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CLI Reference

All commands are available under kedro azureml. Run kedro azureml --help to list them.

kedro azureml init

kedro azureml init

Initializes the plugin in the current Kedro project. Creates:

  • conf/base/azureml.yml: configuration file with placeholder values
  • .amlignore: file exclusion list for code upload

No flags.

kedro azureml compile

kedro azureml compile -j JOB_NAME [options]

Compiles named job(s) into Azure ML pipeline YAML definitions without submitting them. See Compile and inspect for a walkthrough.

Flag Description
-j JOB_NAME Job name from jobs in azureml.yml. Required. Repeatable for multiple jobs.
-o OUTPUT Output YAML file path (default: pipeline.yaml)
--aml-env ENV Override the Azure ML environment for this invocation
--params JSON Runtime parameters as a JSON string (e.g. '{"key": "value"}')
--env-var KEY=VALUE Inject an environment variable into pipeline steps. Repeatable.
--load-versions KEY:VERSION Pin a dataset to a specific Kedro-versioned version. Repeatable.

kedro azureml run

kedro azureml run -j JOB_NAME [options]

Submits named job(s) to Azure ML managed compute immediately, ignoring any configured schedule.

Flag Description
-j JOB_NAME Job name from jobs in azureml.yml. Required. Repeatable for multiple jobs.
--dry-run Preview the pipeline definition without submitting to Azure ML
--wait-for-completion Block the terminal until the run finishes
-w WORKSPACE Override the workspace for all jobs in this batch
--aml-env ENV Override the Azure ML environment for this invocation
--params JSON Runtime parameters as a JSON string
--env-var KEY=VALUE Inject an environment variable into pipeline steps. Repeatable.
--load-versions KEY:VERSION Pin a dataset to a specific Kedro-versioned version. Repeatable.
--on-job-scheduled MODULE:FUNC Callback invoked after each job is submitted (e.g. mymodule:notify)

kedro azureml schedule

kedro azureml schedule -j JOB_NAME [options]

Creates or updates persistent Azure ML schedules for named job(s). Every selected job must have a schedule configured in azureml.yml.

Flag Description
-j JOB_NAME Job name from jobs in azureml.yml. Required. Repeatable for multiple jobs.
--dry-run Preview the schedule definition without creating it in Azure ML
-w WORKSPACE Override the workspace for all jobs in this batch
--aml-env ENV Override the Azure ML environment for this invocation
--params JSON Runtime parameters as a JSON string
--env-var KEY=VALUE Inject an environment variable into pipeline steps. Repeatable.
--load-versions KEY:VERSION Pin a dataset to a specific Kedro-versioned version. Repeatable.

kedro azureml execute

Used internally by Azure ML pipeline steps to run individual Kedro nodes on compute. Not intended for direct use. You may see this command in Azure ML step logs when inspecting pipeline run output in Azure ML Studio.

Common flags

The following flags are accepted by compile, run, and schedule:

Flag Description
--params JSON Runtime parameters as a JSON string
--env-var KEY=VALUE Inject environment variables into pipeline steps (repeatable)
--load-versions KEY:VERSION Dataset version overrides (repeatable)
--aml-env ENV Override the Azure ML environment