A Python reference implementation of the CF data model
The cfdm Python package is a reference implementation of the CF data model, that identifies the fundamental elements of the CF conventions and shows how they relate to each other, independently of the netCDF encoding.
The central element defined by the CF data model is the field construct, which corresponds to a CF-netCDF data variable with all of its metadata.
A simple example of reading a field construct from a file and inspecting it:
>>> import cfdm >>> f = cfdm.read('file.nc') >>> f [<Field: air_temperature(time(12), latitude(64), longitude(128)) K>] >>> print(f) 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 cfdm package can
- read field constructs from netCDF datasets,
- create new field constructs in memory,
- write field constructs to netCDF datasets on disk,
- read netCDF and CDL datasets containing hierarchical groups,
- inspect field constructs,
- test whether two field constructs are the same,
- modify field construct metadata and data,
- create subspaces of field constructs,
- incorporate, and create, metadata stored in external files,
- 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, and
- read, write, and create coordinates defined by geometry cells.
Command line utility
During installation the cfdump command line tool is also installed, which generates text descriptions of the field constructs contained in a netCDF dataset.
This project is hosted in a GitHub repository where you can access the most up-to-date source.
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