automl beta [(#1575)](GoogleCloudPlatform/python-docs-samples#1575)

* automl initial commit

* lint

* fix import groupings

* add requirements.txt

* address review comments

samples/samples/snippets/automl_translation_dataset.py

@@ -0,0 +1,278 @@
+#!/usr/bin/env python
+
+# Copyright 2018 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""This application demonstrates how to perform basic operations on dataset
+with the Google AutoML Translation API.
+
+For more information, see the documentation at
+https://cloud.google.com/translate/automl/docs
+"""
+
+import argparse
+import os
+
+
+def create_dataset(project_id, compute_region, dataset_name, source, target):
+    """Create a dataset."""
+    # [START automl_translation_create_dataset]
+    # TODO(developer): Uncomment and set the following variables
+    # project_id = 'PROJECT_ID_HERE'
+    # compute_region = 'COMPUTE_REGION_HERE'
+    # dataset_name = 'DATASET_NAME_HERE'
+    # source = 'LANGUAGE_CODE_OF_SOURCE_LANGUAGE'
+    # target = 'LANGUAGE_CODE_OF_TARGET_LANGUAGE'
+
+    from google.cloud import automl_v1beta1 as automl
+
+    client = automl.AutoMlClient()
+
+    # A resource that represents Google Cloud Platform location.
+    project_location = client.location_path(project_id, compute_region)
+
+    # Specify the source and target language.
+    dataset_metadata = {
+        "source_language_code": source,
+        "target_language_code": target,
+    }
+    # Set dataset name and dataset metadata
+    my_dataset = {
+        "display_name": dataset_name,
+        "translation_dataset_metadata": dataset_metadata,
+    }
+
+    # Create a dataset with the dataset metadata in the region.
+    dataset = client.create_dataset(project_location, my_dataset)
+
+    # Display the dataset information
+    print("Dataset name: {}".format(dataset.name))
+    print("Dataset id: {}".format(dataset.name.split("/")[-1]))
+    print("Dataset display name: {}".format(dataset.display_name))
+    print("Translation dataset Metadata:")
+    print(
+        "\tsource_language_code: {}".format(
+            dataset.translation_dataset_metadata.source_language_code
+        )
+    )
+    print(
+        "\ttarget_language_code: {}".format(
+            dataset.translation_dataset_metadata.target_language_code
+        )
+    )
+    print("Dataset create time:")
+    print("\tseconds: {}".format(dataset.create_time.seconds))
+    print("\tnanos: {}".format(dataset.create_time.nanos))
+
+    # [END automl_translation_create_dataset]
+
+
+def list_datasets(project_id, compute_region, filter_):
+    """List Datasets."""
+    # [START automl_translation_list_datasets]
+    # TODO(developer): Uncomment and set the following variables
+    # project_id = 'PROJECT_ID_HERE'
+    # compute_region = 'COMPUTE_REGION_HERE'
+    # filter_ = 'filter expression here'
+
+    from google.cloud import automl_v1beta1 as automl
+
+    client = automl.AutoMlClient()
+
+    # A resource that represents Google Cloud Platform location.
+    project_location = client.location_path(project_id, compute_region)
+
+    # List all the datasets available in the region by applying filter.
+    response = client.list_datasets(project_location, filter_)
+
+    print("List of datasets:")
+    for dataset in response:
+        # Display the dataset information
+        print("Dataset name: {}".format(dataset.name))
+        print("Dataset id: {}".format(dataset.name.split("/")[-1]))
+        print("Dataset display name: {}".format(dataset.display_name))
+        print("Translation dataset metadata:")
+        print(
+            "\tsource_language_code: {}".format(
+                dataset.translation_dataset_metadata.source_language_code
+            )
+        )
+        print(
+            "\ttarget_language_code: {}".format(
+                dataset.translation_dataset_metadata.target_language_code
+            )
+        )
+        print("Dataset create time:")
+        print("\tseconds: {}".format(dataset.create_time.seconds))
+        print("\tnanos: {}".format(dataset.create_time.nanos))
+
+    # [END automl_translation_list_datasets]
+
+
+def get_dataset(project_id, compute_region, dataset_id):
+    """Get the dataset."""
+    # [START automl_translation_get_dataset]
+    # TODO(developer): Uncomment and set the following variables
+    # project_id = 'PROJECT_ID_HERE'
+    # compute_region = 'COMPUTE_REGION_HERE'
+    # dataset_id = 'DATASET_ID_HERE'
+
+    from google.cloud import automl_v1beta1 as automl
+
+    client = automl.AutoMlClient()
+
+    # Get the full path of the dataset
+    dataset_full_id = client.dataset_path(
+        project_id, compute_region, dataset_id
+    )
+
+    # Get complete detail of the dataset.
+    dataset = client.get_dataset(dataset_full_id)
+
+    # Display the dataset information
+    print("Dataset name: {}".format(dataset.name))
+    print("Dataset id: {}".format(dataset.name.split("/")[-1]))
+    print("Dataset display name: {}".format(dataset.display_name))
+    print("Translation dataset metadata:")
+    print(
+        "\tsource_language_code: {}".format(
+            dataset.translation_dataset_metadata.source_language_code
+        )
+    )
+    print(
+        "\ttarget_language_code: {}".format(
+            dataset.translation_dataset_metadata.target_language_code
+        )
+    )
+    print("Dataset create time:")
+    print("\tseconds: {}".format(dataset.create_time.seconds))
+    print("\tnanos: {}".format(dataset.create_time.nanos))
+
+    # [END automl_translation_get_dataset]
+
+
+def import_data(project_id, compute_region, dataset_id, path):
+    """Import sentence pairs to the dataset."""
+    # [START automl_translation_import_data]
+    # TODO(developer): Uncomment and set the following variables
+    # project_id = 'PROJECT_ID_HERE'
+    # compute_region = 'COMPUTE_REGION_HERE'
+    # dataset_id = 'DATASET_ID_HERE'
+    # path = 'gs://path/to/file.csv'
+
+    from google.cloud import automl_v1beta1 as automl
+
+    client = automl.AutoMlClient()
+
+    # Get the full path of the dataset.
+    dataset_full_id = client.dataset_path(
+        project_id, compute_region, dataset_id
+    )
+
+    # Get the multiple Google Cloud Storage URIs
+    input_uris = path.split(",")
+    input_config = {"gcs_source": {"input_uris": input_uris}}
+
+    # Import data from the input URI
+    response = client.import_data(dataset_full_id, input_config)
+
+    print("Processing import...")
+    # synchronous check of operation status
+    print("Data imported. {}".format(response.result()))
+
+    # [END automl_translation_import_data]
+
+
+def delete_dataset(project_id, compute_region, dataset_id):
+    """Delete a dataset."""
+    # [START automl_translation_delete_dataset]]
+    # TODO(developer): Uncomment and set the following variables
+    # project_id = 'PROJECT_ID_HERE'
+    # compute_region = 'COMPUTE_REGION_HERE'
+    # dataset_id = 'DATASET_ID_HERE'
+
+    from google.cloud import automl_v1beta1 as automl
+
+    client = automl.AutoMlClient()
+
+    # Get the full path of the dataset.
+    dataset_full_id = client.dataset_path(
+        project_id, compute_region, dataset_id
+    )
+
+    # Delete a dataset.
+    response = client.delete_dataset(dataset_full_id)
+
+    # synchronous check of operation status
+    print("Dataset deleted. {}".format(response.result()))
+
+    # [END automl_translation_delete_dataset]
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(
+        description=__doc__,
+        formatter_class=argparse.RawDescriptionHelpFormatter,
+    )
+    subparsers = parser.add_subparsers(dest="command")
+
+    create_dataset_parser = subparsers.add_parser(
+        "create_dataset", help=create_dataset.__doc__
+    )
+    create_dataset_parser.add_argument("dataset_name")
+    create_dataset_parser.add_argument("source")
+    create_dataset_parser.add_argument("target")
+
+    list_datasets_parser = subparsers.add_parser(
+        "list_datasets", help=list_datasets.__doc__
+    )
+    list_datasets_parser.add_argument("filter", nargs="?", default="")
+
+    import_data_parser = subparsers.add_parser(
+        "import_data", help=import_data.__doc__
+    )
+    import_data_parser.add_argument("dataset_id")
+    import_data_parser.add_argument("path")
+
+    delete_dataset_parser = subparsers.add_parser(
+        "delete_dataset", help=delete_dataset.__doc__
+    )
+    delete_dataset_parser.add_argument("dataset_id")
+
+    get_dataset_parser = subparsers.add_parser(
+        "get_dataset", help=get_dataset.__doc__
+    )
+    get_dataset_parser.add_argument("dataset_id")
+
+    project_id = os.environ["PROJECT_ID"]
+    compute_region = os.environ["REGION_NAME"]
+
+    args = parser.parse_args()
+
+    if args.command == "create_dataset":
+        create_dataset(
+            project_id,
+            compute_region,
+            args.dataset_name,
+            args.source,
+            args.target,
+        )
+    if args.command == "list_datasets":
+        list_datasets(project_id, compute_region, args.filter)
+    if args.command == "get_dataset":
+        get_dataset(project_id, compute_region, args.dataset_id)
+    if args.command == "import_data":
+        import_data(project_id, compute_region, args.dataset_id, args.path)
+    if args.command == "delete_dataset":
+        delete_dataset(project_id, compute_region, args.dataset_id)