Utility script for dataset management.

Usage: kdataset <command>

Available Commands:

  • bash-completion: Generates bash completion scripts
  • delete: Delete specific catalog entity.
  • list: List catalog entities for the given workspace.
  • help: Help for any kdataset command.
  • pull: Download the data entity archive.
  • push: Push the data within the current directory.
  • version-delete: Delete specific version of the catalog entity.
  • version-list: List versions for the given catalog entity.


  • --config string Path to config file. (default ~/.kuberlab/config)
  • --debug Enable debug level (shortcut for --log-level=debug).
  • -h, --help help for kdataset
  • --insecure Enable insecure SSL/TLS connection (skip verify).
  • --log-level string Logging level. One of (debug, info, warning, error) (default "info")
  • --secret string Kibernetika AI workspace secret (auth method)
  • -t, --token string Kibernetika AI user token
  • --type entityType Choose entityType type for request: [dataset model] (default dataset)
  • --url string Base url to dataset storage.
  • --version version for kdataset
  • --workspace string Kibernetika AI workspace name (auth method)

kdataset commands#


Usage: kdataset delete <workspace> <entity-name>


kdataset delete my-workspace dataset-to-delete

Usage: kdataset list <workspace>

Example(listing models):

kdataset list my-workspace --type model

Usage: kdataset pull <workspace> <entity-name>:<version> [-O output-file.tar]


  • -O, --output string: Output filename.


kdataset pull my-workspace big-dataset:1.0.1

Note: The command above will create a file named my-workspace-big-dataset.1.0.1.tar


Usage: kdataset push <workspace> <entity-name>:<version> [flags]


  • --chunk-size int: Chunk-size for scanning (default 1024000 ~ 1MB).
  • -c, --concurrency int: Number of concurrent request to server (defaults to CPU cores num).
  • --create: Create entity in catalog if not exists.
  • --comment string: Comment for the new version
  • -f, --force: Force uploading regardless warnings.
  • --publish Newly created dataset will be public. Only used in conjunction with --create.

Example (creating and publishing some dataset):

kdataset push my-workspace big-dataset:1.0.1 --create --publish

Usage: kdataset version-delete <workspace> <entity-name>:<version>

Example (deleting model version):

kdataset --type model version-delete my-workspace tf-model:1.0.1

Usage: kdataset version-list <workspace> <entity-name>


kdataset version-list my-workspace big-dataset

More Examples:#

kdataset push test-projects cifar-10:1.0.0

kdataset push test-projects cifar-10:1.0.0 --create

kdataset version-list test-projects cifar-10

kdataset pull test-projects cifar-10:1.0.0


Download the version for your OS from the kdataset release page

Uncompress the downloaded tarball.

Copy the kdataset utility to the folder pointed to by “PATH” environment” variable

sudo cp kdataset /usr/local/bin

To connect from the kdataset utility to the Kibernetika application, you need a Kibernetika config file at ~/.kuberlab/config. If you do not have one, you need to create one.

The configuration values that need to be created are (basically, it is a simple file in YAML format):

base_url: https://cloud.kibernetika.io/api/v0.2 # url to access Kibernetika API.
token: xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx # your token, which can be obtained from the settings page of the Kibernetika application.

Please refer to kdataset README.md for more detailed configuration.

Note for MacOS: Due to the security requirements, to execute kdataset it is necessary to open executable file first from the file manager using Ctl-click and selecting Open in the dialog. MacOS will remember your choice and the application will work from the command line.

To verify the installation, at first use kdataset --version, to verify that you are executing the right version of utility

Then execute kdataset list kuberlab-demo

And you should see the list of all the demo data sets.