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Merge branch 'release/1.1.0' into production
* release/1.1.0: 1.1.0 bump kfp to v1.8.12 (trival) fix unittest about InputPath
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README.md

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# kfp-local
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Pipelines built with [kfp(kubeflow pipeline)](https://github.com/kubeflow/pipelines) execute in k8s cluster.
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During the development of kubeflow pipeline components, we usually upload the pipeline to kfp server and run it in k8s, if anything wrong we fix it locally and upload it again.
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During the development of kubeflow pipeline components, we usually upload the pipeline to kfp server and run it in k8s, if anything wrong we fix it locally and upload it again.
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It should be helpful for the development efficiency if the above process takes place in local host, that's what `kfp-local` cares.
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)
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if result.success:
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a_output_filepath = result.get_output_file(task_name="a-task", output="a_output_name")
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```
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## Additional configuration
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There are some options of `ExecutionMode`:
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* mode: Default execution mode, default 'docker'
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* images_to_exclude: If the image of op is in images_to_exclude, the op is
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executed in the mode different from default_mode.
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For more information about how to make use of kfp_local, please refer to unit test.
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## kfp compatibility
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kfp-local is tested with kfp=1.8.9 for now.
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kfp-local is tested with kfp>=1.8.9,<2.0 for now.
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Supports:
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* Control flow: Condition, ParallelFor, ExitHandler
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Don't support for now:
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* Importer
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* Artifact iterator
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* Caching
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* Caching

kfp_local/_local_client.py

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pipeline_root: The root directory where the output artifact of component
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will be saved.
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"""
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warnings.warn(
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"LocalClient is an Alpha[1] feature. It may be deprecated in the future.\n"
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"[1] https://github.com/kubeflow/pipelines/blob/master/docs/release/feature-stages.md#alpha", # noqa: E501
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category=FutureWarning,
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)
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_pipeline_root = pipeline_root or tempfile.tempdir
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kfp_local/_version.py

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__version__ = "1.0.1"
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__version__ = "1.1.0"

kfp_local/local_client_test.py

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@dsl.component
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def component_with_inputpath(src: dsl.InputPath(str)) -> str:
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def component_with_inputpath(src: dsl.InputPath()) -> str:
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with open(src, "r") as f:
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return f.read()
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requirements.in

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kfp==1.8.9
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kfp>=1.8.12,<2.0

requirements.txt

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#
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# pip-compile
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#
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absl-py==0.11.0
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absl-py==1.0.0
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# via kfp
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attrs==21.4.0
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# via jsonschema
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# via kfp
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fire==0.4.0
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# via kfp
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google-api-core==2.7.1
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google-api-core==2.7.2
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# via
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# google-api-python-client
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# google-cloud-core
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# google-cloud-storage
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# kfp
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google-api-python-client==1.12.11
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# via kfp
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google-auth==1.35.0
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# kubernetes
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google-auth-httplib2==0.1.0
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# via google-api-python-client
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google-cloud-core==2.2.3
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google-cloud-core==2.3.0
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# via google-cloud-storage
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google-cloud-storage==1.44.0
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# via kfp
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# jsonschema
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jsonschema==3.2.0
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# via kfp
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kfp==1.8.9
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kfp==1.8.12
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# via -r requirements.in
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kfp-pipeline-spec==0.1.14
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# via kfp
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# via
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# google-api-core
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# google-cloud-storage
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# googleapis-common-protos
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# kfp
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# kfp-pipeline-spec
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pyasn1==0.4.8
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# via google-auth
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pydantic==1.9.0
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# via kfp
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pyparsing==3.0.7
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pyparsing==3.0.8
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# via httplib2
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pyrsistent==0.18.1
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# via jsonschema

setup.py

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def _load_requires(
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requirements="requirements.txt",
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requirements="requirements.in",
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) -> List[str]:
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requirements_path = os.path.join(ROOT_PATH, requirements)
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with open(requirements_path) as f:

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