Metadata-Version: 2.1
Name: myanmartools
Version: 1.2.0
Summary: Tools for processing font encodings used in Myanmar
Home-page: https://github.com/google/myanmar-tools
Author: William (Wai Yan) Zhu
Author-email: williamzhu345@gmail.com
License: Apache License, Version 2.0
Description: Myanmar Tools Python Documentation
        ==================================
        
        This documentation is python specific usage of Myanmar Tools.
        For general documentation, see `the top-level README`_.
        
        Installation
        ------------
        
        From PyPI
        *********
        
        ``$ pip install myanmartools``
        
        From GitHub
        ***********
        
        ``$ pip install 'git+https://github.com/google/myanmar-tools@master#egg=myanmartools&subdirectory=clients/python'``
        
        Usage Examples
        --------------
        
        To detect Zawgyi, create an instance of ZawgyiDetector,
        and call ``get_zawgyi_probability`` with a string::
        
            from myanmartools import ZawgyiDetector
        
            detector = ZawgyiDetector()
            score = detector.get_zawgyi_probability('မ္း')
            # score is now 0.999772 (very likely Zawgyi)
        
        
        For Zawgyi-to-Unicode conversion, you can use the ICU library. Install it
        using ``pip install PyICU``.
        
        To convert Zawgyi to Unicode, create an instance of ICU Transliterator with
        the transform ID "Zawgyi-my", and call ``transiliterate`` with a string::
        
            from icu import Transliterator
        
            converter = Transliterator.createInstance('Zawgyi-my')
            output = converter.transliterate('မ္း')
            # output is now 'မ်း'
        
        .. _`the top-level README`: https://github.com/google/myanmar-tools/blob/master/README.md
        
Keywords: burmese,encoding,myanmar,nlp,unicode,zawgyi
Platform: any
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Topic :: Text Processing
Requires-Python: >=3.7
Description-Content-Type: text/x-rst
