Metadata-Version: 2.1
Name: pybo
Version: 0.2.18
Summary: Python utils for processing Tibetan
Home-page: https://github.com/Esukhia/pybo
Author: Esukhia development team
Author-email: esukhiadev@gmail.com
License: Apache2
Project-URL: Source, https://github.com/Esukhia/pybo
Project-URL: Tracker, https://github.com/Esukhia/pybo/issues
Description: <img src=https://raw.githubusercontent.com/mikkokotila/pybo/master/pybo_logo.png width=200>
        
        [![Build Status](https://travis-ci.org/Esukhia/pybo.svg?branch=master)](https://travis-ci.org/Esukhia/pybo)  [![Coverage Status](https://coveralls.io/repos/github/Esukhia/pybo/badge.svg?branch=master)](https://coveralls.io/github/Esukhia/pybo?branch=master)
        
        ## Overview
        
        pybo is a word tokenizer for the Tibetan language entirely written in Python. pybo takes in chuncks of text, and returns lists of words. It provides an easy-to-use, high-performance tokenization pipeline that can be adapted either as a stand-alone solution or compliment.
        
        ## Getting Started 
        
            pip install pybo
            
        Or if you for some reason want to install from the latest Master branch:
        
            pip install git+https://github.com/Esukhia/pybo.git
        
        ## Use 
        
        #### To initiate the tokenizer together with part-of-speech capability: 
        
            # initialize the tokenizer
            pybo = bo.BoTokenizer('POS')
            
            # read in some Tibetan text
            input_str = '༄༅། །རྒྱ་གར་སྐད་དུ། བོ་དྷི་སཏྭ་ཙརྻ་ཨ་བ་ཏ་ར། བོད་སྐད་དུ། བྱང་ཆུབ་སེམས་དཔའི་སྤྱོད་པ་ལ་འཇུག་པ། །སངས་རྒྱས་དང་བྱང་ཆུབ་སེམས་དཔའ་ཐམས་ཅད་ལ་ཕྱག་འཚལ་ལོ། །བདེ་གཤེགས་ཆོས་ཀྱི་སྐུ་མངའ་སྲས་བཅས་དང༌། །ཕྱག་འོས་ཀུན་ལའང་གུས་པར་ཕྱག་འཚལ་ཏེ། །བདེ་གཤེགས་སྲས་ཀྱི་སྡོམ་ལ་འཇུག་པ་ནི། །ལུང་བཞིན་མདོར་བསྡུས་ནས་ནི་བརྗོད་པར་བྱ། །'
            
            # run the tokenizer
            tokens = tok.tokenize(input_str)
            
        #### Now in 'tokens' you have an iterable where each token consist of several meta-data:
        
            # access the first token in the iterable
            tokens[0]
        
        This will yield:
        
            content: "༄༅། "
            char_types: |punct|punct|punct|space|
            type: punct
            start: 0
            len: 4
            syls: None
            tag: punct
            pos: punct
            skr: "False"
            freq: 0
            
        notes:
         - `start` is the starting index of the current token in the input string.
         - `syls` is a list of cleaned syllables, each syllable being represented as a list of indices.
        Each index leads to a constituting character within the input string. 
        
        #### In case you want to access all words in a list: 
        
            # iterate through the tokens object to get all the words in a list
            [t.content for t in tokens]
        
        #### Or just get all the nouns that were used in the text
        
            # extract nouns from the tokens
            [t.content for t in tokens if t.tag == 'NOUNᛃᛃᛃ']
            
        These examples highlight the basic principle of accessing attributes within each token object. 
        
        ## Acknowledgement
        
        **pybo** is an open source library for Tibetan NLP.
        
        We are always open to cooperation in introducing new features, tool integrations and testing solutions.
        
        Many thanks to companies and organizations who supported the development of pybo, especially:
        
        * [Khyentse Foundation](https://khyentsefoundation.org) for contributing USD22,000 to kickstart the project 
        * The [Barom/Esukhia canon project](http://www.barom.org) for sponsoring training data curation
        * [BDRC](https://tbrc.org) for contributing 2 staff for 6 months for data curation
        
        ## Maintainance
        
        Build the source dist:
        
        ```
        rm -rf dist/
        python3 setup.py clean sdist
        ```
        
        and upload on twine (versio >= `1.11.0`) with:
        
        ```
        twine upload dist/*
        ```
Keywords: nlp computational_linguistics search ngrams language_models linguistics toolkit tibetan
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Topic :: Text Processing :: Linguistic
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Natural Language :: Tibetan
Requires-Python: >=3.4
Description-Content-Type: text/markdown
