Metadata-Version: 2.1
Name: natto-py
Version: 0.9.2
Summary: A Tasty Python Binding with MeCab(FFI-based, no SWIG or compiler necessary)
Home-page: https://github.com/buruzaemon/natto-py
Author: Brooke M. Fujita
Author-email: buruzaemon@gmail.com
License: BSD
Description: natto-py
        ========
        
        What is natto-py?
        -----------------
        A package leveraging FFI (foreign function interface), ``natto-py`` combines
        the Python_ programming language with MeCab_, the part-of-speech and
        morphological analyzer for the Japanese language. No compiler is necessary, as
        it is **not** a C extension. ``natto-py`` will run on Mac OS, Windows and
        \*nix.
        
        You can learn more about `natto-py at GitHub`_.
        
        |version| |pyversions| |license| |travis| |readthedocs|
        
        Requirements
        ------------
        ``natto-py`` requires the following:
        
        - An existing installation of `MeCab 0.996`_
        - A system dictionary, like `IPA`_, `Juman`_ or `Unidic`_
        - `cffi 0.8.6`_ or greater
        
        The following Python versions are supported:
        
        - `Python 2.7`_
        - `Python 3.2`_
        - `Python 3.3`_
        - `Python 3.4`_
        - `Python 3.5`_
        - `Python 3.6`_
        - `Python 3.7`_
        - `Python 3.8`_
        
        Installation
        ------------
        Install ``natto-py`` as you would any other Python package:
        
        .. code-block:: bash
        
            $ pip install natto-py
        
        This will automatically install the ``cffi`` package, which ``natto-py`` uses
        to bind to the ``mecab`` library.
        
        Automatic Configuration
        -----------------------
        As long as the ``mecab`` (and ``mecab-config`` for \*nix and Mac OS)
        executables are on your ``PATH``, ``natto-py`` does not require any explicit
        configuration.
        
        - On \*nix and Mac OS, it queries ``mecab-config`` to discover the path to the ``libmecab.so`` or ``libmecab.dylib``, respectively.
        - On Windows, it queries the Windows Registry to locate the MeCab installation folder.
        - In order to convert character encodings to/from Unicode, ``natto-py`` will examine the charset of the ``mecab`` system dictionary.
        
        Explicit configuration via MECAB_PATH and MECAB_CHARSET
        -------------------------------------------------------
        If ``natto-py`` for some reason cannot locate the ``mecab`` library,
        or if it cannot determine the correct charset used internally by
        ``mecab``, then you will need to set the ``MECAB_PATH`` and ``MECAB_CHARSET``
        environment variables.
        
        - Set the ``MECAB_PATH`` environment variable to the exact name/path to your ``mecab`` library.
        - Set the ``MECAB_CHARSET`` environment variable to the ``charset`` character encoding used by your system dictionary.
        
        e.g., for Mac OS:
        
        .. code-block:: bash
        
            export MECAB_PATH=/usr/local/Cellar/mecab/0.996/lib/libmecab.dylib
            export MECAB_CHARSET=utf8
        
        e.g., for bash on UNIX/Linux:
        
        .. code-block:: bash
        
            export MECAB_PATH=/usr/local/lib/libmecab.so
            export MECAB_CHARSET=euc-jp
        
        e.g., on Windows:
        
        .. code-block:: bat
        
            set MECAB_PATH=C:\Program Files\MeCab\bin\libmecab.dll
            set MECAB_CHARSET=shift-jis
        
        e.g., from within a Python program:
        
        .. code-block:: python
        
            import os
        
            os.environ['MECAB_PATH']='/usr/local/lib/libmecab.so'
            os.environ['MECAB_CHARSET']='utf-16'
        
        Usage
        -----
        Here's a very quick guide to using ``natto-py``.
        
        Instantiate a reference to the ``mecab`` library, and display some details:
        
        .. code-block:: python
        
            from natto import MeCab
        
            nm = MeCab()
            print(nm)
        
            # displays details about the MeCab instance
            <natto.mecab.MeCab
             model=<cdata 'mecab_model_t *' 0x801c16300>,
             tagger=<cdata 'mecab_t *' 0x801c17470>,
             lattice=<cdata 'mecab_lattice_t *' 0x801c196c0>,
             libpath="/usr/local/lib/libmecab.so",
             options={},
             dicts=[<natto.dictionary.DictionaryInfo
                     dictionary='mecab_dictionary_info_t *' 0x801c19540>,
                     filepath="/usr/local/lib/mecab/dic/ipadic/sys.dic",
                     charset=utf8,
                     type=0],
             version=0.996>
        
        ----
        
        Display details about the ``mecab`` system dictionary used:
        
        .. code-block:: python
        
            sysdic = nm.dicts[0]
            print(sysdic)
        
            # displays the MeCab system dictionary info
            <natto.dictionary.DictionaryInfo
             dictionary='mecab_dictionary_info_t *' 0x801c19540>,
             filepath="/usr/local/lib/mecab/dic/ipadic/sys.dic",
             charset=utf8,
             type=0>
        
        ----
        
        Parse Japanese text and send the MeCab result as a single string to
        ``stdout``:
        
        .. code-block:: python
        
            print(nm.parse('ピンチの時には必ずヒーローが現れる。'))
        
            # MeCab result as a single string
            ピンチ    名詞,一般,*,*,*,*,ピンチ,ピンチ,ピンチ
            の      助詞,連体化,*,*,*,*,の,ノ,ノ
            時      名詞,非自立,副詞可能,*,*,*,時,トキ,トキ
            に      助詞,格助詞,一般,*,*,*,に,ニ,ニ
            は      助詞,係助詞,*,*,*,*,は,ハ,ワ
            必ず    副詞,助詞類接続,*,*,*,*,必ず,カナラズ,カナラズ
            ヒーロー  名詞,一般,*,*,*,*,ヒーロー,ヒーロー,ヒーロー
            が      助詞,格助詞,一般,*,*,*,が,ガ,ガ
            現れる  動詞,自立,*,*,一段,基本形,現れる,アラワレル,アラワレル
            。      記号,句点,*,*,*,*,。,。,。
            EOS
        
        ----
        
        Next, try parsing the text with MeCab node parsing. A generator yielding the
        MeCabNode instances lets you efficiently iterate over the output without first
        materializing each and every resulting MeCabNode instance. The MeCabNode
        instances yielded allow access to more detailed information about each
        morpheme.
        
        Here we use a `Python with-statement`_ to automatically clean up after we
        finish node parsing with the MeCab tagger. This is the recommended approach
        for using ``natto-py`` in a production environment:
        
        .. code-block:: python
        
            # Use a Python with-statement to ensure mecab_destroy is invoked
            #
            with MeCab() as nm:
                for n in nm.parse('ピンチの時には必ずヒーローが現れる。', as_nodes=True):
            ...     # ignore any end-of-sentence nodes
            ...     if not n.is_eos():
            ...         print('{}\t{}'.format(n.surface, n.cost))
            ...
            ピンチ    3348
            の        3722
            時        5176
            に        5083
            は        5305
            必ず    7525
            ヒーロー   11363
            が       10508
            現れる   10841
            。        7127
        
        ----
        
        MeCab output formatting is extremely flexible and is highly recommended for
        any serious natural language processing task. Rather than parsing the MeCab
        output as a single, large string, use MeCab's ``--node-format`` option
        (short form ``-F``) to customize the node's ``feature`` attribute.
        
        - morpheme surface
        - part-of-speech
        - part-of-speech ID
        - pronunciation
        
        It is good practice when using ``--node-format`` to also specify node 
        formatting in the case where the morpheme cannot be found in the dictionary,
        by using ``--unk-format`` (short form ``-U``).
        
        This example formats the node ``feature`` to capture the items above as a
        comma-separated value:
        
        .. code-block:: python
        
            # MeCab options used:
            #
            # -F    ... short-form of --node-format
            # %m    ... morpheme surface
            # %f[0] ... part-of-speech
            # %h    ... part-of-speech id (ipadic)
            # %f[8] ... pronunciation
            # 
            # -U    ... short-form of --unk-format
            #           output ?,?,?,? for morphemes not in dictionary
            #
            with MeCab(r'-F%m,%f[0],%h,%f[8]\n -U?,?,?,?\n') as nm:
                for n in nm.parse('ピンチの時には必ずヒーローが現れる。', as_nodes=True):
            ...     # only normal nodes, ignore any end-of-sentence and unknown nodes
            ...     if n.is_nor():
            ...         print(n.feature)
            ...
            ピンチ,名詞,38,ピンチ
            の,助詞,24,ノ
            時,名詞,66,トキ
            に,助詞,13,ニ
            は,助詞,16,ワ
            必ず,副詞,35,カナラズ
            ヒーロー,名詞,38,ヒーロー
            が,助詞,13,ガ
            現れる,動詞,31,アラワレル
            。,記号,7,。
        
        
        ----
        
        `Partial parsing`_ (制約付き解析), allows you to pass hints to MeCab on
        how to tokenize morphemes when parsing. Most useful are boundary constraint
        parsing and feature constraint parsing.
        
        With boundary constraint parsing, you can specify either a compiled ``re``
        regular expression object or a string to tell MeCab where the boundaries of
        a morpheme should be. Use the ``boundary_constraints`` keyword. For hints on
        tokenization, please see `Regular expression operations`_ and `re.finditer`_
        in particular.
        
        This example uses the ``-F`` node-format option to customize the resulting
        ``MeCabNode`` feature attribute to extract:
        
        - ``%m`` - morpheme surface
        - ``%f[0]`` - node part-of-speech
        - ``%s`` - node ``stat`` status value, 1 is ``unknown``
        
        Note that any such morphemes captured will have node ``stat`` status of 1 (unknown):
        
        .. code-block:: python
        
            import re
        
            with MeCab(r'-F%m,\s%f[0],\s%s\n') as nm:
        
                text = '俺は努力したよっ？ お前の10倍、いや100倍1000倍したよっ！'
                
                # capture 10倍, 100倍 and 1000倍 as single parts-of-speech
                pattern = re.compile('10+倍') 
        
                for n in nm.parse(text, boundary_constraints=pattern, as_nodes=True):
            ...     print(n.feature)
            ...
            俺, 名詞, 0
            は, 助詞, 0
            努力, 名詞, 0
            し, 動詞, 0
            たよっ, 動詞, 0
            ？, 記号, 0
            お前, 名詞, 0
            の, 助詞, 0
            10倍, 名詞, 1
            、, 記号, 0
            いや, 接続詞, 0
            100倍, 名詞, 1
            1000倍, 名詞, 1
            し, 動詞, 0
            たよっ, 動詞, 0
            ！, 記号, 0
            EOS
        
        With feature constraint parsing, you can provide instructions to MeCab
        on what feature to use for a matching morpheme. Use the 
        ``feature_constraints`` keyword to pass in a ``tuple`` containing elements
        that themselves are ``tuple`` instances with a specific morpheme (str) 
        and a corresponding feature (str), in order of constraint precedence:
        
        .. code-block:: python
        
            with MeCab(r'-F%m,\s%f[0],\s%s\n') as nm:
        
                text = '心の中で3回唱え、 ヒーロー見参！ヒーロー見参！ヒーロー見参！'
                features = (('ヒーロー見参', '感動詞'),)
        
                for n in nm.parse(text, feature_constraints=features, as_nodes=True):
            ...     print(n.feature)
            ...
            心, 名詞, 0
            の, 助詞, 0
            中, 名詞, 0
            で, 助詞, 0
            3, 名詞, 1
            回, 名詞, 0
            唱え, 動詞, 0
            、, 記号, 0
            ヒーロー見参, 感動詞, 1
            ！, 記号, 0
            ヒーロー見参, 感動詞, 1
            ！, 記号, 0
            ヒーロー見参, 感動詞, 1
            ！, 記号, 0
            EOS
        
        
        ----
        
        Learn More
        ----------
        - Examples and more detailed information about ``natto-py`` can be found on the `project Wiki`_.
        - Working code in Jupyter notebook form can be found under this `project's notebooks directory`_.
        - `API documentation on Read the Docs`_.
        
        Contributing to natto-py
        ------------------------
        - Use git_ and `check out the latest code at GitHub`_ to make sure the
          feature hasn't been implemented or the bug hasn't been fixed yet.
        - `Browse the issue tracker`_ to make sure someone already hasn't requested it
          and/or contributed it.
        - Fork the project.
        - Start a feature/bugfix branch.
        - Commit and push until you are happy with your contribution.
        - Make sure to add tests for it. This is important so I don't break it in a
          future version unintentionally.
        - Please try not to mess with the ``setup.py``, ``CHANGELOG``, or version
          files. If you must have your own version, that is fine, but please isolate
          to its own commit so I can cherry-pick around it.
        - This project uses the following packages for development:
        
          - Sphinx_ for document generation
          - twine_ for secure uploads during release
          - unittest_ for unit tests, as it is very natural and easy-to-use
          - PyYAML_ for data loading during tests
        
        Changelog
        ---------
        Please see the ``CHANGELOG`` for the release history.
        
        Copyright
        ---------
        Copyright |copy| 2020, Brooke M. Fujita. All rights reserved. Please see
        the ``LICENSE`` file for further details.
        
        .. |version| image:: https://badge.fury.io/py/natto-py.svg
            :target: https://pypi.python.org/pypi/natto-py
        .. |pyversions| image:: https://img.shields.io/pypi/pyversions/natto-py.svg?style=flat
        .. |travis| image:: https://travis-ci.org/buruzaemon/natto-py.svg?branch=master
            :target: https://travis-ci.org/buruzaemon/natto-py
        .. |license| image:: https://img.shields.io/badge/license-BSD-blue.svg
            :target: _
        .. |readthedocs| image:: https://readthedocs.org/projects/natto-py/badge/?version=master
            :target: http://natto-py.readthedocs.org/en/master/?badge=master
            :alt: Documentation Status
        .. _Python: http://www.python.org/
        .. _MeCab: http://taku910.github.io/mecab/
        .. _IPA: http://taku910.github.io/mecab/#download
        .. _Juman: http://taku910.github.io/mecab/#download
        .. _Unidic: http://taku910.github.io/mecab/#download
        .. _natto-py at GitHub: https://github.com/buruzaemon/natto-py
        .. _MeCab 0.996: http://taku910.github.io/mecab/#download
        .. _cffi 0.8.6: https://bitbucket.org/cffi/cffi
        .. _Python 2.7: https://docs.python.org/2.7/whatsnew/2.7.html 
        .. _Python 3.2: https://docs.python.org/3.2/whatsnew/3.2.html
        .. _Python 3.3: https://docs.python.org/3.3/whatsnew/3.3.html 
        .. _Python 3.4: https://docs.python.org/3.4/whatsnew/3.4.html 
        .. _Python 3.5: https://docs.python.org/3.5/whatsnew/3.5.html 
        .. _Python 3.6: https://docs.python.org/3.6/whatsnew/3.6.html 
        .. _Python 3.7: https://docs.python.org/3.7/whatsnew/3.7.html 
        .. _Python 3.8: https://docs.python.org/3.8/whatsnew/3.8.html 
        .. _NLTK3's lead: https://github.com/nltk/nltk/wiki/Porting-your-code-to-NLTK-3.0
        .. _Python with-statement: https://www.python.org/dev/peps/pep-0343/
        .. _Partial parsing: http://taku910.github.io/mecab/partial.html
        .. _Regular expression operations: https://docs.python.org/3/library/re.html
        .. _re.finditer: https://docs.python.org/3/library/re.html#re.finditer
        .. _project Wiki: https://github.com/buruzaemon/natto-py/wiki 
        .. _project's notebooks directory: https://github.com/buruzaemon/natto-py/tree/master/notebooks
        .. _API documentation on Read the Docs: http://natto-py.readthedocs.org/en/master/
        .. _git: http://git-scm.com/downloads
        .. _check out the latest code at GitHub: https://github.com/buruzaemon/natto-py
        .. _Browse the issue tracker: https://github.com/buruzaemon/natto-py/issues
        .. _Sphinx: http://sphinx-doc.org/
        .. _twine: https://github.com/pypa/twine
        .. _unittest: http://pythontesting.net/framework/unittest/unittest-introduction/
        .. _PyYAML: https://github.com/yaml/pyyaml 
        .. |copy| unicode:: 0xA9 .. copyright sign
        
Keywords: MeCab 和布蕪 納豆 Japanese morphological analyzer NLP 形態素解析 自然言語処理 FFI binding バインディング
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Text Processing :: Linguistic
Classifier: Natural Language :: Japanese
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: POSIX :: BSD
Classifier: Operating System :: POSIX :: Linux
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: Microsoft :: Windows
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.2
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Description-Content-Type: text/x-rst
