This section of the documentation gives an overview of the public facing functions used in the Jupyter notebooks available at the OpenGHG hub. For developers documentation of the internal workings of the library are available in the developer API section.
These modules are used to process observation data. Classes in this module should not be used directly as they
are used by functions in the
LocalClient modules when either uploading data to the OpenGHG cloud platform
or processing data for storage in a local object store.
Process surface observation data
Classes within the client module are used to interact with the cloud based OpenGHG system.
Classes within this module are used for running simulation jobs on high performace computing (HPC) clusters either locally or within the cloud based on a cluster as a service (CaaS) offering (see CitC).
For use with a local version of the object store. These functions make it easy to take advantage of the processing and export capabilities
of OpenGHG on your local filesystem. Use of this module results in the creation of a local object store in a location controlled by the
OPENGHG_PATH environment variable.
Many of the functions in this submodule are only for internal use and will be renamed.
Get a bucket (data container) for storing of data within the object store
This submodule contains functions that are widely used in the processing functions found in
Assign attributes to a dictionary of observation data in NetCDF format using
Write attributes to an in-memory NetCDF file to ensure it is CF-compliant
Create a file that contains the correct attributes for uploading to the CEDA archive
Recombine separate NetCDF files into a single file sorted by date
The function that is used by
openghg.localclient.Searchto search the object store
Assings data to exisiting Datasources or creates new Datasources