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        "author": "Thomas Levine",
        "author_email": "Thomas Levine",
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        "classifiers": [
            "Intended Audience :: Developers",
            "License :: OSI Approved :: MIT License",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: SQL",
            "Topic :: Database :: Front-Ends"
        ],
        "description": "pytreasuryio\n======\nAccess .. _treasury.io: http://treasury.io from Python.\n\nThis is a package consisting of a single, simple function for submitting ``SQL`` queries to .. _treasury.io: http://treasury.io from ``python``. While you could simply copy-and-paste the function from script-to-script, this makes it quicker and easier to get up and running!\n\nIt also has some helpers to make a Twitter bot from the treasury.io data.\n\nInstallation\n--------\nInstall with pip.::\n\n    pip install treasuryio\n\nExample\n---------\n\nBasic query\n~~~~~~~~~\nSend an SQL query and receive a pandas data frame.::\n\n    # Operating cash balances for May 22, 2013\n    import treasuryio\n    sql = 'SELECT * FROM \"t1\" WHERE \"date\" = \\'2013-05-22\\';'\n    treasuryio.query(sql)\n\nTwitter bot\n~~~~~~~~~\nWrite a ``~/.twitter.yml`` file.::\n\n    consumer_key: oeshaoduhsaousaoeuhts\n    consumer_secret: b233tsao-enuhsaoehsunoesudtuhoelaouhs2uo\n    access_token: 2349081293-astoehusatoehusaoeustahoeuhh2AOEUTAouhc\n    access_token_secret: 9023uonshesuaHONETuoeuoeouo0eOHNEuhOuoeu\n\nDefine a function that produces the text of the tweet, and decorate it with the\n``@treasurio.tweet`` decorator.::\n\n    import treasuryio\n    import humanize\n    import math\n\n    MIL = 1e6\n\n    # Helpers to humanize numbers / dates\n    def human_number(num):\n        return humanize.intword(int(math.ceil(num))).lower()\n\n    def human_date(date):\n        return humanize.naturalday(date).title()\n\n    @treasuryio.tweet\n    def total_debt_tweet():\n        df = treasuryio.query('SELECT date, close_today FROM t3c WHERE (item LIKE \\'%subject to limit%\\' AND year = 2013 AND month >=1) ORDER BY date DESC')\n\n        # determine length of DataFrame\n        end = len(df)-1\n\n        # extract current amount and amount at the beginning of the year\n        current_amt = df['close_today'][0]*MIL\n        previous_amt = df['close_today'][end]*MIL\n\n        # calculate change\n        delta = abs(current_amt - previous_amt)\n\n        # generate word to represnet the direction of change\n        if current_amt > previous_amt:\n            change = \"increased\"\n        elif current_amt < previous_amt:\n            change = \"decreased\"\n\n        # humanize values\n        # Notice the included ``human_date`` and ``human_number`` functions which simplify these values for you\n        current_date = human_date(df['date'][0])\n        amt = human_number(current_amt)\n        delta = human_number(delta)\n        previous_date = human_date(df['date'][end])\n\n        # generate tweet\n        vals = (current_date, amt, change, previous_date, 'http://treasury.io')\n        return \"As of %s, the US Gov is $%s in debt. This amount has %s since %s - %s\" % vals\n\nThen just run it.::\n\n    total_debt_tweet()\n\nYou can get fancy by switching the functions that you use.::\n\n    import treasuryio\n    import random\n\n    @treasurio.tweet\n    def tweet_a():\n        # ...\n\n    @treasurio.tweet\n    def tweet_b():\n        # ...\n\n    @treasurio.tweet\n    def tweet_c():\n        # ...\n\n    random.choice([tweet_a, tweet_b, tweet_c])()",
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        "license": "MIT",
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        "name": "treasuryio",
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