Metadata-Version: 1.2
Name: python-datamuse
Version: 1.2.0
Summary: Python wrapper for the Datamuse API
Home-page: https://github.com/gmarmstrong/python-datamuse
Author: Guthrie McAfee Armstrong
Author-email: guthrie.armstrong@gmail.com
License: MIT
Description: [![Build Status](https://travis-ci.org/gmarmstrong/python-datamuse.svg?branch=master)](https://travis-ci.org/gmarmstrong/python-datamuse)
        
        # python-datamuse
        
        Python wrapper and scripts for the [Datamuse API](http://datamuse.com/api/).
        Available on PyPI at <https://pypi.python.org/pypi/python-datamuse>. You can
        install this library with `pip3 install python-datamuse`.
        
        ## Changelog
        
        ### Version 1.2.0
        
        - Raise Python version to 3.6
        - Mock the Datamuse API for tests
        - Restructure project files
        - Set README as PyPI long description
        
        ### Version 1.1.0
        
        - Changed to Python 3
        - Uploaded to PyPI, added instructions for PyPI installation
        - Changed README example to reflect PyPI packaging
        - Set up Travis CI
        - Temporarily removed pandas
        - Changed mode of scripts to executable
        
        ## Example
        
        ```python
        >>> from datamuse import datamuse
        >>> api = datamuse.Datamuse()
        >>> orange_rhymes = api.words(rel_rhy='orange', max=5)
        >>> orange_rhymes
        []
        >>> orange_near_rhymes = api.words(rel_nry='orange', max=5)
        >>> orange_near_rhymes
        [{'score': 973, 'word': 'storage'}, {'score': 858, 'word': 'knowledge'}, {'score': 615, 'word': 'homage'}, {'score': 560, 'word': 'warrant'}]
        >>>
        >>>
        >>> foo_complete = api.suggest(s='foo', max=10)
        >>> foo_complete
        [{u'score': 626, u'word': u'food'}, {u'score': 568, u'word': u'foot'}, {u'score': 520, u'word': u'fool'}, {u'score': 315, u'word': u'footage'}, {u'score': 297, u'word': u'foolish'}, {u'score': 279, u'word': u'football'}, {u'score': 272, u'word': u'footprint'}, {u'score': 232, u'word': u'footing'}, {u'score': 221, u'word': u'foof'}, {u'score': 185, u'word': u'foolproof'}]
        >>> from datamuse import scripts
        >>> foo_df = scripts.dm_to_df(foo_complete)
        >>> foo_df
           score       word
        0    626       food
        1    568       foot
        2    521       fool
        3    315    footage
        4    297    foolish
        5    279   football
        6    272  footprint
        7    232    footing
        8    221       foof
        9    185  foolproof
        
        [10 rows x 2 columns]
        ```
        
        Note that the default number of results is set to 100. You can set the default
        `max` to something else using the `set_max_default` method, e.g.
        `api.set_max_default(300)`. Datamuse only returns 1000 results max.
        
Keywords: datamuse,linguistics,language,wrapper
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.6
