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        "author": "pdevty",
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            "Intended Audience :: Financial and Insurance Industry",
            "License :: OSI Approved :: MIT License",
            "Programming Language :: Python :: 3.6"
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        "description": "googlefinance.client\n====================\n\ngooglefinance.client is a python client library for google finance api\n\nInstallation\n------------\n\n::\n\n    $ pip install googlefinance.client\n\nUsage\n-----\n\n.. code:: python\n\n    from googlefinance.client import get_price_data, get_prices_data, get_prices_time_data\n\n    # Dow Jones\n    param = {\n        'q': \".DJI\", # Stock symbol (ex: \"AAPL\")\n        'i': \"86400\", # Interval size in seconds (\"86400\" = 1 day intervals)\n        'x': \"INDEXDJX\", # Stock exchange symbol on which stock is traded (ex: \"NASD\")\n        'p': \"1Y\" # Period (Ex: \"1Y\" = 1 year)\n    }\n    # get price data (return pandas dataframe)\n    df = get_price_data(param)\n    print(df)\n    #                          Open      High       Low     Close     Volume\n    # 2016-05-17 05:00:00  17531.76   17755.8  17531.76  17710.71   88436105\n    # 2016-05-18 05:00:00  17701.46  17701.46  17469.92  17529.98  103253947\n    # 2016-05-19 05:00:00  17501.28  17636.22  17418.21  17526.62   79038923\n    # 2016-05-20 05:00:00  17514.16  17514.16  17331.07   17435.4   95531058\n    # 2016-05-21 05:00:00  17437.32  17571.75  17437.32  17500.94  111992332\n    # ...                       ...       ...       ...       ...        ...\n\n    params = [\n        # Dow Jones\n        {\n            'q': \".DJI\",\n            'x': \"INDEXDJX\",\n        },\n        # NYSE COMPOSITE (DJ)\n        {\n            'q': \"NYA\",\n            'x': \"INDEXNYSEGIS\",\n        },\n        # S&P 500\n        {\n            'q': \".INX\",\n            'x': \"INDEXSP\",\n        }\n    ]\n    period = \"1Y\"\n    # get open, high, low, close, volume data (return pandas dataframe)\n    df = get_prices_data(params, period)\n    print(df)\n    #            .DJI_Open  .DJI_High  .DJI_Low  .DJI_Close  .DJI_Volume  \\\n    # 2016-07-20   18503.12   18562.53  18495.11    18559.01    85840786   \n    # 2016-07-21   18582.70   18622.01  18555.65    18595.03    93233337   \n    # 2016-07-22   18589.96   18590.44  18469.67    18517.23    86803016   \n    # 2016-07-23   18524.15   18571.30  18491.59    18570.85    87706622   \n    # 2016-07-26   18554.49   18555.69  18452.62    18493.06    76807470   \n    # ...               ...        ...       ...         ...         ...   \n\n    params = [\n        # Dow Jones\n        {\n            'q': \".DJI\",\n            'x': \"INDEXDJX\",\n        },\n        # NYSE COMPOSITE (DJ)\n        {\n            'q': \"NYA\",\n            'x': \"INDEXNYSEGIS\",\n        },\n        # S&P 500\n        {\n            'q': \".INX\",\n            'x': \"INDEXSP\",\n        }\n    ]\n    period = \"1Y\"\n    interval = 60*30 # 30 minutes\n    # get open, high, low, close, volume time data (return pandas dataframe)\n    df = get_prices_time_data(params, period, interval)\n    print(df)\n    #                      .DJI_Open  .DJI_High  .DJI_Low  .DJI_Close  .DJI_Volume  \\\n    # 2016-07-19 23:00:00   18503.12   18542.13  18495.11    18522.47            0   \n    # 2016-07-19 23:30:00   18522.44   18553.30  18509.25    18546.27            0   \n    # 2016-07-20 00:00:00   18546.20   18549.59  18519.77    18539.93            0   \n    # 2016-07-20 00:30:00   18540.24   18549.80  18526.99    18534.18            0   \n    # 2016-07-20 01:00:00   18534.05   18540.38  18507.34    18516.41            0   \n    # ...                        ...        ...       ...         ...          ...   \n\nContributing\n------------\n\n1. Fork it\n2. Create your feature branch (``git checkout -b my-new-feature``)\n3. Commit your changes (``git commit -am 'Add some feature'``)\n4. Push to the branch (``git push origin my-new-feature``)\n5. Create new Pull Request\n",
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