# PIPELINE DEFINITION
# Name: preprocess
# Description: Dummy preprocessing step.
# Inputs:
#    input_dict_parameter: dict
#    input_list_parameter: list
#    message: str
# Outputs:
#    output_bool_parameter_path: bool
#    output_dataset_one: system.Dataset
#    output_dataset_two_path: system.Dataset
#    output_dict_parameter_path: dict
#    output_list_parameter_path: list
#    output_parameter_path: str
components:
  comp-preprocess:
    executorLabel: exec-preprocess
    inputDefinitions:
      parameters:
        input_dict_parameter:
          parameterType: STRUCT
        input_list_parameter:
          parameterType: LIST
        message:
          parameterType: STRING
    outputDefinitions:
      artifacts:
        output_dataset_one:
          artifactType:
            schemaTitle: system.Dataset
            schemaVersion: 0.0.1
        output_dataset_two_path:
          artifactType:
            schemaTitle: system.Dataset
            schemaVersion: 0.0.1
      parameters:
        output_bool_parameter_path:
          parameterType: BOOLEAN
        output_dict_parameter_path:
          parameterType: STRUCT
        output_list_parameter_path:
          parameterType: LIST
        output_parameter_path:
          parameterType: STRING
deploymentSpec:
  executors:
    exec-preprocess:
      container:
        args:
        - --executor_input
        - '{{$}}'
        - --function_to_execute
        - preprocess
        command:
        - sh
        - -c
        - "\nif ! [ -x \"$(command -v pip)\" ]; then\n    python3 -m ensurepip ||\
          \ python3 -m ensurepip --user || apt-get install python3-pip\nfi\n\nPIP_DISABLE_PIP_VERSION_CHECK=1\
          \ python3 -m pip install --quiet --no-warn-script-location 'kfp==2.1.3'\
          \ '--no-deps' 'typing-extensions>=3.7.4,<5; python_version<\"3.9\"' && \"\
          $0\" \"$@\"\n"
        - sh
        - -ec
        - 'program_path=$(mktemp -d)


          printf "%s" "$0" > "$program_path/ephemeral_component.py"

          _KFP_RUNTIME=true python3 -m kfp.dsl.executor_main                         --component_module_path                         "$program_path/ephemeral_component.py"                         "$@"

          '
        - "\nimport kfp\nfrom kfp import dsl\nfrom kfp.dsl import *\nfrom typing import\
          \ *\n\ndef preprocess(\n    # An input parameter of type string.\n    message:\
          \ str,\n    # An input parameter of type dict.\n    input_dict_parameter:\
          \ Dict[str, int],\n    # An input parameter of type list.\n    input_list_parameter:\
          \ List[str],\n    # Use Output[T] to get a metadata-rich handle to the output\
          \ artifact\n    # of type `Dataset`.\n    output_dataset_one: Output[Dataset],\n\
          \    # A locally accessible filepath for another output artifact of type\n\
          \    # `Dataset`.\n    output_dataset_two_path: OutputPath('Dataset'),\n\
          \    # A locally accessible filepath for an output parameter of type string.\n\
          \    output_parameter_path: OutputPath(str),\n    # A locally accessible\
          \ filepath for an output parameter of type bool.\n    output_bool_parameter_path:\
          \ OutputPath(bool),\n    # A locally accessible filepath for an output parameter\
          \ of type dict.\n    output_dict_parameter_path: OutputPath(Dict[str, int]),\n\
          \    # A locally accessible filepath for an output parameter of type list.\n\
          \    output_list_parameter_path: OutputPath(List[str]),\n):\n    \"\"\"\
          Dummy preprocessing step.\"\"\"\n\n    # Use Dataset.path to access a local\
          \ file path for writing.\n    # One can also use Dataset.uri to access the\
          \ actual URI file path.\n    with open(output_dataset_one.path, 'w') as\
          \ f:\n        f.write(message)\n\n    # OutputPath is used to just pass\
          \ the local file path of the output artifact\n    # to the function.\n \
          \   with open(output_dataset_two_path, 'w') as f:\n        f.write(message)\n\
          \n    with open(output_parameter_path, 'w') as f:\n        f.write(message)\n\
          \n    with open(output_bool_parameter_path, 'w') as f:\n        f.write(\n\
          \            str(True))  # use either `str()` or `json.dumps()` for bool\
          \ values.\n\n    import json\n    with open(output_dict_parameter_path,\
          \ 'w') as f:\n        f.write(json.dumps(input_dict_parameter))\n\n    with\
          \ open(output_list_parameter_path, 'w') as f:\n        f.write(json.dumps(input_list_parameter))\n\
          \n"
        image: python:3.7
pipelineInfo:
  name: preprocess
root:
  dag:
    outputs:
      artifacts:
        output_dataset_one:
          artifactSelectors:
          - outputArtifactKey: output_dataset_one
            producerSubtask: preprocess
        output_dataset_two_path:
          artifactSelectors:
          - outputArtifactKey: output_dataset_two_path
            producerSubtask: preprocess
      parameters:
        output_bool_parameter_path:
          valueFromParameter:
            outputParameterKey: output_bool_parameter_path
            producerSubtask: preprocess
        output_dict_parameter_path:
          valueFromParameter:
            outputParameterKey: output_dict_parameter_path
            producerSubtask: preprocess
        output_list_parameter_path:
          valueFromParameter:
            outputParameterKey: output_list_parameter_path
            producerSubtask: preprocess
        output_parameter_path:
          valueFromParameter:
            outputParameterKey: output_parameter_path
            producerSubtask: preprocess
    tasks:
      preprocess:
        cachingOptions:
          enableCache: true
        componentRef:
          name: comp-preprocess
        inputs:
          parameters:
            input_dict_parameter:
              componentInputParameter: input_dict_parameter
            input_list_parameter:
              componentInputParameter: input_list_parameter
            message:
              componentInputParameter: message
        taskInfo:
          name: preprocess
  inputDefinitions:
    parameters:
      input_dict_parameter:
        parameterType: STRUCT
      input_list_parameter:
        parameterType: LIST
      message:
        parameterType: STRING
  outputDefinitions:
    artifacts:
      output_dataset_one:
        artifactType:
          schemaTitle: system.Dataset
          schemaVersion: 0.0.1
      output_dataset_two_path:
        artifactType:
          schemaTitle: system.Dataset
          schemaVersion: 0.0.1
    parameters:
      output_bool_parameter_path:
        parameterType: BOOLEAN
      output_dict_parameter_path:
        parameterType: STRUCT
      output_list_parameter_path:
        parameterType: LIST
      output_parameter_path:
        parameterType: STRING
schemaVersion: 2.1.0
sdkVersion: kfp-2.1.3