component.yaml

name: Automl create dataset for tables
description: automl_create_dataset_for_tables creates an empty Dataset for AutoML
  tables
inputs:
- {name: gcp_project_id, type: String}
- {name: gcp_region, type: String}
- {name: display_name, type: String}
- {name: description, type: String, optional: true}
- {name: tables_dataset_metadata, type: JsonObject, default: '{}', optional: true}
- {name: retry, optional: true}
- {name: timeout, type: Float, optional: true}
- {name: metadata, type: JsonObject, optional: true}
outputs:
- {name: dataset_path, type: String}
- {name: create_time, type: String}
- {name: dataset_id, type: String}
- {name: dataset_url, type: URI}
implementation:
  container:
    image: python:3.7
    command:
    - sh
    - -c
    - (PIP_DISABLE_PIP_VERSION_CHECK=1 python3 -m pip install --quiet --no-warn-script-location
      'google-cloud-automl==0.4.0' || PIP_DISABLE_PIP_VERSION_CHECK=1 python3 -m pip
      install --quiet --no-warn-script-location 'google-cloud-automl==0.4.0' --user)
      && "$0" "$@"
    - python3
    - -u
    - -c
    - |
      def automl_create_dataset_for_tables(
          gcp_project_id ,
          gcp_region ,
          display_name ,
          description  = None,
          tables_dataset_metadata  = {},
          retry=None, #=google.api_core.gapic_v1.method.DEFAULT,
          timeout  = None, #=google.api_core.gapic_v1.method.DEFAULT,
          metadata  = None,
      )          :
          '''automl_create_dataset_for_tables creates an empty Dataset for AutoML tables
          '''
          import google
          from google.cloud import automl
          client = automl.AutoMlClient()

          location_path = client.location_path(gcp_project_id, gcp_region)
          dataset_dict = {
              'display_name': display_name,
              'description': description,
              'tables_dataset_metadata': tables_dataset_metadata,
          }
          dataset = client.create_dataset(
              location_path,
              dataset_dict,
              retry or google.api_core.gapic_v1.method.DEFAULT,
              timeout or google.api_core.gapic_v1.method.DEFAULT,
              metadata,
          )
          print(dataset)
          dataset_id = dataset.name.rsplit('/', 1)[-1]
          dataset_url = 'https://console.cloud.google.com/automl-tables/locations/{region}/datasets/{dataset_id}/schemav2?project={project_id}'.format(
              project_id=gcp_project_id,
              region=gcp_region,
              dataset_id=dataset_id,
          )
          return (dataset.name, dataset.create_time, dataset_id, dataset_url)

      import json
      def _serialize_str(str_value: str) -> str:
          if not isinstance(str_value, str):
              raise TypeError('Value "{}" has type "{}" instead of str.'.format(str(str_value), str(type(str_value))))
          return str_value

      import argparse
      _parser = argparse.ArgumentParser(prog='Automl create dataset for tables', description='automl_create_dataset_for_tables creates an empty Dataset for AutoML tables')
      _parser.add_argument("--gcp-project-id", dest="gcp_project_id", type=str, required=True, default=argparse.SUPPRESS)
      _parser.add_argument("--gcp-region", dest="gcp_region", type=str, required=True, default=argparse.SUPPRESS)
      _parser.add_argument("--display-name", dest="display_name", type=str, required=True, default=argparse.SUPPRESS)
      _parser.add_argument("--description", dest="description", type=str, required=False, default=argparse.SUPPRESS)
      _parser.add_argument("--tables-dataset-metadata", dest="tables_dataset_metadata", type=json.loads, required=False, default=argparse.SUPPRESS)
      _parser.add_argument("--retry", dest="retry", type=str, required=False, default=argparse.SUPPRESS)
      _parser.add_argument("--timeout", dest="timeout", type=float, required=False, default=argparse.SUPPRESS)
      _parser.add_argument("--metadata", dest="metadata", type=json.loads, required=False, default=argparse.SUPPRESS)
      _parser.add_argument("----output-paths", dest="_output_paths", type=str, nargs=4)
      _parsed_args = vars(_parser.parse_args())
      _output_files = _parsed_args.pop("_output_paths", [])

      _outputs = automl_create_dataset_for_tables(**_parsed_args)

      _output_serializers = [
          _serialize_str,
          _serialize_str,
          _serialize_str,
          str,

      ]

      import os
      for idx, output_file in enumerate(_output_files):
          try:
              os.makedirs(os.path.dirname(output_file))
          except OSError:
              pass
          with open(output_file, 'w') as f:
              f.write(_output_serializers[idx](_outputs[idx]))
    args:
    - --gcp-project-id
    - {inputValue: gcp_project_id}
    - --gcp-region
    - {inputValue: gcp_region}
    - --display-name
    - {inputValue: display_name}
    - if:
        cond: {isPresent: description}
        then:
        - --description
        - {inputValue: description}
    - if:
        cond: {isPresent: tables_dataset_metadata}
        then:
        - --tables-dataset-metadata
        - {inputValue: tables_dataset_metadata}
    - if:
        cond: {isPresent: retry}
        then:
        - --retry
        - {inputValue: retry}
    - if:
        cond: {isPresent: timeout}
        then:
        - --timeout
        - {inputValue: timeout}
    - if:
        cond: {isPresent: metadata}
        then:
        - --metadata
        - {inputValue: metadata}
    - '----output-paths'
    - {outputPath: dataset_path}
    - {outputPath: create_time}
    - {outputPath: dataset_id}
    - {outputPath: dataset_url}