n\nIn version 0.3.5, you can choose translating mode: for example, \"information-seeking\" in sentence type, to \"\u60c5\u5831\u7372\u5f97\".\n\n### 0.3.4\n\nIn version 0.3.4, you can use technical term dictionaries on parse, named entity extraction, keyword extraction and similarity calculation. However, I, origin master of CotohapPy, cannot use nor examine the mode because I use Cotoha API for Developer, not for Enterprise. I want for Academic.\n\n\n",
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