prompt: We are currently solving the following issue within our repository. Here is the issue text:
  --- BEGIN ISSUE ---
  [Component] AutoML Tables component should show link as an artifact
  /cc @jessiezcc 
  /cc @jingzhang36 
  /assign @Ark-kun 
  
  It will be helpful if components in 
  https://github.com/kubeflow/pipelines/tree/b89aabbce5d48fca10817c3ed3ecc2acf6c0066a/components/gcp/automl can show related AutoML tables url as markdown artifacts.
  
  e.g.
  > We would like to be able to click on a link that would take us from the component’s page to an AutoML Tables models page
  
  --- END ISSUE ---
  
  Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
  --- BEGIN FILES ---
  Path: `components/gcp/automl/create_model_for_tables/component.py`
  Content:
  ```
  1 # Copyright 2019 Google LLC
  2 #
  3 # Licensed under the Apache License, Version 2.0 (the "License");
  4 # you may not use this file except in compliance with the License.
  5 # You may obtain a copy of the License at
  6 #
  7 #      http://www.apache.org/licenses/LICENSE-2.0
  8 #
  9 # Unless required by applicable law or agreed to in writing, software
  10 # distributed under the License is distributed on an "AS IS" BASIS,
  11 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  12 # See the License for the specific language governing permissions and
  13 # limitations under the License.
  14 
  15 from typing import NamedTuple
  16 
  17 
  18 def automl_create_model_for_tables(
  19     gcp_project_id: str,
  20     gcp_region: str,
  21     display_name: str,
  22     dataset_id: str,
  23     target_column_path: str = None,
  24     input_feature_column_paths: list = None,
  25     optimization_objective: str = 'MAXIMIZE_AU_PRC',
  26     train_budget_milli_node_hours: int = 1000,
  27 ) -> NamedTuple('Outputs', [('model_path', str), ('model_id', str)]):
  28     import sys
  29     import subprocess
  30     subprocess.run([sys.executable, '-m', 'pip', 'install', 'google-cloud-automl==0.4.0', '--quiet', '--no-warn-script-location'], env={'PIP_DISABLE_PIP_VERSION_CHECK': '1'}, check=True)
  31 
  32     from google.cloud import automl
  33     client = automl.AutoMlClient()
  34 
  35     location_path = client.location_path(gcp_project_id, gcp_region)
  36     model_dict = {
  37         'display_name': display_name,
  38         'dataset_id': dataset_id,
  39         'tables_model_metadata': {
  40             'target_column_spec': automl.types.ColumnSpec(name=target_column_path),
  41             'input_feature_column_specs': [automl.types.ColumnSpec(name=path) for path in input_feature_column_paths] if input_feature_column_paths else None,
  42             'optimization_objective': optimization_objective,
  43             'train_budget_milli_node_hours': train_budget_milli_node_hours,
  44         },
  45     }
  46 
  47     create_model_response = client.create_model(location_path, model_dict)
  48     print('Create model operation: {}'.format(create_model_response.operation))
  49     result = create_model_response.result()
  50     print(result)
  51     model_name = result.name
  52     model_id = model_name.rsplit('/', 1)[-1]
  53     return (model_name, model_id)
  54 
  55 
  56 if __name__ == '__main__':
  57     import kfp
  58     kfp.components.func_to_container_op(automl_create_model_for_tables, output_component_file='component.yaml', base_image='python:3.7')
  59
  ```
  
  Path: `components/gcp/automl/create_dataset_for_tables/component.py`
  Content:
  ```
  1 # Copyright 2019 Google LLC
  2 #
  3 # Licensed under the Apache License, Version 2.0 (the "License");
  4 # you may not use this file except in compliance with the License.
  5 # You may obtain a copy of the License at
  6 #
  7 #      http://www.apache.org/licenses/LICENSE-2.0
  8 #
  9 # Unless required by applicable law or agreed to in writing, software
  10 # distributed under the License is distributed on an "AS IS" BASIS,
  11 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  12 # See the License for the specific language governing permissions and
  13 # limitations under the License.
  14 
  15 from typing import NamedTuple
  16 
  17 
  18 def automl_create_dataset_for_tables(
  19     gcp_project_id: str,
  20     gcp_region: str,
  21     display_name: str,
  22     description: str = None,
  23     tables_dataset_metadata: dict = {},
  24     retry=None, #=google.api_core.gapic_v1.method.DEFAULT,
  25     timeout: float = None, #=google.api_core.gapic_v1.method.DEFAULT,
  26     metadata: dict = None,
  27 ) -> NamedTuple('Outputs', [('dataset_path', str), ('create_time', str), ('dataset_id', str)]):
  28     '''automl_create_dataset_for_tables creates an empty Dataset for AutoML tables
  29     '''
  30     import sys
  31     import subprocess
  32     subprocess.run([sys.executable, '-m', 'pip', 'install', 'google-cloud-automl==0.4.0', '--quiet', '--no-warn-script-location'], env={'PIP_DISABLE_PIP_VERSION_CHECK': '1'}, check=True)
  33 
  34     import google
  35     from google.cloud import automl
  36     client = automl.AutoMlClient()
  37 
  38     location_path = client.location_path(gcp_project_id, gcp_region)
  39     dataset_dict = {
  40         'display_name': display_name,
  41         'description': description,
  42         'tables_dataset_metadata': tables_dataset_metadata,
  43     }
  44     dataset = client.create_dataset(
  45         location_path,
  46         dataset_dict,
  47         retry or google.api_core.gapic_v1.method.DEFAULT,
  48         timeout or google.api_core.gapic_v1.method.DEFAULT,
  49         metadata,
  50     )
  51     print(dataset)
  52     dataset_id = dataset.name.rsplit('/', 1)[-1]
  53     return (dataset.name, dataset.create_time, dataset_id)
  54 
  55 
  56 if __name__ == '__main__':
  57     import kfp
  58     kfp.components.func_to_container_op(automl_create_dataset_for_tables, output_component_file='component.yaml', base_image='python:3.7')
  59
  ```
  --- END FILES ---
  
  Please first localize the bug based on the issue statement, and then generate a patch according to the `git diff` format fenced by three backticks.
  
  Here is an example:
  
  ```diff
  diff --git a/examples/server_async.py b/examples/server_async.py
  --- a/examples/server_async.py
  +++ b/examples/server_async.py
  @@ -313,4 +313,4 @@
   
   
   if __name__ == "__main__":
  -    asyncio.run(run_async_server("."), debug=True)
  +    asyncio.run(run_async_server(), debug=True)
  diff --git a/examples/server_sync.py b/examples/server_sync.py
  --- a/examples/server_sync.py
  +++ b/examples/server_sync.py
  @@ -313,5 +313,5 @@
   
   
   if __name__ == "__main__":
  -    server = run_sync_server(".")
  +    server = run_sync_server()
       server.shutdown()
  
  ```
  
golden_diff: diff --git a/components/gcp/automl/create_dataset_for_tables/component.py b/components/gcp/automl/create_dataset_for_tables/component.py
  --- a/components/gcp/automl/create_dataset_for_tables/component.py
  +++ b/components/gcp/automl/create_dataset_for_tables/component.py
  @@ -24,13 +24,9 @@
       retry=None, #=google.api_core.gapic_v1.method.DEFAULT,
       timeout: float = None, #=google.api_core.gapic_v1.method.DEFAULT,
       metadata: dict = None,
  -) -> NamedTuple('Outputs', [('dataset_path', str), ('create_time', str), ('dataset_id', str)]):
  +) -> NamedTuple('Outputs', [('dataset_path', str), ('create_time', str), ('dataset_id', str), ('dataset_url', 'URI')]):
       '''automl_create_dataset_for_tables creates an empty Dataset for AutoML tables
       '''
  -    import sys
  -    import subprocess
  -    subprocess.run([sys.executable, '-m', 'pip', 'install', 'google-cloud-automl==0.4.0', '--quiet', '--no-warn-script-location'], env={'PIP_DISABLE_PIP_VERSION_CHECK': '1'}, check=True)
  -
       import google
       from google.cloud import automl
       client = automl.AutoMlClient()
  @@ -50,9 +46,19 @@
       )
       print(dataset)
       dataset_id = dataset.name.rsplit('/', 1)[-1]
  -    return (dataset.name, dataset.create_time, dataset_id)
  +    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)
   
   
   if __name__ == '__main__':
       import kfp
  -    kfp.components.func_to_container_op(automl_create_dataset_for_tables, output_component_file='component.yaml', base_image='python:3.7')
  +    kfp.components.func_to_container_op(
  +        automl_create_dataset_for_tables,
  +        output_component_file='component.yaml',
  +        base_image='python:3.7',
  +        packages_to_install=['google-cloud-automl==0.4.0']
  +    )
  diff --git a/components/gcp/automl/create_model_for_tables/component.py b/components/gcp/automl/create_model_for_tables/component.py
  --- a/components/gcp/automl/create_model_for_tables/component.py
  +++ b/components/gcp/automl/create_model_for_tables/component.py
  @@ -24,11 +24,7 @@
       input_feature_column_paths: list = None,
       optimization_objective: str = 'MAXIMIZE_AU_PRC',
       train_budget_milli_node_hours: int = 1000,
  -) -> NamedTuple('Outputs', [('model_path', str), ('model_id', str)]):
  -    import sys
  -    import subprocess
  -    subprocess.run([sys.executable, '-m', 'pip', 'install', 'google-cloud-automl==0.4.0', '--quiet', '--no-warn-script-location'], env={'PIP_DISABLE_PIP_VERSION_CHECK': '1'}, check=True)
  -
  +) -> NamedTuple('Outputs', [('model_path', str), ('model_id', str), ('model_page_url', 'URI'),]):
       from google.cloud import automl
       client = automl.AutoMlClient()
   
  @@ -50,9 +46,21 @@
       print(result)
       model_name = result.name
       model_id = model_name.rsplit('/', 1)[-1]
  -    return (model_name, model_id)
  +    model_url = 'https://console.cloud.google.com/automl-tables/locations/{region}/datasets/{dataset_id};modelId={model_id};task=basic/train?project={project_id}'.format(
  +        project_id=gcp_project_id,
  +        region=gcp_region,
  +        dataset_id=dataset_id,
  +        model_id=model_id,
  +    )
  +
  +    return (model_name, model_id, model_url)
   
   
   if __name__ == '__main__':
       import kfp
  -    kfp.components.func_to_container_op(automl_create_model_for_tables, output_component_file='component.yaml', base_image='python:3.7')
  +    kfp.components.func_to_container_op(
  +        automl_create_model_for_tables,
  +        output_component_file='component.yaml',
  +        base_image='python:3.7',
  +        packages_to_install=['google-cloud-automl==0.4.0']
  +    )
  
verification_info: {"golden_diff": "diff --git a/components/gcp/automl/create_dataset_for_tables/component.py b/components/gcp/automl/create_dataset_for_tables/component.py\n--- a/components/gcp/automl/create_dataset_for_tables/component.py\n+++ b/components/gcp/automl/create_dataset_for_tables/component.py\n@@ -24,13 +24,9 @@\n     retry=None, #=google.api_core.gapic_v1.method.DEFAULT,\n     timeout: float = None, #=google.api_core.gapic_v1.method.DEFAULT,\n     metadata: dict = None,\n-) -> NamedTuple('Outputs', [('dataset_path', str), ('create_time', str), ('dataset_id', str)]):\n+) -> NamedTuple('Outputs', [('dataset_path', str), ('create_time', str), ('dataset_id', str), ('dataset_url', 'URI')]):\n     '''automl_create_dataset_for_tables creates an empty Dataset for AutoML tables\n     '''\n-    import sys\n-    import subprocess\n-    subprocess.run([sys.executable, '-m', 'pip', 'install', 'google-cloud-automl==0.4.0', '--quiet', '--no-warn-script-location'], env={'PIP_DISABLE_PIP_VERSION_CHECK': '1'}, check=True)\n-\n     import google\n     from google.cloud import automl\n     client = automl.AutoMlClient()\n@@ -50,9 +46,19 @@\n     )\n     print(dataset)\n     dataset_id = dataset.name.rsplit('/', 1)[-1]\n-    return (dataset.name, dataset.create_time, dataset_id)\n+    dataset_url = 'https://console.cloud.google.com/automl-tables/locations/{region}/datasets/{dataset_id}/schemav2?project={project_id}'.format(\n+        project_id=gcp_project_id,\n+        region=gcp_region,\n+        dataset_id=dataset_id,\n+    )\n+    return (dataset.name, dataset.create_time, dataset_id, dataset_url)\n \n \n if __name__ == '__main__':\n     import kfp\n-    kfp.components.func_to_container_op(automl_create_dataset_for_tables, output_component_file='component.yaml', base_image='python:3.7')\n+    kfp.components.func_to_container_op(\n+        automl_create_dataset_for_tables,\n+        output_component_file='component.yaml',\n+        base_image='python:3.7',\n+        packages_to_install=['google-cloud-automl==0.4.0']\n+    )\ndiff --git a/components/gcp/automl/create_model_for_tables/component.py b/components/gcp/automl/create_model_for_tables/component.py\n--- a/components/gcp/automl/create_model_for_tables/component.py\n+++ b/components/gcp/automl/create_model_for_tables/component.py\n@@ -24,11 +24,7 @@\n     input_feature_column_paths: list = None,\n     optimization_objective: str = 'MAXIMIZE_AU_PRC',\n     train_budget_milli_node_hours: int = 1000,\n-) -> NamedTuple('Outputs', [('model_path', str), ('model_id', str)]):\n-    import sys\n-    import subprocess\n-    subprocess.run([sys.executable, '-m', 'pip', 'install', 'google-cloud-automl==0.4.0', '--quiet', '--no-warn-script-location'], env={'PIP_DISABLE_PIP_VERSION_CHECK': '1'}, check=True)\n-\n+) -> NamedTuple('Outputs', [('model_path', str), ('model_id', str), ('model_page_url', 'URI'),]):\n     from google.cloud import automl\n     client = automl.AutoMlClient()\n \n@@ -50,9 +46,21 @@\n     print(result)\n     model_name = result.name\n     model_id = model_name.rsplit('/', 1)[-1]\n-    return (model_name, model_id)\n+    model_url = 'https://console.cloud.google.com/automl-tables/locations/{region}/datasets/{dataset_id};modelId={model_id};task=basic/train?project={project_id}'.format(\n+        project_id=gcp_project_id,\n+        region=gcp_region,\n+        dataset_id=dataset_id,\n+        model_id=model_id,\n+    )\n+\n+    return (model_name, model_id, model_url)\n \n \n if __name__ == '__main__':\n     import kfp\n-    kfp.components.func_to_container_op(automl_create_model_for_tables, output_component_file='component.yaml', base_image='python:3.7')\n+    kfp.components.func_to_container_op(\n+        automl_create_model_for_tables,\n+        output_component_file='component.yaml',\n+        base_image='python:3.7',\n+        packages_to_install=['google-cloud-automl==0.4.0']\n+    )\n", "issue": "[Component] AutoML Tables component should show link as an artifact\n/cc @jessiezcc \r\n/cc @jingzhang36 \r\n/assign @Ark-kun \r\n\r\nIt will be helpful if components in \r\nhttps://github.com/kubeflow/pipelines/tree/b89aabbce5d48fca10817c3ed3ecc2acf6c0066a/components/gcp/automl can show related AutoML tables url as markdown artifacts.\r\n\r\ne.g.\r\n> We would like to be able to click on a link that would take us from the component\u2019s page to an AutoML Tables models page\n", "before_files": [{"content": "# Copyright 2019 Google LLC\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n#      http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\nfrom typing import NamedTuple\n\n\ndef automl_create_model_for_tables(\n    gcp_project_id: str,\n    gcp_region: str,\n    display_name: str,\n    dataset_id: str,\n    target_column_path: str = None,\n    input_feature_column_paths: list = None,\n    optimization_objective: str = 'MAXIMIZE_AU_PRC',\n    train_budget_milli_node_hours: int = 1000,\n) -> NamedTuple('Outputs', [('model_path', str), ('model_id', str)]):\n    import sys\n    import subprocess\n    subprocess.run([sys.executable, '-m', 'pip', 'install', 'google-cloud-automl==0.4.0', '--quiet', '--no-warn-script-location'], env={'PIP_DISABLE_PIP_VERSION_CHECK': '1'}, check=True)\n\n    from google.cloud import automl\n    client = automl.AutoMlClient()\n\n    location_path = client.location_path(gcp_project_id, gcp_region)\n    model_dict = {\n        'display_name': display_name,\n        'dataset_id': dataset_id,\n        'tables_model_metadata': {\n            'target_column_spec': automl.types.ColumnSpec(name=target_column_path),\n            'input_feature_column_specs': [automl.types.ColumnSpec(name=path) for path in input_feature_column_paths] if input_feature_column_paths else None,\n            'optimization_objective': optimization_objective,\n            'train_budget_milli_node_hours': train_budget_milli_node_hours,\n        },\n    }\n\n    create_model_response = client.create_model(location_path, model_dict)\n    print('Create model operation: {}'.format(create_model_response.operation))\n    result = create_model_response.result()\n    print(result)\n    model_name = result.name\n    model_id = model_name.rsplit('/', 1)[-1]\n    return (model_name, model_id)\n\n\nif __name__ == '__main__':\n    import kfp\n    kfp.components.func_to_container_op(automl_create_model_for_tables, output_component_file='component.yaml', base_image='python:3.7')\n", "path": "components/gcp/automl/create_model_for_tables/component.py"}, {"content": "# Copyright 2019 Google LLC\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n#      http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\nfrom typing import NamedTuple\n\n\ndef automl_create_dataset_for_tables(\n    gcp_project_id: str,\n    gcp_region: str,\n    display_name: str,\n    description: str = None,\n    tables_dataset_metadata: dict = {},\n    retry=None, #=google.api_core.gapic_v1.method.DEFAULT,\n    timeout: float = None, #=google.api_core.gapic_v1.method.DEFAULT,\n    metadata: dict = None,\n) -> NamedTuple('Outputs', [('dataset_path', str), ('create_time', str), ('dataset_id', str)]):\n    '''automl_create_dataset_for_tables creates an empty Dataset for AutoML tables\n    '''\n    import sys\n    import subprocess\n    subprocess.run([sys.executable, '-m', 'pip', 'install', 'google-cloud-automl==0.4.0', '--quiet', '--no-warn-script-location'], env={'PIP_DISABLE_PIP_VERSION_CHECK': '1'}, check=True)\n\n    import google\n    from google.cloud import automl\n    client = automl.AutoMlClient()\n\n    location_path = client.location_path(gcp_project_id, gcp_region)\n    dataset_dict = {\n        'display_name': display_name,\n        'description': description,\n        'tables_dataset_metadata': tables_dataset_metadata,\n    }\n    dataset = client.create_dataset(\n        location_path,\n        dataset_dict,\n        retry or google.api_core.gapic_v1.method.DEFAULT,\n        timeout or google.api_core.gapic_v1.method.DEFAULT,\n        metadata,\n    )\n    print(dataset)\n    dataset_id = dataset.name.rsplit('/', 1)[-1]\n    return (dataset.name, dataset.create_time, dataset_id)\n\n\nif __name__ == '__main__':\n    import kfp\n    kfp.components.func_to_container_op(automl_create_dataset_for_tables, output_component_file='component.yaml', base_image='python:3.7')\n", "path": "components/gcp/automl/create_dataset_for_tables/component.py"}], "after_files": [{"content": "# Copyright 2019 Google LLC\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n#      http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\nfrom typing import NamedTuple\n\n\ndef automl_create_model_for_tables(\n    gcp_project_id: str,\n    gcp_region: str,\n    display_name: str,\n    dataset_id: str,\n    target_column_path: str = None,\n    input_feature_column_paths: list = None,\n    optimization_objective: str = 'MAXIMIZE_AU_PRC',\n    train_budget_milli_node_hours: int = 1000,\n) -> NamedTuple('Outputs', [('model_path', str), ('model_id', str), ('model_page_url', 'URI'),]):\n    from google.cloud import automl\n    client = automl.AutoMlClient()\n\n    location_path = client.location_path(gcp_project_id, gcp_region)\n    model_dict = {\n        'display_name': display_name,\n        'dataset_id': dataset_id,\n        'tables_model_metadata': {\n            'target_column_spec': automl.types.ColumnSpec(name=target_column_path),\n            'input_feature_column_specs': [automl.types.ColumnSpec(name=path) for path in input_feature_column_paths] if input_feature_column_paths else None,\n            'optimization_objective': optimization_objective,\n            'train_budget_milli_node_hours': train_budget_milli_node_hours,\n        },\n    }\n\n    create_model_response = client.create_model(location_path, model_dict)\n    print('Create model operation: {}'.format(create_model_response.operation))\n    result = create_model_response.result()\n    print(result)\n    model_name = result.name\n    model_id = model_name.rsplit('/', 1)[-1]\n    model_url = 'https://console.cloud.google.com/automl-tables/locations/{region}/datasets/{dataset_id};modelId={model_id};task=basic/train?project={project_id}'.format(\n        project_id=gcp_project_id,\n        region=gcp_region,\n        dataset_id=dataset_id,\n        model_id=model_id,\n    )\n\n    return (model_name, model_id, model_url)\n\n\nif __name__ == '__main__':\n    import kfp\n    kfp.components.func_to_container_op(\n        automl_create_model_for_tables,\n        output_component_file='component.yaml',\n        base_image='python:3.7',\n        packages_to_install=['google-cloud-automl==0.4.0']\n    )\n", "path": "components/gcp/automl/create_model_for_tables/component.py"}, {"content": "# Copyright 2019 Google LLC\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n#      http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\nfrom typing import NamedTuple\n\n\ndef automl_create_dataset_for_tables(\n    gcp_project_id: str,\n    gcp_region: str,\n    display_name: str,\n    description: str = None,\n    tables_dataset_metadata: dict = {},\n    retry=None, #=google.api_core.gapic_v1.method.DEFAULT,\n    timeout: float = None, #=google.api_core.gapic_v1.method.DEFAULT,\n    metadata: dict = None,\n) -> NamedTuple('Outputs', [('dataset_path', str), ('create_time', str), ('dataset_id', str), ('dataset_url', 'URI')]):\n    '''automl_create_dataset_for_tables creates an empty Dataset for AutoML tables\n    '''\n    import google\n    from google.cloud import automl\n    client = automl.AutoMlClient()\n\n    location_path = client.location_path(gcp_project_id, gcp_region)\n    dataset_dict = {\n        'display_name': display_name,\n        'description': description,\n        'tables_dataset_metadata': tables_dataset_metadata,\n    }\n    dataset = client.create_dataset(\n        location_path,\n        dataset_dict,\n        retry or google.api_core.gapic_v1.method.DEFAULT,\n        timeout or google.api_core.gapic_v1.method.DEFAULT,\n        metadata,\n    )\n    print(dataset)\n    dataset_id = dataset.name.rsplit('/', 1)[-1]\n    dataset_url = 'https://console.cloud.google.com/automl-tables/locations/{region}/datasets/{dataset_id}/schemav2?project={project_id}'.format(\n        project_id=gcp_project_id,\n        region=gcp_region,\n        dataset_id=dataset_id,\n    )\n    return (dataset.name, dataset.create_time, dataset_id, dataset_url)\n\n\nif __name__ == '__main__':\n    import kfp\n    kfp.components.func_to_container_op(\n        automl_create_dataset_for_tables,\n        output_component_file='component.yaml',\n        base_image='python:3.7',\n        packages_to_install=['google-cloud-automl==0.4.0']\n    )\n", "path": "components/gcp/automl/create_dataset_for_tables/component.py"}]}