Metadata-Version: 1.1
Name: chirptext
Version: 0.1a15
Summary: ChirpText is a collection of text processing tools for Python.
Home-page: https://github.com/letuananh/chirptext
Author: Le Tuan Anh
Author-email: tuananh.ke@gmail.com
License: MIT License
Description: ChirpText is a collection of text processing tools for Python. It is not
        meant to be a powerful tank like the popular NTLK but a small package
        which you can pip-install anywhere and write a few lines of code to
        process textual data.
        
        Main features
        =============
        
        -  **[New]** Does not require ``mecab-python3`` package to use
           MeCab/Deko on Windows. Only binary release (``mecab.exe``) is
           required.
        -  Text annotation framework (TTL, a.k.a TextTagLib format) which can
           import/export JSON or human-readable text files
        -  Helper functions and useful data for processing English, Japanese,
           Chinese and Vietnamese.
        -  Quick text-based report generation
        -  Application configuration files management which can make educated
           guess about config files' whereabouts
        -  Web fetcher with responsible web crawling ethics (support caching out
           of the box)
        -  CSV helper functions
        -  Console application template
        
        Project homepage: https://github.com/letuananh/chirptext
        
        Installation
        ============
        
        .. code:: bash
        
            pip install chirptext
            # pip script sometimes doesn't work properly, so you may want to try this instead
            python3 -m pip install chirptext
        
        **Note**: chirptext library does not support Python 2 anymore. Please
        update to Python 3 to use this package.
        
        Sample codes
        ============
        
        Using MeCab on Windows
        ----------------------
        
        You can download mecab binary package from
        http://taku910.github.io/mecab/#download and install it. After installed
        you can try:
        
        .. code:: python
        
            >>> from chirptext import deko
            >>> sent = deko.parse('猫が好きです。')
            >>> sent.tokens
            [[猫(名詞-一般/*/*|猫|ネコ|ネコ)], [が(助詞-格助詞/一般/*|が|ガ|ガ)], [好き(名詞-形容動詞語幹/*/*|好き|スキ|スキ)], [です(助動詞-*/*/*|です|デス|デス)], [。(記号-句点/*/*|。|。|。)], [EOS(-//|||)]]
            >>> sent.words
            ['猫', 'が', '好き', 'です', '。']
            >>> sent[0].pos
            '名詞'
            >>> sent[0].root
            '猫'
            >>> sent[0].reading
            'ネコ'
        
        If you installed MeCab to a custom location, for example
        ``C:\mecab\bin\mecab.exe``, try
        
        .. code:: python
        
            >>> deko.set_mecab_bin("C:\\mecab\\bin\\mecab.exe")
            >>> deko.get_mecab_bin()
            'C:\\mecab\\bin\\mecab.exe'
        
            # Just that & now you can use mecab
            >>> deko.parse('雨が降る。').words
            ['雨', 'が', '降る', '。']
        
        Web fetcher
        -----------
        
        .. code:: python
        
            from chirptext import WebHelper
        
            web = WebHelper('~/tmp/webcache.db')
            data = web.fetch('https://letuananh.github.io/test/data.json')
            data
            >>> b'{ "name": "Kungfu Panda" }\n'
            data_json = web.fetch_json('https://letuananh.github.io/test/data.json')
            data_json
            >>> {'name': 'Kungfu Panda'}
        
        Using Counter
        -------------
        
        .. code:: python
        
            from chirptext import Counter, TextReport
            from chirptext.leutile import LOREM_IPSUM
        
            ct = Counter()
            vc = Counter()  # vowel counter
            for char in LOREM_IPSUM:
                if char == ' ':
                    continue
                ct.count(char)
                vc.count("Letters")
                if char in 'auieo':
                    vc.count("Vowels")
                else:
                    vc.count("Consonants")
            vc.summarise()
            ct.summarise(byfreq=True, limit=5)
        
        Output
        ~~~~~~
        
        ::
        
            Letters: 377 
            Consonants: 212 
            Vowels: 165 
            i: 42 
            e: 37 
            t: 32 
            o: 29 
            a: 29 
        
        Sample TextReport
        -----------------
        
        .. code:: python
        
            # a string report
            rp = TextReport()  # by default, TextReport will write to standard output, i.e. terminal
            rp = TextReport(TextReport.STDOUT)  # same as above
            rp = TextReport('~/tmp/my-report.txt')  # output to a file
            rp = TextReport.null()  # ouptut to /dev/null, i.e. nowhere
            rp = TextReport.string()  # output to a string. Call rp.content() to get the string
            rp = TextReport(TextReport.STRINGIO)  # same as above
        
            # TextReport will close the output stream automatically by using the with statement
            with TextReport.string() as rp:
                rp.header("Lorem Ipsum Analysis", level="h0")
                rp.header("Raw", level="h1")
                rp.print(LOREM_IPSUM)
                rp.header("Top 5 most common letters")
                ct.summarise(report=rp, limit=5)
                print(rp.content())
        
        Output
        ~~~~~~
        
        ::
        
            +---------------------------------------------------------------------------------- 
            | Lorem Ipsum Analysis 
            +---------------------------------------------------------------------------------- 
             
            Raw 
            ------------------------------------------------------------ 
            Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum. 
             
            Top 5 most common letters
            ------------------------------------------------------------ 
            i: 42 
            e: 37 
            t: 32 
            o: 29 
            a: 29 
        
Keywords: nlp
Platform: any
Classifier: Programming Language :: Python
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Natural Language :: English
Classifier: Environment :: Plugins
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Topic :: Text Processing
Classifier: Topic :: Software Development :: Libraries :: Python Modules
