Getting started

To get started with the tutorials, pip install kfp v2:

pip install kfp

Here is a simple pipeline that prints a greeting:

from kfp import dsl

@dsl.component
def say_hello(name: str) -> str:
    hello_text = f'Hello, {name}!'
    print(hello_text)
    return hello_text

@dsl.pipeline
def hello_pipeline(recipient: str) -> str:
    hello_task = say_hello(name=recipient)
    return hello_task.output

You can [compile the pipeline][compile-a-pipeline] to YAML with the KFP SDK DSL [Compiler][compiler]:

from kfp import compiler

compiler.Compiler().compile(hello_pipeline, 'pipeline.yaml')

The [dsl.component][dsl-component] and [dsl.pipeline][dsl-pipeline] decorators turn your type-annotated Python functions into components and pipelines, respectively. The KFP SDK compiler compiles the domain-specific language (DSL) objects to a self-contained pipeline [YAML file][ir-yaml].

You can submit the YAML file to a KFP-conformant backend for execution. If you have already deployed a [KFP open source backend instance][installation] and obtained the endpoint for your deployment, you can submit the pipeline for execution using the KFP SDK [Client][client]. The following submits the pipeline for execution with the argument recipient='World':

from kfp.client import Client

client = Client(host='<MY-KFP-ENDPOINT>')
run = client.create_run_from_pipeline_package(
    'pipeline.yaml',
    arguments={
        'recipient': 'World',
    },
)

The client will print a link to view the pipeline execution graph and logs in the UI. In this case, the pipeline has one task that prints and returns 'Hello, World!'.

Next steps

• Learn more about Connecting the Pipelines SDK to Kubeflow Pipelines.