Metadata-Version: 2.1
Name: SudachiPy
Version: 0.2.0.1
Summary: Python version of Sudachi, the Japanese Morphological Analyzer
Home-page: https://github.com/WorksApplications/SudachiPy
Author: Works Applications
Author-email: takaoka_k@worksap.co.jp
License: Apache-2.0
Description: # SudachiPy
        [![Build Status](https://travis-ci.com/WorksApplications/SudachiPy.svg?branch=develop)](https://travis-ci.com/WorksApplications/SudachiPy)
        
        SudachiPy is a Python version of [Sudachi](https://github.com/WorksApplications/Sudachi), a Japanese morphological analyzer.
        
        Sudachi & SudachiPy are developed in [WAP Tokushima Laboratory of AI and NLP](http://nlp.worksap.co.jp/), an institute under [Works Applications](http://www.worksap.com/) that focuses on Natural Language Processing (NLP).
        
        **Warning: SudachiPy is still under development, and some of the functions are still not complete. Please use it at your own risk.**
        
        
        ## Setup
        
        SudachiPy requires Python3.5+.
        
        SudachiPy is not registered to PyPI just yet, so you may not install it via `pip` command at the moment.
        
        ```
        $ pip install -e git+git://github.com/WorksApplications/SudachiPy@develop#egg=SudachiPy
        ```
        The dictionary file is not included in the repository. You can get the built dictionary from [Releases · WorksApplications/Sudachi](https://github.com/WorksApplications/Sudachi/releases). Please download either `sudachi-x.y.z-dictionary-core.zip` or `sudachi-x.y.z-dictionary-full.zip`, unzip and rename it to `system.dic`, then place it under `SudachiPy/resources/`. In the end, we would like to make a flow to get these resources via the code, like [NLTK](https://www.nltk.org/data.html) (e.g., `import nltk; nltk.download()`) or [spaCy](https://spacy.io/usage/models) (e.g., `$python -m spacy download en`).
        
        ## Usage
        
        ### As a command
        
        After installing SudachiPy, you may also use it in the terminal via command `sudachipy`.
        `sudachipy` has 3 subcommands (in default `tokenize`)
        
        ```bash
        $ sudachipy tokenize -h
        usage: sudachipy tokenize [-h] [-r file] [-m {A,B,C}] [-o file] [-a] [-d]
                                  file [file ...]
        
        Tokenize Text
        
        positional arguments:
          file        text written in utf-8
        
        optional arguments:
          -h, --help  show this help message and exit
          -r file     the setting file in JSON format
          -m {A,B,C}  the mode of splitting
          -o file     the output file
          -a          print all of the fields
          -d          print the debug information
        ```
        ```bash
        $ sudachipy build -h
        usage: sudachipy build [-h] [-o file] [-d string] -m file file [file ...]
        
        Build Sudachi Dictionary
        
        positional arguments:
          file        source files with CSV format (one of more)
        
        optional arguments:
          -h, --help  show this help message and exit
          -o file     output file (default: system.dic)
          -d string   description comment to be embedded on dictionary
        
        required named arguments:
          -m file     connection matrix file with MeCab's matrix.def format
        ```
        ```bash
        $ sudachipy ubuild -h
        usage: sudachipy ubuild [-h] [-d string] [-o file] [-s file] file [file ...]
        
        Build User Dictionary
        
        positional arguments:
          file        source files with CSV format (one or more)
        
        optional arguments:
          -h, --help  show this help message and exit
          -d string   description comment to be embedded on dictionary
          -o file     output file (default: user.dic)
          -s file     system dictionary (default: ${SUDACHIPY}/resouces/system.dic)
        ```
        
        ### As a Python package
        
        Here is an example usage;
        
        ```python
        from sudachipy import tokenizer
        from sudachipy import dictionary
        
        
        tokenizer_obj = dictionary.Dictionary().create()
        
        
        # Multi-granular tokenization
        # (following results are w/ `system_full.dic`
        # you may not be able to replicate this particular example w/ `system_core.dic`)
        
        mode = tokenizer.Tokenizer.SplitMode.C
        [m.surface() for m in tokenizer_obj.tokenize("医薬品安全管理責任者", mode)]
        # => ['医薬品安全管理責任者']
        
        mode = tokenizer.Tokenizer.SplitMode.B
        [m.surface() for m in tokenizer_obj.tokenize("医薬品安全管理責任者", mode)]
        # => ['医薬品', '安全', '管理', '責任者']
        
        mode = tokenizer.Tokenizer.SplitMode.A
        [m.surface() for m in tokenizer_obj.tokenize("医薬品安全管理責任者", mode)]
        # => ['医薬', '品', '安全', '管理', '責任', '者']
        
        
        # Morpheme information
        
        m = tokenizer_obj.tokenize("食べ", mode)[0]
        
        m.surface() # => '食べ'
        m.dictionary_form() # => '食べる'
        m.reading_form() # => 'タベ'
        m.part_of_speech() # => ['動詞', '一般', '*', '*', '下一段-バ行', '連用形-一般']
        
        
        # Normalization
        
        tokenizer_obj.tokenize("附属", mode)[0].normalized_form()
        # => '付属'
        tokenizer_obj.tokenize("SUMMER", mode)[0].normalized_form()
        # => 'サマー'
        tokenizer_obj.tokenize("シュミレーション", mode)[0].normalized_form()
        # => 'シミュレーション'
        ```
        
        ## For developer
        
        ### Code format
        
        You can use `./scripts/format.sh` and check if your code is in rule. `flake8` `flake8-import-order` `flake8-buitins` is required. See `requirements.txt`
        
        ### Test
        
        You can use `./script/test.sh` and check if not your change cause regression.
        
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