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        "author": "Teddy Crepineau",
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            "License :: OSI Approved :: MIT License",
            "Operating System :: MacOS",
            "Programming Language :: Python :: 3.6",
            "Topic :: Scientific/Engineering :: Artificial Intelligence"
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        "description": "Python library to Explore Emotions Behind Tweets\n================================================\n\ntwitter-sentiment is a Python library leveraging NLP algorithm and the Twitter API to classify the sentiment of a tweet.\n\nInstallation \n------------ \nInstalling twitter-sentiment is simple, you just have to use pip.\n::\n\n    pip install twitter-sentiment\n\n\nDocumentation\n-------------  \nDocumentation is available at [twitter-sentiment.readthedocs.io](https://twitter-sentiment.readthedocs.io/en/latest/index.html)\n\ntwitter-sentiment in a nutshel  \n------------------------------\ntwitter-sentiment let you classify a tweet/list of tweets as positive (1) or negative (0). twitter-sentiment then calculate and returns the ration of positive tweets. To classify a tweet, twitter-sentiment levereage TextBlob Naive Byaise NLP library. More information can be find at [textblob.readthedocs.io](https://textblob.readthedocs.io/en/dev/advanced_usage.html#sentiment-analyzers)\n\nContinuous Integration\n---------------------\ntwitter-sentiment uses circleci as a continuous integration tool. Pushing a new git tag to the remote repositiory will trigger circleci workflow and:\n* validate the test in /test/test_twitterSentiment.py\n* check for a match between the `VERSION` variable in the setup.py file and the git tag version. \nIf all tests pass, the build will be automatically upload to the pypi server\n\n\n",
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