Interact with KFP via the CLI

This section provides a summary of the available commands in the KFP CLI. For more comprehensive documentation about all the available commands in the KFP CLI, see Command Line Interface in the KFP SDK reference documentation.

Installation

The KFP CLI is installed when you install the KFP SDK: pip install kfp.

Check availability of KFP CLI

To check whether KFP CLI is installed in your environment, run the following command:

kfp --version

General syntax

All commands in the KFP CLI use the following general syntax:

kfp [OPTIONS] COMMAND [ARGS]...

For example, to list all runs for a specific endpoint, run the following command:

kfp --endpoint http://my_kfp_endpoint.com run list

Get help for a command

To get help for a specific command, use the argument --help directly in the command line. For example, to view guidance about the kfp run command, type the following command:

kfp run --help

Main functons of the KFP CLI

You can use the KFP CLI to do the following:

• Installation
  • Check availability of KFP CLI
  • General syntax
  • Get help for a command
• Main functons of the KFP CLI
  • Interact with KFP resources
  • Compile pipelines
  • Build containerized Python components
    • Before you begin
    • Build the component

Interact with KFP resources

The majority of the KFP CLI commands let you create, read, update, or delete KFP resources from the KFP backend. All of these commands use the following general syntax:

kfp <resource_name> <action>

The <resource_name> argument can be one of the following:

• run
• recurring-run
• pipeline
• experiment

For all values of the <resource_name> argument, the <action> argument can be one of the following:

• create
• list
• get
• delete

Some resource names have additional resource-specific actions. The following table lists a few examples of resource-specific actions:

Compile pipelines

You can use the kfp dsl compile command to compile pipelines or components defined in a Python file to IR YAML.

• To compile a pipeline definition defined in a Python file, run the following command.

  kfp dsl compile --py [PATH_TO_INPUT_PYTHON] --output [PATH_TO_OUTPUT_YAML] --function [PIPELINE_NAME]
  

  For example:

  kfp dsl compile --py path/to/pipeline.py --output path/to/output.yaml
  

  To compile a single pipeline or component from a Python file containing multiple pipeline or component definitions, use the --function argument.

  For example:

  kfp dsl compile --py path/to/pipeline.py --output path/to/output.yaml --function my_pipeline
  

  kfp dsl compile --py path/to/pipeline.py --output path/to/output.yaml --function my_component
  

• To specify pipeline parameters, use the --pipeline-parameters argument and provide the parameters as JSON.

  kfp dsl compile [PATH_TO_INPUT_PYTHON] --output [PATH_TO_OUTPUT_YAML] --pipeline-parameters [PIPELINE_PARAMETERS_JSON]
  

  For example:

  kfp dsl compile --py path/to/pipeline.py --output path/to/output.yaml --pipeline-parameters '{"param1": 2.0, "param2": "my_val"}'
  

Build containerized Python components

You can author Containerized Python Components in the KFP SDK. This lets you use handle more source code with better code organization than the simpler Lightweight Python Component authoring experience.

Before you begin

Run the following command to install the KFP SDK with the additional Docker dependency:

pip install kfp[all]

Build the component

To build a containerized Python component, use the following convenience command in the KFP CLI. Using this command, you can build an image with all the source code found in COMPONENTS_DIRECTORY. The command uses the component found in the directory as the component runtime entrypoint.

kfp component build [OPTIONS] [COMPONENTS_DIRECTORY] [ARGS]...

For example:

kfp component build src/ --component-filepattern my_component --push-image

For more information about the arguments and flags supported by the kfp component build command, see build in the KFP SDK API reference. For more information about creating containerized Python components, see Authoring Python Containerized Components.