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import codecs
import os
from setuptools import setup, find_packages
HERE = os.path.abspath(os.path.dirname(__file__))
def read(*parts):
"""
Build an absolute path from *parts* and and return the contents of the
resulting file. Assume UTF-8 encoding.
"""
with codecs.open(os.path.join(HERE, *parts), "rb", "utf-8") as f:
return f.read()
setup(
name = 'vaderSentiment',
#packages = ['vaderSentiment'], # this must be the same as the name above
packages = find_packages(exclude=['tests*']), # a better way to do it than the line above -- this way no typo/transpo errors
include_package_data=True,
version = '3.2.1',
description = 'VADER Sentiment Analysis. VADER (Valence Aware Dictionary and sEntiment Reasoner) is a lexicon and rule-based sentiment analysis tool that is specifically attuned to sentiments expressed in social media, and works well on texts from other domains.',
long_description = read("README.rst"),
long_description_content_type = 'text/markdown',
author = 'C.J. Hutto',
author_email = 'cjhutto@gatech.edu',
license = 'MIT License: http://opensource.org/licenses/MIT',
url = 'https://github.com/cjhutto/vaderSentiment', # use the URL to the github repo
download_url = 'https://github.com/cjhutto/vaderSentiment/archive/master.zip',
keywords = ['vader', 'sentiment', 'analysis', 'opinion', 'mining', 'nlp', 'text', 'data',
'text analysis', 'opinion analysis', 'sentiment analysis', 'text mining', 'twitter sentiment',
'opinion mining', 'social media', 'twitter', 'social', 'media'], # arbitrary keywords
classifiers = ['Development Status :: 4 - Beta', 'Intended Audience :: Science/Research',
'License :: OSI Approved :: MIT License', 'Natural Language :: English',
'Programming Language :: Python :: 3.5', 'Topic :: Scientific/Engineering :: Artificial Intelligence',
'Topic :: Scientific/Engineering :: Information Analysis', 'Topic :: Text Processing :: Linguistic',
'Topic :: Text Processing :: General'],
)
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