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        "author": "Mike Kittridge",
        "author_email": "mullenkamp1@gmail.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 3 - Alpha",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: Apache Software License",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Topic :: Software Development :: Build Tools"
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        "description": "nzmetservice - A Python package for handling  New Zealand MetService forecast data\r\n==================================================================================\r\n\r\nThe nzmetservice package contains various functions for downloading, processing, and handling of New Zealand MetService forecast data.\r\nThis package is not associated with the MetService.\r\n\r\n.. Documentation\r\n.. --------------\r\n.. The primary documentation for the package can be found `here <http://eto.readthedocs.io>`_.\r\n\r\nInstallation\r\n------------\r\nnzmetservice can be installed via pip or conda::\r\n\r\n  pip install nzmetservice\r\n\r\nor::\r\n\r\n  conda install -c mullenkamp nzmetservice\r\n\r\nThe core dependencies are `Pandas <http://pandas.pydata.org/pandas-docs/stable/>`_ and `xarray <http://xarray.pydata.org>`_.\r\n\r\nUsage\r\n-----\r\nftp_transfer\r\n~~~~~~~~~~~~\r\nThe ftp_transfer functions does as the name implies. It looks at the output_path on your local drive then compares it to the MetService ftp site and downloads what is on the ftp site that isn't in the output_path.\r\nIt can be loaded in from the basic module:\r\n\r\n.. code:: python\r\n\r\n  from nzmetservice import ftp_transfer\r\n\r\nAnd feed it with the necessary parameters:\r\n\r\n.. code:: python\r\n\r\n  ftp_transfer(ftp_path, username, password, output_path)\r\n\r\nYou will likely want to create a scheduled task to run a script containing this function once an hour.\r\n\r\nSelection and processing\r\n~~~~~~~~~~~~~~~~~~~~~~~~\r\nThe other two functions are simple selection and conversion tools.\r\n\r\n.. code:: python\r\n\r\n  import pandas as pd\r\n  from nzmetservice import select_bounds, to_df, datasets\r\n\r\n  pd.options.display.max_columns = 10\r\n\r\n  #####################################\r\n  ### Parameters\r\n\r\n  min_lat = -47\r\n  max_lat = -40\r\n  min_lon = 166\r\n  max_lon = 175\r\n  nc1_path = datasets.get_path('wrf_hourly_precip_nz8km_test')\r\n\r\n  ####################################\r\n  ### Examples\r\n\r\n  ms1 = select_bounds(nc1_path, min_lat, max_lat, min_lon, max_lon)\r\n\r\n  ms_df = to_df(ms1, to_rate=True)\r\n",
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        "name": "nzmetservice",
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