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        "author": "Narongdej Sarnsuwan",
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        "description": "# pythaiwordcut - Thai Wordcut in Python\n\n[![Codacy Badge](https://api.codacy.com/project/badge/Grade/c4cb39daa5a54ffd9c1a797072e0f6d2)](https://www.codacy.com/app/narongdejsrn/pythaiwordcut?utm_source=github.com&amp;utm_medium=referral&amp;utm_content=narongdejsrn/pythaiwordcut&amp;utm_campaign=Badge_Grade)\n![PyPI - Downloads](https://img.shields.io/pypi/dm/pythaiwordcut.svg)\n![PyPI - License](https://img.shields.io/pypi/l/pythaiwordcut.svg)\n![PyPI - Python Version](https://img.shields.io/pypi/pyversions/pythaiwordcut.svg)\n\n-----\n\nA simple Thai wordcut written in Python, based on Maximum Matching algorithm by [S. Manabu](http://www.aclweb.org/anthology/E14-4016)\n. Uses Lexitron (by [NECTEC](http://www.sansarn.com/lexto/license-lexitron.php)) dictionary as default\n\n> Please note: This project is under development and should not be use in production , all function and interface are subject to change. If you have issue or suggestion please feel free to ask, contribution is also very welcome :)\n\n## Installation\n\n```bash\npip install pythaiwordcut\n```\n\nor\n\n```bash\ngit clone https://github.com/zenyai/pythaiwordcut.git\npython setup.py install\n```\n\n## Usage\n\n```python\nimport pythaiwordcut as pwt\n\npt = pwt.wordcut(removeRepeat=True, stopDictionary=\"<full path to txt file>\", removeSpaces=True, minLength=1, stopNumber=False, removeNonCharacter=False, caseSensitive=True, ngram=(1, 2), negation=False)\nprint \"|\".join(pt.segment(u'\u0e17\u0e14\u0e2a\u0e2d\u0e1a\u0e01\u0e32\u0e23\u0e15\u0e31\u0e14\u0e04\u0e33'))\n```\n\n  * removeRepeat: remove intention insertion spelling error such as (\u0e2a\u0e1a\u0e32\u0e22\u0e22\u0e22\u0e22\u0e22\u0e22)\n  * stopDictionary: remove word that exist in this specify text file (one word one line)\n  * removeSpaces: remove blank space\n  * minLength: minimum length of each word\n  * stopNumber: remove number if exist\n  * removeNonCharacter: remove character that are not Thai or English character\n  * caseSensitive: if set to false, will remove stop word without regarding the case\n  * ngram: Add word ngram from (1, 2)\n  * negation: If set to true, then it will add NOT_ to every word after negation word and space",
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