# SD1.2.5.1.1.5-B NetCDF Python API
# Background

Python is an interpreted, object-oriented language that is supported on a wide range of hardware and operating systems.
There are now several NetCDF interfaces for Python.

netcdf4-python is a Python interface to the NetCDF C library.
It is implemented on top of HDF5.
This module can read and write files in both the new NetCDF 4 and the old NetCDF 3 format and can create files that are readable by HDF5 clients.
xray is a higher-level interface that uses netcdf4-python internally to implement a pandas-like package for N-D labelled arrays for scientific data.

pycdf is a recent Python interface to the NetCDF library.
It provides almost complete coverage of the NetCDF C API, wrapping it inside easy to use python classes.
NetCDF arrays are handled using array objects provided either by the python numpy, Numeric or numarray packages.

PyNIO is a Python package that allows read and/or write access to a variety of data formats using an interface modelled on NetCDF.
Currently supported formats include NetCDF, HDF4, GRIB1 and GRIB2 (read-only), and HDF-EOS 2 Grid and Swath data (read-only).

PyPNetCDF is a Python interface to PNetCDF.
It allows access to NetCDF files using MPI and the library PNetCDF.
The tools can read and write in a parallel way.

Pupynere (PUre PYthon NEtcdf REader) allows read-access to NetCDF files using the same syntax as the Scientific.IO.NetCDF Python module.
Even though it's written in Python, the module is up to 40% faster than Scientific.IO.NetCDF and pynetcdf.

# Aim

  * To use Python for working with NetCDF data.

# Outcomes

  * Write a two-dimensional array of sample data and read data from this file.
  * Write some variables with units attributes and coordinate dimensions and read data variables and attributes from this file.
  * Write some four-dimensional variables using a record dimension and read from the variables from this file.

# Subskills
  * [[skill-tree:k:1:3:2:5:2:b]]