Howtos

How to install CliMetLab?

pip install climetlab

See the installing instructions for more details.

How to access data?

There are two ways to access data using CliMetLab:

  • Using a Dataset: CliMetLab provides a few demo datasets. In order to access other datasets with cml.load_dataset(), the relevant plugin must be installed.

  • Using a data Source: A data Source allows loading various kinds of data format and location through cml.load_source(). Data sources should be used when there is no dataset plugin for the data you are interested in.

How to help others to use my data ?

Creating a CliMetLab plugin can be a solution to share some code along with the dataset that you are publishing/using. See the plugin documentation.

How to set up my cache directory ?

See Caching.

How to share my cache directory with another user ?

It is not recommended to share your cache with others. What you are looking for may be a mirror. This feature is not implemented yet.

Climetlab dask tools

Start an local cluster and client

from climetlab.utils.dask import start start(‘local’) # or $ climetlab dask start local # or $ climetlab dask local –start

Start an ssh cluster and client

from climetlab.utils.dask import start start(‘ssh’)

Start a SLURM dask cluster and client

from climetlab.utils.dask import start start(‘slurm’)

Start a slurm dask cluster on HPC

This is assumes that your HPC admin set up the hpc-name-config-1.yaml file on the appropriate location.

from climetlab.utils.dask import start start(‘hpc-name-config-1’)

Access the dask dashboard

Todo

todo

Access the dask logs

Todo

todo

Stop the dask cluster

The dask cluster and client will usually stop automatically when the python process ends. Nevertheless, it is possible to stop dask if it has been started from climetlab.

from climetlab.utils.dask import stop stop()

Advanced dask usages

Note: In this section a “dask deployement” refers to a client and a cluster. It does not refers to a Cloud deployement using Kubernetes, etc.

Create a custom dask deployement specifications

Create the yaml file $HOME/.climetlab/dask/hpc-name-config-1.yaml. Then use it with: from climetlab.utils.dask import start start(‘hpc-name-config-1’)

Note

For HPC system admin: Adding yaml files in /opt/climetlab/dask/*.yaml will give global access to all users.

Reuse the dask client

from climetlab.utils.dask import start client = start(‘local’).client

Scale the dask cluster

from climetlab.utils.dask import start deploy = start(‘slurm’) deploy.scale(..)