PyNIO ("pie-nee-oh") is a Python module that allows read and/or write
access to a variety of scientific data formats (NetCDF 3/4, GRIB1,
GRIB2, HDF4, HDF-EOS2, HDF-EOS5, shapefile, CCM History tape) using an
interface modelled on NetCDF.

Use of this software implies agreement of the PyNIO source code
license, which can be found in the "LICENSE" file.

You can import this package with:

  import Nio
For inline documentation:
  print Nio.__doc__

Since building from source can be challenging and time-consuming, we
recommend that you install this package using conda. Conda install packages
are currently available for 64-bit Linux and Macintosh OSX systems.
As a prerequisite, you will need to set up an anaconda or miniconda environment.
See https://www.continuum.io/downloads for anaconda or
http://conda.pydata.org/miniconda.html for miniconda. Miniconda is a lighter
weight version of anaconda. Both are easy to install -- anaconda just takes
longer.

Once your environment is up and runing, installing PyNIO is easy. All the necessary
dependencies are installed automatically. Currently there are two versions:
PyNIO 1.4.4 and PyNIO 1.5.0. PyNIO 1.4.4 uses a NetCDF3 type interface; it
supports NetCDF4-Classic file features such as compression, but it does not read or
write full NetCDF4 files. PyNIO 1.5.0 has still-evolving support for the full
NetCDF4 and HDF5 data models with access to groups, user-defined compound data
types and variable length arrays.
Install PyNIO 1.4.4 using:

  conda install -c ncar pynio

Install PyNIO 1.5.0 using:

  conda install -c conda-forge pynio

Currently, the PyNIO packages available on conda support NumPy 1.11.x through 1.13.x.
For now, it requires Python 2.7.x, but a Python 3+ version should be available soon.

For full documentation, see:

  http://www.pyngl.ucar.edu/Nio.shtml

Bug reports and feedback are appreciated (see email addresses below).

David Brown and Mary Haley
National Center for Atmospheric Research
1850 Table Mesa Drive
Boulder, CO  80305
USA
E-Mail: [email protected], [email protected]

Installing from source:
---------

Source code installation is not trivial. See the INSTALL file
in this directory.

Examples and tests:
---------

There are some PyNIO tests in the "test" directory and examples in the "examples"
directory.