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.

• To use Python for working with NetCDF data.

• 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.

• K1.3.2.5.2-B PNetCDF