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Datalayer from CLI

Datalayer provides a Command Line Interface (CLI) allowing that support the platform features on Notebooks and Python files with Remote Kernels.

Check you have python>=3.9 and pip and install Datalayer with the following command in your terminal.

pip install datalayer
If you have already installed datalayer, upgrade with the following command.
pip install datalayer --upgrade

Once installed you can invoke the datalayer command.

datalayer

Datalayer - Version 1.0.0 - Connected as None on https://prod1.datalayer.run

[DatalayerCLI] One of `about` `benchmarks` `envs` `kernels` `login` `logout` `web` `who` `whoami` must be specified.

Ask details adding --help to any of the commands.

datalayer --help
The Datalayer CLI application.

Subcommands
===========
Subcommands are launched as `datalayer_core cmd [args]`. For information on
using subcommand 'cmd', do: `datalayer_core cmd -h`.

about
benchmarks
envs
kernels
login
logout
...
tip

You can use dla or even d as shortcut, instead of datalayer if you prefer.

The about command is available to explain you the features

datalayer about

Datalayer - Version 1.0.0 - Connected as None on https://prod1.datalayer.run

About                                                                                                       

Datalayer provides a command line tool allowing to list, 
create, terminate and open a console against a Remote Kernel.                                                                                             

Read more on https://datalayer.io

All command lines support an option --run-url to set the URL of the Datalayer RUN cluster providing the Datalayer services.

datalayer kernels list --run-url https://prod1.datalayer.run

Alternatively, you can set environment variables to avoid adding parameters to every command.

export DATALAYER_RUN_URL="https://prod1.datalayer.run"
export DATALAYER_TOKEN="MY_TOKEN"
export DATALAYER_EXTERNAL_TOKEN="MY_EXTERNAL_TOKEN"
datalayer whoami
datalayer envs list
datalayer kernels list

We also made it easy for you to get the values via a User Interface (on SaaS, JupyterLab...). Go to the action menu of the Kernel list and select the Copy terminal command line action. This will copy in your clipboard the command to run from CLI with the needed environment variables.