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**Introduction**
================

----

Version |release| for version |version| of the CF conventions.

The Python `cf` package is an Earth Science data analysis library that
is built on a complete implementation of the :ref:`CF-data-model`.



**Functionality**
-----------------
----

.. important:: **This version of cf is for Python 3 only** and there are
          :ref:`incompatible differences between versions 2.x and 3.x
          <two-to-three-changes>` of `cf`.

	  Scripts written for version 2.x but running under version
          3.x should either work as expected, or provide informative
          error messages on the new API usage. However, it is advised
          that the outputs of older scripts are checked when running
          with Python 3 versions of the `cf` library.

	  For version 2.x documentation, see the :ref:`older releases
	  <Older-releases>` page.

The `cf` package implements the :ref:`CF-data-model` [#cfdm]_ for its
internal data structures and so is able to process any CF-compliant
dataset. It is not strict about CF-compliance, however, so that
partially conformant datasets may be ingested from existing datasets
and written to new datasets.This is so that datasets that are
partially conformant may nonetheless be modified in memory.

.. code-block:: python
   :caption: *A simple example of reading a field construct from a
             file and inspecting it.*

   >>> import cf
   >>> f = cf.read('file.nc')
   >>> f
   [<CF Field: air_temperature(time(12), latitude(64), longitude(128)) K>]
   >>> print(f[0])
   Field: air_temperature (ncvar%tas)
   ----------------------------------
   Data            : air_temperature(time(12), latitude(64), longitude(128)) K
   Cell methods    : time(12): mean (interval: 1.0 month)
   Dimension coords: time(12) = [0450-11-16 00:00:00, ..., 0451-10-16 12:00:00] noleap
                   : latitude(64) = [-87.8638, ..., 87.8638] degrees_north
                   : longitude(128) = [0.0, ..., 357.1875] degrees_east
                   : height(1) = [2.0] m

The `cf` package can:

* read field constructs from netCDF, CDL, PP and UM datasets,

* create new field constructs in memory,

* inspect field constructs,

* test whether two field constructs are the same,

* modify field construct metadata and data,

* create subspaces of field constructs,

* write field constructs to netCDF datasets on disk,

* incorporate, and create, metadata stored in external files (*new in
  version 3.0.0*),

* read, write, and create data that have been compressed by convention
  (i.e. ragged or gathered arrays), whilst presenting a view of the
  data in its uncompressed form,

* read, write, and create coordinates defined by geometry cells (*new
  in version 3.2.0*),

* combine field constructs arithmetically,

* manipulate field construct data by arithmetical and trigonometrical
  operations,

* perform statistical collapses on field constructs,

* perform histogram, percentile and binning operations on field
  constructs (*new in version 3.0.3*),
  
* regrid field constructs with (multi-)linear, nearest neighbour,
  first- and second-order conservative and higher order patch recovery
  methods,

* apply convolution filters to field constructs,

* create moving means from field constructs (**new in version
  3.3.0**),

* calculate derivatives of field constructs,

* create field constructs to create derived quantities (such as
  vorticity).

All of the above use LAMA functionality, which allows multiple
fields larger than the available memory to exist and be manipulated.


Hierarchical groups
^^^^^^^^^^^^^^^^^^^

Hierarchical groups provide a powerful mechanism to structure
variables within datasets. A future release of `cf` will include support
for netCDF4 files containing data organised in hierarchical groups,
but this is not available in version |release| (even though it is
allowed in CF-1.8).


**Visualization**
-----------------

----

Powerful, flexible, and very simple to produce visualizations of field
constructs are available with the `cfplot` package, that is installed
separately to `cf` (see http://ajheaps.github.io/cf-plot for details).

See the `cfplot gallery
<http://ajheaps.github.io/cf-plot/gallery.html>`_ for the wide range
range plotting possibilities with example code.

.. figure:: images/cfplot_example.png

   *Example output of `cfplot` displaying a `cf` field construct.*

----
   
.. [#cfdm] Hassell, D., Gregory, J., Blower, J., Lawrence, B. N., and
           Taylor, K. E.: A data model of the Climate and Forecast
           metadata conventions (CF-1.6) with a software
           implementation (cf-python v2.1), Geosci. Model Dev., 10,
           4619-4646, https://doi.org/10.5194/gmd-10-4619-2017, 2017.