diff --git a/.github/.OwlBot.lock.yaml b/.github/.OwlBot.lock.yaml index cb89b2e3..eecb84c2 100644 --- a/.github/.OwlBot.lock.yaml +++ b/.github/.OwlBot.lock.yaml @@ -1,3 +1,3 @@ docker: image: gcr.io/cloud-devrel-public-resources/owlbot-python:latest - digest: sha256:ec49167c606648a063d1222220b48119c912562849a0528f35bfb592a9f72737 + digest: sha256:ae600f36b6bc972b368367b6f83a1d91ec2c82a4a116b383d67d547c56fe6de3 diff --git a/.github/CODEOWNERS b/.github/CODEOWNERS index efc461e0..62aced93 100644 --- a/.github/CODEOWNERS +++ b/.github/CODEOWNERS @@ -3,9 +3,10 @@ # # For syntax help see: # https://help.github.com/en/github/creating-cloning-and-archiving-repositories/about-code-owners#codeowners-syntax +# Note: This file is autogenerated. To make changes to the codeowner team, please update .repo-metadata.json. -# The @googleapis/yoshi-python is the default owner for changes in this repo -* @googleapis/yoshi-python +# @googleapis/yoshi-python @googleapis/cdpe-cloudai are the default owners for changes in this repo +* @googleapis/yoshi-python @googleapis/cdpe-cloudai - -/samples/**/*.py @telpirion @sirtorry @googleapis/python-samples-owners +# @googleapis/python-samples-reviewers @googleapis/cdpe-cloudai are the default owners for samples changes +/samples/ @googleapis/python-samples-reviewers @googleapis/cdpe-cloudai diff --git a/.github/release-please.yml b/.github/release-please.yml index 4507ad05..466597e5 100644 --- a/.github/release-please.yml +++ b/.github/release-please.yml @@ -1 +1,2 @@ releaseType: python +handleGHRelease: true diff --git a/.github/release-trigger.yml b/.github/release-trigger.yml new file mode 100644 index 00000000..d4ca9418 --- /dev/null +++ b/.github/release-trigger.yml @@ -0,0 +1 @@ +enabled: true diff --git a/.kokoro/release.sh b/.kokoro/release.sh index 9fb1ab29..9c3fb7c1 100755 --- a/.kokoro/release.sh +++ b/.kokoro/release.sh @@ -26,7 +26,7 @@ python3 -m pip install --upgrade twine wheel setuptools export PYTHONUNBUFFERED=1 # Move into the package, build the distribution and upload. -TWINE_PASSWORD=$(cat "${KOKORO_GFILE_DIR}/secret_manager/google-cloud-pypi-token") +TWINE_PASSWORD=$(cat "${KOKORO_KEYSTORE_DIR}/73713_google-cloud-pypi-token-keystore-1") cd github/python-automl python3 setup.py sdist bdist_wheel twine upload --username __token__ --password "${TWINE_PASSWORD}" dist/* diff --git a/.kokoro/release/common.cfg b/.kokoro/release/common.cfg index 5926a5cf..f105268c 100644 --- a/.kokoro/release/common.cfg +++ b/.kokoro/release/common.cfg @@ -23,8 +23,18 @@ env_vars: { value: "github/python-automl/.kokoro/release.sh" } +# Fetch PyPI password +before_action { + fetch_keystore { + keystore_resource { + keystore_config_id: 73713 + keyname: "google-cloud-pypi-token-keystore-1" + } + } +} + # Tokens needed to report release status back to GitHub env_vars: { key: "SECRET_MANAGER_KEYS" - value: "releasetool-publish-reporter-app,releasetool-publish-reporter-googleapis-installation,releasetool-publish-reporter-pem,google-cloud-pypi-token" + value: "releasetool-publish-reporter-app,releasetool-publish-reporter-googleapis-installation,releasetool-publish-reporter-pem" } diff --git a/.repo-metadata.json b/.repo-metadata.json index ee97ad54..c0257b34 100644 --- a/.repo-metadata.json +++ b/.repo-metadata.json @@ -1,14 +1,17 @@ { - "name": "automl", - "name_pretty": "Cloud AutoML", - "product_documentation": "https://cloud.google.com/automl/docs/", - "client_documentation": "https://googleapis.dev/python/automl/latest", - "issue_tracker": "https://issuetracker.google.com/savedsearches/559744", - "release_level": "ga", - "language": "python", - "library_type": "GAPIC_AUTO", - "repo": "googleapis/python-automl", - "distribution_name": "google-cloud-automl", - "api_id": "automl.googleapis.com", - "requires_billing": true -} \ No newline at end of file + "name": "automl", + "name_pretty": "Cloud AutoML", + "product_documentation": "https://cloud.google.com/automl/docs/", + "client_documentation": "https://cloud.google.com/python/docs/reference/automl/latest", + "issue_tracker": "https://issuetracker.google.com/savedsearches/559744", + "release_level": "stable", + "language": "python", + "library_type": "GAPIC_AUTO", + "repo": "googleapis/python-automl", + "distribution_name": "google-cloud-automl", + "api_id": "automl.googleapis.com", + "requires_billing": true, + "default_version": "v1", + "codeowner_team": "@googleapis/cdpe-cloudai", + "api_shortname": "automl" +} diff --git a/CHANGELOG.md b/CHANGELOG.md index 4c7f705f..8f31f975 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -4,6 +4,18 @@ [1]: https://pypi.org/project/google-cloud-automl/#history +## [2.6.0](https://github.com/googleapis/python-automl/compare/v2.5.2...v2.6.0) (2022-01-15) + + +### Features + +* publish updated protos for cloud/automl/v1 service ([#318](https://github.com/googleapis/python-automl/issues/318)) ([3bf0271](https://github.com/googleapis/python-automl/commit/3bf0271dce60fe9843711068e85978b627f77db6)) + + +### Bug Fixes + +* **deps:** allow google-cloud-storage < 3.0.0dev ([#316](https://github.com/googleapis/python-automl/issues/316)) ([ba271a8](https://github.com/googleapis/python-automl/commit/ba271a8cfea916f7fb3df536258cda2dca32a423)) + ### [2.5.2](https://www.github.com/googleapis/python-automl/compare/v2.5.1...v2.5.2) (2021-11-01) diff --git a/README.rst b/README.rst index 0cdb8b3e..abb1b3e1 100644 --- a/README.rst +++ b/README.rst @@ -18,7 +18,7 @@ transfer learning, and Neural Architecture Search technology. .. |versions| image:: https://img.shields.io/pypi/pyversions/google-cloud-automl.svg :target: https://pypi.org/project/google-cloud-automl/ .. _Cloud AutoML API: https://cloud.google.com/automl -.. _Client Library Documentation: https://googleapis.dev/python/automl/latest +.. _Client Library Documentation: https://cloud.google.com/python/docs/reference/automl/latest .. _Product Documentation: https://cloud.google.com/automl Quick Start diff --git a/google/cloud/automl_v1/services/auto_ml/async_client.py b/google/cloud/automl_v1/services/auto_ml/async_client.py index cea29911..adc27c99 100644 --- a/google/cloud/automl_v1/services/auto_ml/async_client.py +++ b/google/cloud/automl_v1/services/auto_ml/async_client.py @@ -19,14 +19,17 @@ from typing import Dict, Sequence, Tuple, Type, Union import pkg_resources -from google.api_core.client_options import ClientOptions # type: ignore -from google.api_core import exceptions as core_exceptions # type: ignore -from google.api_core import gapic_v1 # type: ignore -from google.api_core import retry as retries # type: ignore +from google.api_core.client_options import ClientOptions +from google.api_core import exceptions as core_exceptions +from google.api_core import gapic_v1 +from google.api_core import retry as retries from google.auth import credentials as ga_credentials # type: ignore from google.oauth2 import service_account # type: ignore -OptionalRetry = Union[retries.Retry, object] +try: + OptionalRetry = Union[retries.Retry, gapic_v1.method._MethodDefault] +except AttributeError: # pragma: NO COVER + OptionalRetry = Union[retries.Retry, object] # type: ignore from google.api_core import operation # type: ignore from google.api_core import operation_async # type: ignore @@ -70,7 +73,7 @@ class AutoMlAsyncClient: Currently the only supported ``location_id`` is "us-central1". On any input that is documented to expect a string parameter in - snake_case or kebab-case, either of those cases is accepted. + snake_case or dash-case, either of those cases is accepted. """ _client: AutoMlClient @@ -1408,7 +1411,6 @@ async def deploy_model( r"""Deploys a model. If a model is already deployed, deploying it with the same parameters has no effect. Deploying with different parametrs (as e.g. changing - [node_number][google.cloud.automl.v1p1beta.ImageObjectDetectionModelDeploymentMetadata.node_number]) will reset the deployment state without pausing the model's availability. diff --git a/google/cloud/automl_v1/services/auto_ml/client.py b/google/cloud/automl_v1/services/auto_ml/client.py index 6ca00fc8..8fdeecdd 100644 --- a/google/cloud/automl_v1/services/auto_ml/client.py +++ b/google/cloud/automl_v1/services/auto_ml/client.py @@ -14,23 +14,25 @@ # limitations under the License. # from collections import OrderedDict -from distutils import util import os import re from typing import Dict, Optional, Sequence, Tuple, Type, Union import pkg_resources -from google.api_core import client_options as client_options_lib # type: ignore -from google.api_core import exceptions as core_exceptions # type: ignore -from google.api_core import gapic_v1 # type: ignore -from google.api_core import retry as retries # type: ignore +from google.api_core import client_options as client_options_lib +from google.api_core import exceptions as core_exceptions +from google.api_core import gapic_v1 +from google.api_core import retry as retries from google.auth import credentials as ga_credentials # type: ignore from google.auth.transport import mtls # type: ignore from google.auth.transport.grpc import SslCredentials # type: ignore from google.auth.exceptions import MutualTLSChannelError # type: ignore from google.oauth2 import service_account # type: ignore -OptionalRetry = Union[retries.Retry, object] +try: + OptionalRetry = Union[retries.Retry, gapic_v1.method._MethodDefault] +except AttributeError: # pragma: NO COVER + OptionalRetry = Union[retries.Retry, object] # type: ignore from google.api_core import operation # type: ignore from google.api_core import operation_async # type: ignore @@ -105,7 +107,7 @@ class AutoMlClient(metaclass=AutoMlClientMeta): Currently the only supported ``location_id`` is "us-central1". On any input that is documented to expect a string parameter in - snake_case or kebab-case, either of those cases is accepted. + snake_case or dash-case, either of those cases is accepted. """ @staticmethod @@ -374,8 +376,15 @@ def __init__( client_options = client_options_lib.ClientOptions() # Create SSL credentials for mutual TLS if needed. - use_client_cert = bool( - util.strtobool(os.getenv("GOOGLE_API_USE_CLIENT_CERTIFICATE", "false")) + if os.getenv("GOOGLE_API_USE_CLIENT_CERTIFICATE", "false") not in ( + "true", + "false", + ): + raise ValueError( + "Environment variable `GOOGLE_API_USE_CLIENT_CERTIFICATE` must be either `true` or `false`" + ) + use_client_cert = ( + os.getenv("GOOGLE_API_USE_CLIENT_CERTIFICATE", "false") == "true" ) client_cert_source_func = None @@ -1584,7 +1593,6 @@ def deploy_model( r"""Deploys a model. If a model is already deployed, deploying it with the same parameters has no effect. Deploying with different parametrs (as e.g. changing - [node_number][google.cloud.automl.v1p1beta.ImageObjectDetectionModelDeploymentMetadata.node_number]) will reset the deployment state without pausing the model's availability. diff --git a/google/cloud/automl_v1/services/auto_ml/transports/base.py b/google/cloud/automl_v1/services/auto_ml/transports/base.py index 57f0f0fc..d96b3823 100644 --- a/google/cloud/automl_v1/services/auto_ml/transports/base.py +++ b/google/cloud/automl_v1/services/auto_ml/transports/base.py @@ -18,11 +18,11 @@ import pkg_resources import google.auth # type: ignore -import google.api_core # type: ignore -from google.api_core import exceptions as core_exceptions # type: ignore -from google.api_core import gapic_v1 # type: ignore -from google.api_core import retry as retries # type: ignore -from google.api_core import operations_v1 # type: ignore +import google.api_core +from google.api_core import exceptions as core_exceptions +from google.api_core import gapic_v1 +from google.api_core import retry as retries +from google.api_core import operations_v1 from google.auth import credentials as ga_credentials # type: ignore from google.oauth2 import service_account # type: ignore @@ -107,7 +107,6 @@ def __init__( credentials, _ = google.auth.load_credentials_from_file( credentials_file, **scopes_kwargs, quota_project_id=quota_project_id ) - elif credentials is None: credentials, _ = google.auth.default( **scopes_kwargs, quota_project_id=quota_project_id diff --git a/google/cloud/automl_v1/services/auto_ml/transports/grpc.py b/google/cloud/automl_v1/services/auto_ml/transports/grpc.py index f1995874..6765f1db 100644 --- a/google/cloud/automl_v1/services/auto_ml/transports/grpc.py +++ b/google/cloud/automl_v1/services/auto_ml/transports/grpc.py @@ -16,9 +16,9 @@ import warnings from typing import Callable, Dict, Optional, Sequence, Tuple, Union -from google.api_core import grpc_helpers # type: ignore -from google.api_core import operations_v1 # type: ignore -from google.api_core import gapic_v1 # type: ignore +from google.api_core import grpc_helpers +from google.api_core import operations_v1 +from google.api_core import gapic_v1 import google.auth # type: ignore from google.auth import credentials as ga_credentials # type: ignore from google.auth.transport.grpc import SslCredentials # type: ignore @@ -53,7 +53,7 @@ class AutoMlGrpcTransport(AutoMlTransport): Currently the only supported ``location_id`` is "us-central1". On any input that is documented to expect a string parameter in - snake_case or kebab-case, either of those cases is accepted. + snake_case or dash-case, either of those cases is accepted. This class defines the same methods as the primary client, so the primary client can load the underlying transport implementation @@ -626,7 +626,6 @@ def deploy_model( Deploys a model. If a model is already deployed, deploying it with the same parameters has no effect. Deploying with different parametrs (as e.g. changing - [node_number][google.cloud.automl.v1p1beta.ImageObjectDetectionModelDeploymentMetadata.node_number]) will reset the deployment state without pausing the model's availability. diff --git a/google/cloud/automl_v1/services/auto_ml/transports/grpc_asyncio.py b/google/cloud/automl_v1/services/auto_ml/transports/grpc_asyncio.py index 38c244e4..f5644c10 100644 --- a/google/cloud/automl_v1/services/auto_ml/transports/grpc_asyncio.py +++ b/google/cloud/automl_v1/services/auto_ml/transports/grpc_asyncio.py @@ -16,9 +16,9 @@ import warnings from typing import Awaitable, Callable, Dict, Optional, Sequence, Tuple, Union -from google.api_core import gapic_v1 # type: ignore -from google.api_core import grpc_helpers_async # type: ignore -from google.api_core import operations_v1 # type: ignore +from google.api_core import gapic_v1 +from google.api_core import grpc_helpers_async +from google.api_core import operations_v1 from google.auth import credentials as ga_credentials # type: ignore from google.auth.transport.grpc import SslCredentials # type: ignore @@ -54,7 +54,7 @@ class AutoMlGrpcAsyncIOTransport(AutoMlTransport): Currently the only supported ``location_id`` is "us-central1". On any input that is documented to expect a string parameter in - snake_case or kebab-case, either of those cases is accepted. + snake_case or dash-case, either of those cases is accepted. This class defines the same methods as the primary client, so the primary client can load the underlying transport implementation @@ -638,7 +638,6 @@ def deploy_model( Deploys a model. If a model is already deployed, deploying it with the same parameters has no effect. Deploying with different parametrs (as e.g. changing - [node_number][google.cloud.automl.v1p1beta.ImageObjectDetectionModelDeploymentMetadata.node_number]) will reset the deployment state without pausing the model's availability. diff --git a/google/cloud/automl_v1/services/prediction_service/async_client.py b/google/cloud/automl_v1/services/prediction_service/async_client.py index c376485c..e2eeb0f0 100644 --- a/google/cloud/automl_v1/services/prediction_service/async_client.py +++ b/google/cloud/automl_v1/services/prediction_service/async_client.py @@ -19,14 +19,17 @@ from typing import Dict, Sequence, Tuple, Type, Union import pkg_resources -from google.api_core.client_options import ClientOptions # type: ignore -from google.api_core import exceptions as core_exceptions # type: ignore -from google.api_core import gapic_v1 # type: ignore -from google.api_core import retry as retries # type: ignore +from google.api_core.client_options import ClientOptions +from google.api_core import exceptions as core_exceptions +from google.api_core import gapic_v1 +from google.api_core import retry as retries from google.auth import credentials as ga_credentials # type: ignore from google.oauth2 import service_account # type: ignore -OptionalRetry = Union[retries.Retry, object] +try: + OptionalRetry = Union[retries.Retry, gapic_v1.method._MethodDefault] +except AttributeError: # pragma: NO COVER + OptionalRetry = Union[retries.Retry, object] # type: ignore from google.api_core import operation # type: ignore from google.api_core import operation_async # type: ignore @@ -44,7 +47,7 @@ class PredictionServiceAsyncClient: """AutoML Prediction API. On any input that is documented to expect a string parameter in - snake_case or kebab-case, either of those cases is accepted. + snake_case or dash-case, either of those cases is accepted. """ _client: PredictionServiceClient @@ -267,7 +270,6 @@ async def predict( AutoML Tables ``feature_importance`` : (boolean) Whether - [feature_importance][google.cloud.automl.v1.TablesModelColumnInfo.feature_importance] is populated in the returned list of [TablesAnnotation][google.cloud.automl.v1.TablesAnnotation] diff --git a/google/cloud/automl_v1/services/prediction_service/client.py b/google/cloud/automl_v1/services/prediction_service/client.py index be8b4b4d..22de25cd 100644 --- a/google/cloud/automl_v1/services/prediction_service/client.py +++ b/google/cloud/automl_v1/services/prediction_service/client.py @@ -14,23 +14,25 @@ # limitations under the License. # from collections import OrderedDict -from distutils import util import os import re from typing import Dict, Optional, Sequence, Tuple, Type, Union import pkg_resources -from google.api_core import client_options as client_options_lib # type: ignore -from google.api_core import exceptions as core_exceptions # type: ignore -from google.api_core import gapic_v1 # type: ignore -from google.api_core import retry as retries # type: ignore +from google.api_core import client_options as client_options_lib +from google.api_core import exceptions as core_exceptions +from google.api_core import gapic_v1 +from google.api_core import retry as retries from google.auth import credentials as ga_credentials # type: ignore from google.auth.transport import mtls # type: ignore from google.auth.transport.grpc import SslCredentials # type: ignore from google.auth.exceptions import MutualTLSChannelError # type: ignore from google.oauth2 import service_account # type: ignore -OptionalRetry = Union[retries.Retry, object] +try: + OptionalRetry = Union[retries.Retry, gapic_v1.method._MethodDefault] +except AttributeError: # pragma: NO COVER + OptionalRetry = Union[retries.Retry, object] # type: ignore from google.api_core import operation # type: ignore from google.api_core import operation_async # type: ignore @@ -83,7 +85,7 @@ class PredictionServiceClient(metaclass=PredictionServiceClientMeta): """AutoML Prediction API. On any input that is documented to expect a string parameter in - snake_case or kebab-case, either of those cases is accepted. + snake_case or dash-case, either of those cases is accepted. """ @staticmethod @@ -294,8 +296,15 @@ def __init__( client_options = client_options_lib.ClientOptions() # Create SSL credentials for mutual TLS if needed. - use_client_cert = bool( - util.strtobool(os.getenv("GOOGLE_API_USE_CLIENT_CERTIFICATE", "false")) + if os.getenv("GOOGLE_API_USE_CLIENT_CERTIFICATE", "false") not in ( + "true", + "false", + ): + raise ValueError( + "Environment variable `GOOGLE_API_USE_CLIENT_CERTIFICATE` must be either `true` or `false`" + ) + use_client_cert = ( + os.getenv("GOOGLE_API_USE_CLIENT_CERTIFICATE", "false") == "true" ) client_cert_source_func = None @@ -455,7 +464,6 @@ def predict( AutoML Tables ``feature_importance`` : (boolean) Whether - [feature_importance][google.cloud.automl.v1.TablesModelColumnInfo.feature_importance] is populated in the returned list of [TablesAnnotation][google.cloud.automl.v1.TablesAnnotation] diff --git a/google/cloud/automl_v1/services/prediction_service/transports/base.py b/google/cloud/automl_v1/services/prediction_service/transports/base.py index 486a0cdb..7470d7e9 100644 --- a/google/cloud/automl_v1/services/prediction_service/transports/base.py +++ b/google/cloud/automl_v1/services/prediction_service/transports/base.py @@ -18,11 +18,11 @@ import pkg_resources import google.auth # type: ignore -import google.api_core # type: ignore -from google.api_core import exceptions as core_exceptions # type: ignore -from google.api_core import gapic_v1 # type: ignore -from google.api_core import retry as retries # type: ignore -from google.api_core import operations_v1 # type: ignore +import google.api_core +from google.api_core import exceptions as core_exceptions +from google.api_core import gapic_v1 +from google.api_core import retry as retries +from google.api_core import operations_v1 from google.auth import credentials as ga_credentials # type: ignore from google.oauth2 import service_account # type: ignore @@ -101,7 +101,6 @@ def __init__( credentials, _ = google.auth.load_credentials_from_file( credentials_file, **scopes_kwargs, quota_project_id=quota_project_id ) - elif credentials is None: credentials, _ = google.auth.default( **scopes_kwargs, quota_project_id=quota_project_id diff --git a/google/cloud/automl_v1/services/prediction_service/transports/grpc.py b/google/cloud/automl_v1/services/prediction_service/transports/grpc.py index a1ba6ec4..ec174da7 100644 --- a/google/cloud/automl_v1/services/prediction_service/transports/grpc.py +++ b/google/cloud/automl_v1/services/prediction_service/transports/grpc.py @@ -16,9 +16,9 @@ import warnings from typing import Callable, Dict, Optional, Sequence, Tuple, Union -from google.api_core import grpc_helpers # type: ignore -from google.api_core import operations_v1 # type: ignore -from google.api_core import gapic_v1 # type: ignore +from google.api_core import grpc_helpers +from google.api_core import operations_v1 +from google.api_core import gapic_v1 import google.auth # type: ignore from google.auth import credentials as ga_credentials # type: ignore from google.auth.transport.grpc import SslCredentials # type: ignore @@ -36,7 +36,7 @@ class PredictionServiceGrpcTransport(PredictionServiceTransport): AutoML Prediction API. On any input that is documented to expect a string parameter in - snake_case or kebab-case, either of those cases is accepted. + snake_case or dash-case, either of those cases is accepted. This class defines the same methods as the primary client, so the primary client can load the underlying transport implementation diff --git a/google/cloud/automl_v1/services/prediction_service/transports/grpc_asyncio.py b/google/cloud/automl_v1/services/prediction_service/transports/grpc_asyncio.py index 8549d7a9..cca25f11 100644 --- a/google/cloud/automl_v1/services/prediction_service/transports/grpc_asyncio.py +++ b/google/cloud/automl_v1/services/prediction_service/transports/grpc_asyncio.py @@ -16,9 +16,9 @@ import warnings from typing import Awaitable, Callable, Dict, Optional, Sequence, Tuple, Union -from google.api_core import gapic_v1 # type: ignore -from google.api_core import grpc_helpers_async # type: ignore -from google.api_core import operations_v1 # type: ignore +from google.api_core import gapic_v1 +from google.api_core import grpc_helpers_async +from google.api_core import operations_v1 from google.auth import credentials as ga_credentials # type: ignore from google.auth.transport.grpc import SslCredentials # type: ignore @@ -37,7 +37,7 @@ class PredictionServiceGrpcAsyncIOTransport(PredictionServiceTransport): AutoML Prediction API. On any input that is documented to expect a string parameter in - snake_case or kebab-case, either of those cases is accepted. + snake_case or dash-case, either of those cases is accepted. This class defines the same methods as the primary client, so the primary client can load the underlying transport implementation diff --git a/google/cloud/automl_v1/types/annotation_payload.py b/google/cloud/automl_v1/types/annotation_payload.py index 74b63c72..56f7401a 100644 --- a/google/cloud/automl_v1/types/annotation_payload.py +++ b/google/cloud/automl_v1/types/annotation_payload.py @@ -40,20 +40,25 @@ class AnnotationPayload(proto.Message): Attributes: translation (google.cloud.automl_v1.types.TranslationAnnotation): Annotation details for translation. + This field is a member of `oneof`_ ``detail``. classification (google.cloud.automl_v1.types.ClassificationAnnotation): Annotation details for content or image classification. + This field is a member of `oneof`_ ``detail``. image_object_detection (google.cloud.automl_v1.types.ImageObjectDetectionAnnotation): Annotation details for image object detection. + This field is a member of `oneof`_ ``detail``. text_extraction (google.cloud.automl_v1.types.TextExtractionAnnotation): Annotation details for text extraction. + This field is a member of `oneof`_ ``detail``. text_sentiment (google.cloud.automl_v1.types.TextSentimentAnnotation): Annotation details for text sentiment. + This field is a member of `oneof`_ ``detail``. annotation_spec_id (str): Output only . The resource ID of the diff --git a/google/cloud/automl_v1/types/annotation_spec.py b/google/cloud/automl_v1/types/annotation_spec.py index 5bcbcff3..05953b96 100644 --- a/google/cloud/automl_v1/types/annotation_spec.py +++ b/google/cloud/automl_v1/types/annotation_spec.py @@ -27,7 +27,6 @@ class AnnotationSpec(proto.Message): Attributes: name (str): Output only. Resource name of the annotation spec. Form: - 'projects/{project_id}/locations/{location_id}/datasets/{dataset_id}/annotationSpecs/{annotation_spec_id}' display_name (str): Required. The name of the annotation spec to show in the diff --git a/google/cloud/automl_v1/types/classification.py b/google/cloud/automl_v1/types/classification.py index 40202f16..2103966d 100644 --- a/google/cloud/automl_v1/types/classification.py +++ b/google/cloud/automl_v1/types/classification.py @@ -169,7 +169,6 @@ class ConfusionMatrix(proto.Message): annotation_spec_id (Sequence[str]): Output only. IDs of the annotation specs used in the confusion matrix. For Tables CLASSIFICATION - [prediction_type][google.cloud.automl.v1p1beta.TablesModelMetadata.prediction_type] only list of [annotation_spec_display_name-s][] is populated. @@ -177,7 +176,6 @@ class ConfusionMatrix(proto.Message): Output only. Display name of the annotation specs used in the confusion matrix, as they were at the moment of the evaluation. For Tables CLASSIFICATION - [prediction_type-s][google.cloud.automl.v1p1beta.TablesModelMetadata.prediction_type], distinct values of the target column at the moment of the model evaluation are populated here. diff --git a/google/cloud/automl_v1/types/data_items.py b/google/cloud/automl_v1/types/data_items.py index 8aaabc7a..041552e4 100644 --- a/google/cloud/automl_v1/types/data_items.py +++ b/google/cloud/automl_v1/types/data_items.py @@ -44,6 +44,7 @@ class Image(proto.Message): Image content represented as a stream of bytes. Note: As with all ``bytes`` fields, protobuffers use a pure binary representation, whereas JSON representations use base64. + This field is a member of `oneof`_ ``data``. thumbnail_uri (str): Output only. HTTP URI to the thumbnail image. @@ -138,7 +139,6 @@ class Layout(proto.Message): The position of the [text_segment][google.cloud.automl.v1.Document.Layout.text_segment] in the page. Contains exactly 4 - [normalized_vertices][google.cloud.automl.v1p1beta.BoundingPoly.normalized_vertices] and they are connected by edges in the order provided, which will represent a rectangle parallel to the frame. The @@ -199,12 +199,15 @@ class ExamplePayload(proto.Message): Attributes: image (google.cloud.automl_v1.types.Image): Example image. + This field is a member of `oneof`_ ``payload``. text_snippet (google.cloud.automl_v1.types.TextSnippet): Example text. + This field is a member of `oneof`_ ``payload``. document (google.cloud.automl_v1.types.Document): Example document. + This field is a member of `oneof`_ ``payload``. """ diff --git a/google/cloud/automl_v1/types/dataset.py b/google/cloud/automl_v1/types/dataset.py index fcca1cd2..2dbb31ab 100644 --- a/google/cloud/automl_v1/types/dataset.py +++ b/google/cloud/automl_v1/types/dataset.py @@ -39,26 +39,32 @@ class Dataset(proto.Message): Attributes: translation_dataset_metadata (google.cloud.automl_v1.types.TranslationDatasetMetadata): Metadata for a dataset used for translation. + This field is a member of `oneof`_ ``dataset_metadata``. image_classification_dataset_metadata (google.cloud.automl_v1.types.ImageClassificationDatasetMetadata): Metadata for a dataset used for image classification. + This field is a member of `oneof`_ ``dataset_metadata``. text_classification_dataset_metadata (google.cloud.automl_v1.types.TextClassificationDatasetMetadata): Metadata for a dataset used for text classification. + This field is a member of `oneof`_ ``dataset_metadata``. image_object_detection_dataset_metadata (google.cloud.automl_v1.types.ImageObjectDetectionDatasetMetadata): Metadata for a dataset used for image object detection. + This field is a member of `oneof`_ ``dataset_metadata``. text_extraction_dataset_metadata (google.cloud.automl_v1.types.TextExtractionDatasetMetadata): Metadata for a dataset used for text extraction. + This field is a member of `oneof`_ ``dataset_metadata``. text_sentiment_dataset_metadata (google.cloud.automl_v1.types.TextSentimentDatasetMetadata): Metadata for a dataset used for text sentiment. + This field is a member of `oneof`_ ``dataset_metadata``. name (str): Output only. The resource name of the dataset. Form: diff --git a/google/cloud/automl_v1/types/image.py b/google/cloud/automl_v1/types/image.py index 129cb5d7..e5d1e151 100644 --- a/google/cloud/automl_v1/types/image.py +++ b/google/cloud/automl_v1/types/image.py @@ -61,13 +61,13 @@ class ImageClassificationModelMetadata(proto.Message): ``location`` as the new model to create, and have the same ``model_type``. train_budget_milli_node_hours (int): - The train budget of creating this model, expressed in milli - node hours i.e. 1,000 value in this field means 1 node hour. - The actual ``train_cost`` will be equal or less than this - value. If further model training ceases to provide any - improvements, it will stop without using full budget and the - stop_reason will be ``MODEL_CONVERGED``. Note, node_hour = - actual_hour \* number_of_nodes_invovled. For model type + Optional. The train budget of creating this model, expressed + in milli node hours i.e. 1,000 value in this field means 1 + node hour. The actual ``train_cost`` will be equal or less + than this value. If further model training ceases to provide + any improvements, it will stop without using full budget and + the stop_reason will be ``MODEL_CONVERGED``. Note, node_hour + = actual_hour \* number_of_nodes_invovled. For model type ``cloud``\ (default), the train budget must be between 8,000 and 800,000 milli node hours, inclusive. The default value is 192, 000 which represents one day in wall time. For model @@ -199,13 +199,13 @@ class ImageObjectDetectionModelMetadata(proto.Message): Output only. The reason that this create model operation stopped, e.g. ``BUDGET_REACHED``, ``MODEL_CONVERGED``. train_budget_milli_node_hours (int): - The train budget of creating this model, expressed in milli - node hours i.e. 1,000 value in this field means 1 node hour. - The actual ``train_cost`` will be equal or less than this - value. If further model training ceases to provide any - improvements, it will stop without using full budget and the - stop_reason will be ``MODEL_CONVERGED``. Note, node_hour = - actual_hour \* number_of_nodes_invovled. For model type + Optional. The train budget of creating this model, expressed + in milli node hours i.e. 1,000 value in this field means 1 + node hour. The actual ``train_cost`` will be equal or less + than this value. If further model training ceases to provide + any improvements, it will stop without using full budget and + the stop_reason will be ``MODEL_CONVERGED``. Note, node_hour + = actual_hour \* number_of_nodes_invovled. For model type ``cloud-high-accuracy-1``\ (default) and ``cloud-low-latency-1``, the train budget must be between 20,000 and 900,000 milli node hours, inclusive. The default @@ -242,7 +242,6 @@ class ImageClassificationModelDeploymentMetadata(proto.Message): Input only. The number of nodes to deploy the model on. A node is an abstraction of a machine resource, which can handle online prediction QPS as given in the model's - [node_qps][google.cloud.automl.v1.ImageClassificationModelMetadata.node_qps]. Must be between 1 and 100, inclusive on both ends. """ @@ -258,7 +257,6 @@ class ImageObjectDetectionModelDeploymentMetadata(proto.Message): Input only. The number of nodes to deploy the model on. A node is an abstraction of a machine resource, which can handle online prediction QPS as given in the model's - [qps_per_node][google.cloud.automl.v1.ImageObjectDetectionModelMetadata.qps_per_node]. Must be between 1 and 100, inclusive on both ends. """ diff --git a/google/cloud/automl_v1/types/io.py b/google/cloud/automl_v1/types/io.py index 4c01feb4..171d5484 100644 --- a/google/cloud/automl_v1/types/io.py +++ b/google/cloud/automl_v1/types/io.py @@ -613,7 +613,6 @@ class InputConfig(proto.Message): [gcs_source][google.cloud.automl.v1.InputConfig.gcs_source] or [bigquery_source][google.cloud.automl.v1.InputConfig.bigquery_source]. All input is concatenated into a single - [primary_table_spec_id][google.cloud.automl.v1.TablesDatasetMetadata.primary_table_spec_id] **For gcs_source:** @@ -632,9 +631,7 @@ class InputConfig(proto.Message): 
         "Id","First Name","Last Name","Dob","Addresses"
-
         "1","John","Doe","1968-01-22","[{"status":"current","address":"123_First_Avenue","city":"Seattle","state":"WA","zip":"11111","numberOfYears":"1"},{"status":"previous","address":"456_Main_Street","city":"Portland","state":"OR","zip":"22222","numberOfYears":"5"}]"
-
         "2","Jane","Doe","1980-10-16","[{"status":"current","address":"789_Any_Avenue","city":"Albany","state":"NY","zip":"33333","numberOfYears":"2"},{"status":"previous","address":"321_Main_Street","city":"Hoboken","state":"NJ","zip":"44444","numberOfYears":"3"}]}
@@ -721,6 +718,7 @@ class InputConfig(proto.Message): ``gcs_source`` points to a CSV file with a structure described in [InputConfig][google.cloud.automl.v1.InputConfig]. + This field is a member of `oneof`_ ``source``. params (Sequence[google.cloud.automl_v1.types.InputConfig.ParamsEntry]): Additional domain-specific parameters describing the @@ -1011,7 +1009,6 @@ class BatchPredictInputConfig(proto.Message): contain values for the corresponding columns. The column names must contain the model's - [input_feature_column_specs'][google.cloud.automl.v1.TablesModelMetadata.input_feature_column_specs] [display_name-s][google.cloud.automl.v1.ColumnSpec.display_name] (order doesn't matter). The columns corresponding to the model's @@ -1025,9 +1022,7 @@ class BatchPredictInputConfig(proto.Message): 
         "First Name","Last Name","Dob","Addresses"
-
         "John","Doe","1968-01-22","[{"status":"current","address":"123_First_Avenue","city":"Seattle","state":"WA","zip":"11111","numberOfYears":"1"},{"status":"previous","address":"456_Main_Street","city":"Portland","state":"OR","zip":"22222","numberOfYears":"5"}]"
-
         "Jane","Doe","1980-10-16","[{"status":"current","address":"789_Any_Avenue","city":"Albany","state":"NY","zip":"33333","numberOfYears":"2"},{"status":"previous","address":"321_Main_Street","city":"Hoboken","state":"NJ","zip":"44444","numberOfYears":"3"}]}
@@ -1037,7 +1032,6 @@ class BatchPredictInputConfig(proto.Message): table must be 100GB or smaller. The column names must contain the model's - [input_feature_column_specs'][google.cloud.automl.v1.TablesModelMetadata.input_feature_column_specs] [display_name-s][google.cloud.automl.v1.ColumnSpec.display_name] (order doesn't matter). The columns corresponding to the model's @@ -1082,6 +1076,7 @@ class BatchPredictInputConfig(proto.Message): gcs_source (google.cloud.automl_v1.types.GcsSource): Required. The Google Cloud Storage location for the input content. + This field is a member of `oneof`_ ``source``. """ @@ -1117,23 +1112,21 @@ class OutputConfig(proto.Message): - For Tables: Output depends on whether the dataset was imported from Google Cloud Storage or BigQuery. Google Cloud Storage case: - - [gcs_destination][google.cloud.automl.v1p1beta.OutputConfig.gcs_destination] - must be set. Exported are CSV file(s) ``tables_1.csv``, - ``tables_2.csv``,...,\ ``tables_N.csv`` with each having as header - line the table's column names, and all other lines contain values - for the header columns. BigQuery case: - - [bigquery_destination][google.cloud.automl.v1p1beta.OutputConfig.bigquery_destination] - pointing to a BigQuery project must be set. In the given project a - new dataset will be created with name - - ``export_data__`` - where will be made BigQuery-dataset-name compatible (e.g. most - special characters will become underscores), and timestamp will be - in YYYY_MM_DDThh_mm_ss_sssZ "based on ISO-8601" format. In that - dataset a new table called ``primary_table`` will be created, and - filled with precisely the same data as this obtained on import. + [gcs_destination][google.cloud.automl.v1p1beta.OutputConfig.gcs_destination] + must be set. Exported are CSV file(s) ``tables_1.csv``, + ``tables_2.csv``,...,\ ``tables_N.csv`` with each having as + header line the table's column names, and all other lines + contain values for the header columns. BigQuery case: + [bigquery_destination][google.cloud.automl.v1p1beta.OutputConfig.bigquery_destination] + pointing to a BigQuery project must be set. In the given + project a new dataset will be created with name + ``export_data__`` + where will be made BigQuery-dataset-name compatible (e.g. most + special characters will become underscores), and timestamp + will be in YYYY_MM_DDThh_mm_ss_sssZ "based on ISO-8601" + format. In that dataset a new table called ``primary_table`` + will be created, and filled with precisely the same data as + this obtained on import. .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields @@ -1147,6 +1140,7 @@ class OutputConfig(proto.Message): export_data-- where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format. All export output will be written into that directory. + This field is a member of `oneof`_ ``destination``. """ @@ -1159,7 +1153,6 @@ class BatchPredictOutputConfig(proto.Message): r"""Output configuration for BatchPredict Action. As destination the - [gcs_destination][google.cloud.automl.v1.BatchPredictOutputConfig.gcs_destination] must be set unless specified otherwise for a domain. If gcs_destination is set then in the given directory a new directory @@ -1184,10 +1177,8 @@ class BatchPredictOutputConfig(proto.Message): predictions). These files will have a JSON representation of a proto that wraps the same "ID" : "" but here followed by exactly one - - [``google.rpc.Status``](https: - //github.com/googleapis/googleapis/blob/master/google/rpc/status.proto) - containing only ``code`` and ``message``\ fields. + ```google.rpc.Status`` `__ + containing only ``code`` and ``message``\ fields. - For Image Object Detection: In the created directory files ``image_object_detection_1.jsonl``, @@ -1206,10 +1197,8 @@ class BatchPredictOutputConfig(proto.Message): predictions). These files will have a JSON representation of a proto that wraps the same "ID" : "" but here followed by exactly one - - [``google.rpc.Status``](https: - //github.com/googleapis/googleapis/blob/master/google/rpc/status.proto) - containing only ``code`` and ``message``\ fields. + ```google.rpc.Status`` `__ + containing only ``code`` and ``message``\ fields. - For Video Classification: In the created directory a video_classification.csv file, and a .JSON file per each video @@ -1219,27 +1208,25 @@ class BatchPredictOutputConfig(proto.Message): :: The format of video_classification.csv is: - - GCS_FILE_PATH,TIME_SEGMENT_START,TIME_SEGMENT_END,JSON_FILE_NAME,STATUS - where: GCS_FILE_PATH,TIME_SEGMENT_START,TIME_SEGMENT_END = matches 1 - to 1 the prediction input lines (i.e. video_classification.csv has - precisely the same number of lines as the prediction input had.) - JSON_FILE_NAME = Name of .JSON file in the output directory, which - contains prediction responses for the video time segment. STATUS = - "OK" if prediction completed successfully, or an error code with - message otherwise. If STATUS is not "OK" then the .JSON file for - that line may not exist or be empty. - - :: - - Each .JSON file, assuming STATUS is "OK", will contain a list of - AnnotationPayload protos in JSON format, which are the predictions - for the video time segment the file is assigned to in the - video_classification.csv. All AnnotationPayload protos will have - video_classification field set, and will be sorted by - video_classification.type field (note that the returned types are - governed by `classifaction_types` parameter in - [PredictService.BatchPredictRequest.params][]). + GCS_FILE_PATH,TIME_SEGMENT_START,TIME_SEGMENT_END,JSON_FILE_NAME,STATUS + where: + GCS_FILE_PATH,TIME_SEGMENT_START,TIME_SEGMENT_END = matches 1 to 1 + the prediction input lines (i.e. video_classification.csv has + precisely the same number of lines as the prediction input had.) + JSON_FILE_NAME = Name of .JSON file in the output directory, which + contains prediction responses for the video time segment. + STATUS = "OK" if prediction completed successfully, or an error code + with message otherwise. If STATUS is not "OK" then the .JSON file + for that line may not exist or be empty. + + Each .JSON file, assuming STATUS is "OK", will contain a list of + AnnotationPayload protos in JSON format, which are the predictions + for the video time segment the file is assigned to in the + video_classification.csv. All AnnotationPayload protos will have + video_classification field set, and will be sorted by + video_classification.type field (note that the returned types are + governed by `classifaction_types` parameter in + [PredictService.BatchPredictRequest.params][]). - For Video Object Tracking: In the created directory a video_object_tracking.csv file will be created, and multiple @@ -1251,24 +1238,22 @@ class BatchPredictOutputConfig(proto.Message): :: The format of video_object_tracking.csv is: - - GCS_FILE_PATH,TIME_SEGMENT_START,TIME_SEGMENT_END,JSON_FILE_NAME,STATUS - where: GCS_FILE_PATH,TIME_SEGMENT_START,TIME_SEGMENT_END = matches 1 - to 1 the prediction input lines (i.e. video_object_tracking.csv has - precisely the same number of lines as the prediction input had.) - JSON_FILE_NAME = Name of .JSON file in the output directory, which - contains prediction responses for the video time segment. STATUS = - "OK" if prediction completed successfully, or an error code with - message otherwise. If STATUS is not "OK" then the .JSON file for - that line may not exist or be empty. - - :: - - Each .JSON file, assuming STATUS is "OK", will contain a list of - AnnotationPayload protos in JSON format, which are the predictions - for each frame of the video time segment the file is assigned to in - video_object_tracking.csv. All AnnotationPayload protos will have - video_object_tracking field set. + GCS_FILE_PATH,TIME_SEGMENT_START,TIME_SEGMENT_END,JSON_FILE_NAME,STATUS + where: + GCS_FILE_PATH,TIME_SEGMENT_START,TIME_SEGMENT_END = matches 1 to 1 + the prediction input lines (i.e. video_object_tracking.csv has + precisely the same number of lines as the prediction input had.) + JSON_FILE_NAME = Name of .JSON file in the output directory, which + contains prediction responses for the video time segment. + STATUS = "OK" if prediction completed successfully, or an error + code with message otherwise. If STATUS is not "OK" then the .JSON + file for that line may not exist or be empty. + + Each .JSON file, assuming STATUS is "OK", will contain a list of + AnnotationPayload protos in JSON format, which are the predictions + for each frame of the video time segment the file is assigned to in + video_object_tracking.csv. All AnnotationPayload protos will have + video_object_tracking field set. - For Text Classification: In the created directory files ``text_classification_1.jsonl``, @@ -1291,10 +1276,8 @@ class BatchPredictOutputConfig(proto.Message): `errors_N.jsonl` files will be created (N depends on total number of failed predictions). These files will have a JSON representation of a proto that wraps input file followed by exactly one - - [``google.rpc.Status``](https: - //github.com/googleapis/googleapis/blob/master/google/rpc/status.proto) - containing only ``code`` and ``message``. + [`google.rpc.Status`](https://github.com/googleapis/googleapis/blob/master/google/rpc/status.proto) + containing only `code` and `message`. - For Text Sentiment: In the created directory files ``text_sentiment_1.jsonl``, @@ -1317,10 +1300,8 @@ class BatchPredictOutputConfig(proto.Message): `errors_N.jsonl` files will be created (N depends on total number of failed predictions). These files will have a JSON representation of a proto that wraps input file followed by exactly one - - [``google.rpc.Status``](https: - //github.com/googleapis/googleapis/blob/master/google/rpc/status.proto) - containing only ``code`` and ``message``. + [`google.rpc.Status`](https://github.com/googleapis/googleapis/blob/master/google/rpc/status.proto) + containing only `code` and `message`. - For Text Extraction: In the created directory files ``text_extraction_1.jsonl``, @@ -1351,98 +1332,78 @@ class BatchPredictOutputConfig(proto.Message): will have a JSON representation of a proto that wraps either the "id" : "" (in case of inline) or the document proto (in case of document) but here followed by exactly one - - [``google.rpc.Status``](https: - //github.com/googleapis/googleapis/blob/master/google/rpc/status.proto) - containing only ``code`` and ``message``. + ```google.rpc.Status`` `__ + containing only ``code`` and ``message``. - For Tables: Output depends on whether - - [gcs_destination][google.cloud.automl.v1p1beta.BatchPredictOutputConfig.gcs_destination] - or - - [bigquery_destination][google.cloud.automl.v1p1beta.BatchPredictOutputConfig.bigquery_destination] - is set (either is allowed). Google Cloud Storage case: In the - created directory files ``tables_1.csv``, ``tables_2.csv``,..., - ``tables_N.csv`` will be created, where N may be 1, and depends on - the total number of the successfully predicted rows. For all - CLASSIFICATION - - [prediction_type-s][google.cloud.automl.v1p1beta.TablesModelMetadata.prediction_type]: - Each .csv file will contain a header, listing all columns' - - [display_name-s][google.cloud.automl.v1p1beta.ColumnSpec.display_name] - given on input followed by M target column names in the format of - - "<[target_column_specs][google.cloud.automl.v1p1beta.TablesModelMetadata.target_column_spec] - - [display_name][google.cloud.automl.v1p1beta.ColumnSpec.display_name]>\_\_score" - where M is the number of distinct target values, i.e. number of - distinct values in the target column of the table used to train the - model. Subsequent lines will contain the respective values of - successfully predicted rows, with the last, i.e. the target, columns - having the corresponding prediction - [scores][google.cloud.automl.v1p1beta.TablesAnnotation.score]. For - REGRESSION and FORECASTING - - [prediction_type-s][google.cloud.automl.v1p1beta.TablesModelMetadata.prediction_type]: - Each .csv file will contain a header, listing all columns' - [display_name-s][google.cloud.automl.v1p1beta.display_name] given on - input followed by the predicted target column with name in the - format of - - "predicted_<[target_column_specs][google.cloud.automl.v1p1beta.TablesModelMetadata.target_column_spec] - - [display_name][google.cloud.automl.v1p1beta.ColumnSpec.display_name]>" - Subsequent lines will contain the respective values of successfully - predicted rows, with the last, i.e. the target, column having the - predicted target value. If prediction for any rows failed, then an - additional ``errors_1.csv``, ``errors_2.csv``,..., ``errors_N.csv`` - will be created (N depends on total number of failed rows). These - files will have analogous format as ``tables_*.csv``, but always - with a single target column having - - [``google.rpc.Status``](https: - //github.com/googleapis/googleapis/blob/master/google/rpc/status.proto) - represented as a JSON string, and containing only ``code`` and - ``message``. BigQuery case: - - [bigquery_destination][google.cloud.automl.v1p1beta.OutputConfig.bigquery_destination] - pointing to a BigQuery project must be set. In the given project a - new dataset will be created with name - ``prediction__`` - where will be made BigQuery-dataset-name compatible (e.g. most - special characters will become underscores), and timestamp will be - in YYYY_MM_DDThh_mm_ss_sssZ "based on ISO-8601" format. In the - dataset two tables will be created, ``predictions``, and ``errors``. - The ``predictions`` table's column names will be the input columns' - - [display_name-s][google.cloud.automl.v1p1beta.ColumnSpec.display_name] - followed by the target column with name in the format of - - "predicted_<[target_column_specs][google.cloud.automl.v1p1beta.TablesModelMetadata.target_column_spec] - - [display_name][google.cloud.automl.v1p1beta.ColumnSpec.display_name]>" - The input feature columns will contain the respective values of - successfully predicted rows, with the target column having an ARRAY - of - - [AnnotationPayloads][google.cloud.automl.v1p1beta.AnnotationPayload], - represented as STRUCT-s, containing - [TablesAnnotation][google.cloud.automl.v1p1beta.TablesAnnotation]. - The ``errors`` table contains rows for which the prediction has - failed, it has analogous input columns while the target column name - is in the format of - - "errors_<[target_column_specs][google.cloud.automl.v1p1beta.TablesModelMetadata.target_column_spec] - - [display_name][google.cloud.automl.v1p1beta.ColumnSpec.display_name]>", - and as a value has - - [``google.rpc.Status``](https: - //github.com/googleapis/googleapis/blob/master/google/rpc/status.proto) - represented as a STRUCT, and containing only ``code`` and - ``message``. + [gcs_destination][google.cloud.automl.v1p1beta.BatchPredictOutputConfig.gcs_destination] + or + [bigquery_destination][google.cloud.automl.v1p1beta.BatchPredictOutputConfig.bigquery_destination] + is set (either is allowed). Google Cloud Storage case: In the + created directory files ``tables_1.csv``, ``tables_2.csv``,..., + ``tables_N.csv`` will be created, where N may be 1, and depends + on the total number of the successfully predicted rows. For all + CLASSIFICATION + [prediction_type-s][google.cloud.automl.v1p1beta.TablesModelMetadata.prediction_type]: + Each .csv file will contain a header, listing all columns' + [display_name-s][google.cloud.automl.v1p1beta.ColumnSpec.display_name] + given on input followed by M target column names in the format of + "<[target_column_specs][google.cloud.automl.v1p1beta.TablesModelMetadata.target_column_spec] + [display_name][google.cloud.automl.v1p1beta.ColumnSpec.display_name]>*\ score" + where M is the number of distinct target values, i.e. number of + distinct values in the target column of the table used to train + the model. Subsequent lines will contain the respective values of + successfully predicted rows, with the last, i.e. the target, + columns having the corresponding prediction + [scores][google.cloud.automl.v1p1beta.TablesAnnotation.score]. + For REGRESSION and FORECASTING + [prediction_type-s][google.cloud.automl.v1p1beta.TablesModelMetadata.prediction_type]: + Each .csv file will contain a header, listing all columns' + [display_name-s][google.cloud.automl.v1p1beta.display_name] given + on input followed by the predicted target column with name in the + format of + "predicted\ <[target_column_specs][google.cloud.automl.v1p1beta.TablesModelMetadata.target_column_spec] + [display_name][google.cloud.automl.v1p1beta.ColumnSpec.display_name]>" + Subsequent lines will contain the respective values of + successfully predicted rows, with the last, i.e. the target, + column having the predicted target value. If prediction for any + rows failed, then an additional ``errors_1.csv``, + ``errors_2.csv``,..., ``errors_N.csv`` will be created (N depends + on total number of failed rows). These files will have analogous + format as ``tables_*.csv``, but always with a single target + column + having*\ ```google.rpc.Status`` `__\ *represented + as a JSON string, and containing only ``code`` and ``message``. + BigQuery case: + [bigquery_destination][google.cloud.automl.v1p1beta.OutputConfig.bigquery_destination] + pointing to a BigQuery project must be set. In the given project + a new dataset will be created with name + ``prediction__`` + where will be made BigQuery-dataset-name compatible (e.g. most + special characters will become underscores), and timestamp will + be in YYYY_MM_DDThh_mm_ss_sssZ "based on ISO-8601" format. In the + dataset two tables will be created, ``predictions``, and + ``errors``. The ``predictions`` table's column names will be the + input columns' + [display_name-s][google.cloud.automl.v1p1beta.ColumnSpec.display_name] + followed by the target column with name in the format of + "predicted*\ <[target_column_specs][google.cloud.automl.v1p1beta.TablesModelMetadata.target_column_spec] + [display_name][google.cloud.automl.v1p1beta.ColumnSpec.display_name]>" + The input feature columns will contain the respective values of + successfully predicted rows, with the target column having an + ARRAY of + [AnnotationPayloads][google.cloud.automl.v1p1beta.AnnotationPayload], + represented as STRUCT-s, containing + [TablesAnnotation][google.cloud.automl.v1p1beta.TablesAnnotation]. + The ``errors`` table contains rows for which the prediction has + failed, it has analogous input columns while the target column + name is in the format of + "errors_<[target_column_specs][google.cloud.automl.v1p1beta.TablesModelMetadata.target_column_spec] + [display_name][google.cloud.automl.v1p1beta.ColumnSpec.display_name]>", + and as a value has + ```google.rpc.Status`` `__ + represented as a STRUCT, and containing only ``code`` and + ``message``. .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields @@ -1452,6 +1413,7 @@ class BatchPredictOutputConfig(proto.Message): Required. The Google Cloud Storage location of the directory where the output is to be written to. + This field is a member of `oneof`_ ``destination``. """ @@ -1477,6 +1439,7 @@ class ModelExportOutputConfig(proto.Message): YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format, will be created. Inside the model and any of its supporting files will be written. + This field is a member of `oneof`_ ``destination``. model_format (str): The format in which the model must be exported. The @@ -1513,10 +1476,8 @@ class ModelExportOutputConfig(proto.Message): - docker - Used for Docker containers. Use the params field to customize the container. The container is verified to work correctly on ubuntu 16.04 operating system. See more - at [containers - - quickstart](https: - //cloud.google.com/vision/automl/docs/containers-gcs-quickstart) + at `containers + quickstart `__ - core_ml - Used for iOS mobile devices. params (Sequence[google.cloud.automl_v1.types.ModelExportOutputConfig.ParamsEntry]): diff --git a/google/cloud/automl_v1/types/model.py b/google/cloud/automl_v1/types/model.py index 0bee0213..d451188f 100644 --- a/google/cloud/automl_v1/types/model.py +++ b/google/cloud/automl_v1/types/model.py @@ -37,21 +37,27 @@ class Model(proto.Message): Attributes: translation_model_metadata (google.cloud.automl_v1.types.TranslationModelMetadata): Metadata for translation models. + This field is a member of `oneof`_ ``model_metadata``. image_classification_model_metadata (google.cloud.automl_v1.types.ImageClassificationModelMetadata): Metadata for image classification models. + This field is a member of `oneof`_ ``model_metadata``. text_classification_model_metadata (google.cloud.automl_v1.types.TextClassificationModelMetadata): Metadata for text classification models. + This field is a member of `oneof`_ ``model_metadata``. image_object_detection_model_metadata (google.cloud.automl_v1.types.ImageObjectDetectionModelMetadata): Metadata for image object detection models. + This field is a member of `oneof`_ ``model_metadata``. text_extraction_model_metadata (google.cloud.automl_v1.types.TextExtractionModelMetadata): Metadata for text extraction models. + This field is a member of `oneof`_ ``model_metadata``. text_sentiment_model_metadata (google.cloud.automl_v1.types.TextSentimentModelMetadata): Metadata for text sentiment models. + This field is a member of `oneof`_ ``model_metadata``. name (str): Output only. Resource name of the model. Format: diff --git a/google/cloud/automl_v1/types/model_evaluation.py b/google/cloud/automl_v1/types/model_evaluation.py index db187bae..2b483a46 100644 --- a/google/cloud/automl_v1/types/model_evaluation.py +++ b/google/cloud/automl_v1/types/model_evaluation.py @@ -44,24 +44,28 @@ class ModelEvaluation(proto.Message): video and tables classification. Tables problem is considered a classification when the target column is CATEGORY DataType. + This field is a member of `oneof`_ ``metrics``. translation_evaluation_metrics (google.cloud.automl_v1.types.TranslationEvaluationMetrics): Model evaluation metrics for translation. + This field is a member of `oneof`_ ``metrics``. image_object_detection_evaluation_metrics (google.cloud.automl_v1.types.ImageObjectDetectionEvaluationMetrics): Model evaluation metrics for image object detection. + This field is a member of `oneof`_ ``metrics``. text_sentiment_evaluation_metrics (google.cloud.automl_v1.types.TextSentimentEvaluationMetrics): Evaluation metrics for text sentiment models. + This field is a member of `oneof`_ ``metrics``. text_extraction_evaluation_metrics (google.cloud.automl_v1.types.TextExtractionEvaluationMetrics): Evaluation metrics for text extraction models. + This field is a member of `oneof`_ ``metrics``. name (str): Output only. Resource name of the model evaluation. Format: - ``projects/{project_id}/locations/{location_id}/models/{model_id}/modelEvaluations/{model_evaluation_id}`` annotation_spec_id (str): Output only. The ID of the annotation spec that the model @@ -69,7 +73,6 @@ class ModelEvaluation(proto.Message): model evaluation. For Tables annotation specs in the dataset do not exist and this ID is always not set, but for CLASSIFICATION - [prediction_type-s][google.cloud.automl.v1.TablesModelMetadata.prediction_type] the [display_name][google.cloud.automl.v1.ModelEvaluation.display_name] @@ -82,7 +85,6 @@ class ModelEvaluation(proto.Message): trained from the same dataset, the values may differ, since display names could had been changed between the two model's trainings. For Tables CLASSIFICATION - [prediction_type-s][google.cloud.automl.v1.TablesModelMetadata.prediction_type] distinct values of the target column at the moment of the model evaluation are populated here. The display_name is @@ -99,7 +101,6 @@ class ModelEvaluation(proto.Message): examples used for evaluation. Otherwise, this is the count of examples that according to the ground truth were annotated by the - [annotation_spec_id][google.cloud.automl.v1.ModelEvaluation.annotation_spec_id]. """ diff --git a/google/cloud/automl_v1/types/operations.py b/google/cloud/automl_v1/types/operations.py index a18624d5..14dde266 100644 --- a/google/cloud/automl_v1/types/operations.py +++ b/google/cloud/automl_v1/types/operations.py @@ -51,30 +51,39 @@ class OperationMetadata(proto.Message): Attributes: delete_details (google.cloud.automl_v1.types.DeleteOperationMetadata): Details of a Delete operation. + This field is a member of `oneof`_ ``details``. deploy_model_details (google.cloud.automl_v1.types.DeployModelOperationMetadata): Details of a DeployModel operation. + This field is a member of `oneof`_ ``details``. undeploy_model_details (google.cloud.automl_v1.types.UndeployModelOperationMetadata): Details of an UndeployModel operation. + This field is a member of `oneof`_ ``details``. create_model_details (google.cloud.automl_v1.types.CreateModelOperationMetadata): Details of CreateModel operation. + This field is a member of `oneof`_ ``details``. create_dataset_details (google.cloud.automl_v1.types.CreateDatasetOperationMetadata): Details of CreateDataset operation. + This field is a member of `oneof`_ ``details``. import_data_details (google.cloud.automl_v1.types.ImportDataOperationMetadata): Details of ImportData operation. + This field is a member of `oneof`_ ``details``. batch_predict_details (google.cloud.automl_v1.types.BatchPredictOperationMetadata): Details of BatchPredict operation. + This field is a member of `oneof`_ ``details``. export_data_details (google.cloud.automl_v1.types.ExportDataOperationMetadata): Details of ExportData operation. + This field is a member of `oneof`_ ``details``. export_model_details (google.cloud.automl_v1.types.ExportModelOperationMetadata): Details of ExportModel operation. + This field is a member of `oneof`_ ``details``. progress_percent (int): Output only. Progress of operation. Range: [0, 100]. Not @@ -203,6 +212,7 @@ class ExportDataOutputInfo(proto.Message): The full path of the Google Cloud Storage directory created, into which the exported data is written. + This field is a member of `oneof`_ ``output_location``. """ @@ -227,7 +237,6 @@ class BatchPredictOperationMetadata(proto.Message): class BatchPredictOutputInfo(proto.Message): r"""Further describes this batch predict's output. Supplements - [BatchPredictOutputConfig][google.cloud.automl.v1.BatchPredictOutputConfig]. @@ -238,6 +247,7 @@ class BatchPredictOutputInfo(proto.Message): The full path of the Google Cloud Storage directory created, into which the prediction output is written. + This field is a member of `oneof`_ ``output_location``. """ diff --git a/google/cloud/automl_v1/types/prediction_service.py b/google/cloud/automl_v1/types/prediction_service.py index 30660c69..1a8de0e2 100644 --- a/google/cloud/automl_v1/types/prediction_service.py +++ b/google/cloud/automl_v1/types/prediction_service.py @@ -68,7 +68,6 @@ class PredictRequest(proto.Message): AutoML Tables ``feature_importance`` : (boolean) Whether - [feature_importance][google.cloud.automl.v1.TablesModelColumnInfo.feature_importance] is populated in the returned list of [TablesAnnotation][google.cloud.automl.v1.TablesAnnotation] diff --git a/google/cloud/automl_v1/types/service.py b/google/cloud/automl_v1/types/service.py index 0c72c544..fa115967 100644 --- a/google/cloud/automl_v1/types/service.py +++ b/google/cloud/automl_v1/types/service.py @@ -92,11 +92,11 @@ class ListDatasetsRequest(proto.Message): An expression for filtering the results of the request. - ``dataset_metadata`` - for existence of the case (e.g. - image_classification_dataset_metadata:*). Some examples - of using the filter are: + ``image_classification_dataset_metadata:*``). Some + examples of using the filter are: - ``translation_dataset_metadata:*`` --> The dataset has - translation_dataset_metadata. + ``translation_dataset_metadata``. page_size (int): Requested page size. Server may return fewer results than requested. If unspecified, server @@ -257,13 +257,13 @@ class ListModelsRequest(proto.Message): An expression for filtering the results of the request. - ``model_metadata`` - for existence of the case (e.g. - video_classification_model_metadata:*). + ``video_classification_model_metadata:*``). - ``dataset_id`` - for = or !=. Some examples of using the filter are: - ``image_classification_model_metadata:*`` --> The model - has image_classification_model_metadata. + has ``image_classification_model_metadata``. - ``dataset_id=5`` --> The model was created from a dataset with ID 5. @@ -352,10 +352,12 @@ class DeployModelRequest(proto.Message): image_object_detection_model_deployment_metadata (google.cloud.automl_v1.types.ImageObjectDetectionModelDeploymentMetadata): Model deployment metadata specific to Image Object Detection. + This field is a member of `oneof`_ ``model_deployment_metadata``. image_classification_model_deployment_metadata (google.cloud.automl_v1.types.ImageClassificationModelDeploymentMetadata): Model deployment metadata specific to Image Classification. + This field is a member of `oneof`_ ``model_deployment_metadata``. name (str): Required. Resource name of the model to diff --git a/google/cloud/automl_v1/types/text_extraction.py b/google/cloud/automl_v1/types/text_extraction.py index 11243879..606f8050 100644 --- a/google/cloud/automl_v1/types/text_extraction.py +++ b/google/cloud/automl_v1/types/text_extraction.py @@ -34,6 +34,7 @@ class TextExtractionAnnotation(proto.Message): An entity annotation will set this, which is the part of the original text to which the annotation pertains. + This field is a member of `oneof`_ ``annotation``. score (float): Output only. A confidence estimate between diff --git a/google/cloud/automl_v1beta1/services/auto_ml/async_client.py b/google/cloud/automl_v1beta1/services/auto_ml/async_client.py index c19a86bd..08465444 100644 --- a/google/cloud/automl_v1beta1/services/auto_ml/async_client.py +++ b/google/cloud/automl_v1beta1/services/auto_ml/async_client.py @@ -19,14 +19,17 @@ from typing import Dict, Sequence, Tuple, Type, Union import pkg_resources -from google.api_core.client_options import ClientOptions # type: ignore -from google.api_core import exceptions as core_exceptions # type: ignore -from google.api_core import gapic_v1 # type: ignore -from google.api_core import retry as retries # type: ignore +from google.api_core.client_options import ClientOptions +from google.api_core import exceptions as core_exceptions +from google.api_core import gapic_v1 +from google.api_core import retry as retries from google.auth import credentials as ga_credentials # type: ignore from google.oauth2 import service_account # type: ignore -OptionalRetry = Union[retries.Retry, object] +try: + OptionalRetry = Union[retries.Retry, gapic_v1.method._MethodDefault] +except AttributeError: # pragma: NO COVER + OptionalRetry = Union[retries.Retry, object] # type: ignore from google.api_core import operation # type: ignore from google.api_core import operation_async # type: ignore diff --git a/google/cloud/automl_v1beta1/services/auto_ml/client.py b/google/cloud/automl_v1beta1/services/auto_ml/client.py index 631650c0..217d1a83 100644 --- a/google/cloud/automl_v1beta1/services/auto_ml/client.py +++ b/google/cloud/automl_v1beta1/services/auto_ml/client.py @@ -14,23 +14,25 @@ # limitations under the License. # from collections import OrderedDict -from distutils import util import os import re from typing import Dict, Optional, Sequence, Tuple, Type, Union import pkg_resources -from google.api_core import client_options as client_options_lib # type: ignore -from google.api_core import exceptions as core_exceptions # type: ignore -from google.api_core import gapic_v1 # type: ignore -from google.api_core import retry as retries # type: ignore +from google.api_core import client_options as client_options_lib +from google.api_core import exceptions as core_exceptions +from google.api_core import gapic_v1 +from google.api_core import retry as retries from google.auth import credentials as ga_credentials # type: ignore from google.auth.transport import mtls # type: ignore from google.auth.transport.grpc import SslCredentials # type: ignore from google.auth.exceptions import MutualTLSChannelError # type: ignore from google.oauth2 import service_account # type: ignore -OptionalRetry = Union[retries.Retry, object] +try: + OptionalRetry = Union[retries.Retry, gapic_v1.method._MethodDefault] +except AttributeError: # pragma: NO COVER + OptionalRetry = Union[retries.Retry, object] # type: ignore from google.api_core import operation # type: ignore from google.api_core import operation_async # type: ignore @@ -422,8 +424,15 @@ def __init__( client_options = client_options_lib.ClientOptions() # Create SSL credentials for mutual TLS if needed. - use_client_cert = bool( - util.strtobool(os.getenv("GOOGLE_API_USE_CLIENT_CERTIFICATE", "false")) + if os.getenv("GOOGLE_API_USE_CLIENT_CERTIFICATE", "false") not in ( + "true", + "false", + ): + raise ValueError( + "Environment variable `GOOGLE_API_USE_CLIENT_CERTIFICATE` must be either `true` or `false`" + ) + use_client_cert = ( + os.getenv("GOOGLE_API_USE_CLIENT_CERTIFICATE", "false") == "true" ) client_cert_source_func = None diff --git a/google/cloud/automl_v1beta1/services/auto_ml/transports/base.py b/google/cloud/automl_v1beta1/services/auto_ml/transports/base.py index 8b05d97e..f3b1f45c 100644 --- a/google/cloud/automl_v1beta1/services/auto_ml/transports/base.py +++ b/google/cloud/automl_v1beta1/services/auto_ml/transports/base.py @@ -18,11 +18,11 @@ import pkg_resources import google.auth # type: ignore -import google.api_core # type: ignore -from google.api_core import exceptions as core_exceptions # type: ignore -from google.api_core import gapic_v1 # type: ignore -from google.api_core import retry as retries # type: ignore -from google.api_core import operations_v1 # type: ignore +import google.api_core +from google.api_core import exceptions as core_exceptions +from google.api_core import gapic_v1 +from google.api_core import retry as retries +from google.api_core import operations_v1 from google.auth import credentials as ga_credentials # type: ignore from google.oauth2 import service_account # type: ignore @@ -110,7 +110,6 @@ def __init__( credentials, _ = google.auth.load_credentials_from_file( credentials_file, **scopes_kwargs, quota_project_id=quota_project_id ) - elif credentials is None: credentials, _ = google.auth.default( **scopes_kwargs, quota_project_id=quota_project_id diff --git a/google/cloud/automl_v1beta1/services/auto_ml/transports/grpc.py b/google/cloud/automl_v1beta1/services/auto_ml/transports/grpc.py index 98731c7a..5d11126f 100644 --- a/google/cloud/automl_v1beta1/services/auto_ml/transports/grpc.py +++ b/google/cloud/automl_v1beta1/services/auto_ml/transports/grpc.py @@ -16,9 +16,9 @@ import warnings from typing import Callable, Dict, Optional, Sequence, Tuple, Union -from google.api_core import grpc_helpers # type: ignore -from google.api_core import operations_v1 # type: ignore -from google.api_core import gapic_v1 # type: ignore +from google.api_core import grpc_helpers +from google.api_core import operations_v1 +from google.api_core import gapic_v1 import google.auth # type: ignore from google.auth import credentials as ga_credentials # type: ignore from google.auth.transport.grpc import SslCredentials # type: ignore diff --git a/google/cloud/automl_v1beta1/services/auto_ml/transports/grpc_asyncio.py b/google/cloud/automl_v1beta1/services/auto_ml/transports/grpc_asyncio.py index 7584fd26..70fff362 100644 --- a/google/cloud/automl_v1beta1/services/auto_ml/transports/grpc_asyncio.py +++ b/google/cloud/automl_v1beta1/services/auto_ml/transports/grpc_asyncio.py @@ -16,9 +16,9 @@ import warnings from typing import Awaitable, Callable, Dict, Optional, Sequence, Tuple, Union -from google.api_core import gapic_v1 # type: ignore -from google.api_core import grpc_helpers_async # type: ignore -from google.api_core import operations_v1 # type: ignore +from google.api_core import gapic_v1 +from google.api_core import grpc_helpers_async +from google.api_core import operations_v1 from google.auth import credentials as ga_credentials # type: ignore from google.auth.transport.grpc import SslCredentials # type: ignore diff --git a/google/cloud/automl_v1beta1/services/prediction_service/async_client.py b/google/cloud/automl_v1beta1/services/prediction_service/async_client.py index 62131f62..32fe3c70 100644 --- a/google/cloud/automl_v1beta1/services/prediction_service/async_client.py +++ b/google/cloud/automl_v1beta1/services/prediction_service/async_client.py @@ -19,14 +19,17 @@ from typing import Dict, Sequence, Tuple, Type, Union import pkg_resources -from google.api_core.client_options import ClientOptions # type: ignore -from google.api_core import exceptions as core_exceptions # type: ignore -from google.api_core import gapic_v1 # type: ignore -from google.api_core import retry as retries # type: ignore +from google.api_core.client_options import ClientOptions +from google.api_core import exceptions as core_exceptions +from google.api_core import gapic_v1 +from google.api_core import retry as retries from google.auth import credentials as ga_credentials # type: ignore from google.oauth2 import service_account # type: ignore -OptionalRetry = Union[retries.Retry, object] +try: + OptionalRetry = Union[retries.Retry, gapic_v1.method._MethodDefault] +except AttributeError: # pragma: NO COVER + OptionalRetry = Union[retries.Retry, object] # type: ignore from google.api_core import operation # type: ignore from google.api_core import operation_async # type: ignore diff --git a/google/cloud/automl_v1beta1/services/prediction_service/client.py b/google/cloud/automl_v1beta1/services/prediction_service/client.py index 4cb9580d..71629b8c 100644 --- a/google/cloud/automl_v1beta1/services/prediction_service/client.py +++ b/google/cloud/automl_v1beta1/services/prediction_service/client.py @@ -14,23 +14,25 @@ # limitations under the License. # from collections import OrderedDict -from distutils import util import os import re from typing import Dict, Optional, Sequence, Tuple, Type, Union import pkg_resources -from google.api_core import client_options as client_options_lib # type: ignore -from google.api_core import exceptions as core_exceptions # type: ignore -from google.api_core import gapic_v1 # type: ignore -from google.api_core import retry as retries # type: ignore +from google.api_core import client_options as client_options_lib +from google.api_core import exceptions as core_exceptions +from google.api_core import gapic_v1 +from google.api_core import retry as retries from google.auth import credentials as ga_credentials # type: ignore from google.auth.transport import mtls # type: ignore from google.auth.transport.grpc import SslCredentials # type: ignore from google.auth.exceptions import MutualTLSChannelError # type: ignore from google.oauth2 import service_account # type: ignore -OptionalRetry = Union[retries.Retry, object] +try: + OptionalRetry = Union[retries.Retry, gapic_v1.method._MethodDefault] +except AttributeError: # pragma: NO COVER + OptionalRetry = Union[retries.Retry, object] # type: ignore from google.api_core import operation # type: ignore from google.api_core import operation_async # type: ignore @@ -294,8 +296,15 @@ def __init__( client_options = client_options_lib.ClientOptions() # Create SSL credentials for mutual TLS if needed. - use_client_cert = bool( - util.strtobool(os.getenv("GOOGLE_API_USE_CLIENT_CERTIFICATE", "false")) + if os.getenv("GOOGLE_API_USE_CLIENT_CERTIFICATE", "false") not in ( + "true", + "false", + ): + raise ValueError( + "Environment variable `GOOGLE_API_USE_CLIENT_CERTIFICATE` must be either `true` or `false`" + ) + use_client_cert = ( + os.getenv("GOOGLE_API_USE_CLIENT_CERTIFICATE", "false") == "true" ) client_cert_source_func = None diff --git a/google/cloud/automl_v1beta1/services/prediction_service/transports/base.py b/google/cloud/automl_v1beta1/services/prediction_service/transports/base.py index 385fd157..5d3ace19 100644 --- a/google/cloud/automl_v1beta1/services/prediction_service/transports/base.py +++ b/google/cloud/automl_v1beta1/services/prediction_service/transports/base.py @@ -18,11 +18,11 @@ import pkg_resources import google.auth # type: ignore -import google.api_core # type: ignore -from google.api_core import exceptions as core_exceptions # type: ignore -from google.api_core import gapic_v1 # type: ignore -from google.api_core import retry as retries # type: ignore -from google.api_core import operations_v1 # type: ignore +import google.api_core +from google.api_core import exceptions as core_exceptions +from google.api_core import gapic_v1 +from google.api_core import retry as retries +from google.api_core import operations_v1 from google.auth import credentials as ga_credentials # type: ignore from google.oauth2 import service_account # type: ignore @@ -101,7 +101,6 @@ def __init__( credentials, _ = google.auth.load_credentials_from_file( credentials_file, **scopes_kwargs, quota_project_id=quota_project_id ) - elif credentials is None: credentials, _ = google.auth.default( **scopes_kwargs, quota_project_id=quota_project_id diff --git a/google/cloud/automl_v1beta1/services/prediction_service/transports/grpc.py b/google/cloud/automl_v1beta1/services/prediction_service/transports/grpc.py index a6d6f940..ae97e4bf 100644 --- a/google/cloud/automl_v1beta1/services/prediction_service/transports/grpc.py +++ b/google/cloud/automl_v1beta1/services/prediction_service/transports/grpc.py @@ -16,9 +16,9 @@ import warnings from typing import Callable, Dict, Optional, Sequence, Tuple, Union -from google.api_core import grpc_helpers # type: ignore -from google.api_core import operations_v1 # type: ignore -from google.api_core import gapic_v1 # type: ignore +from google.api_core import grpc_helpers +from google.api_core import operations_v1 +from google.api_core import gapic_v1 import google.auth # type: ignore from google.auth import credentials as ga_credentials # type: ignore from google.auth.transport.grpc import SslCredentials # type: ignore diff --git a/google/cloud/automl_v1beta1/services/prediction_service/transports/grpc_asyncio.py b/google/cloud/automl_v1beta1/services/prediction_service/transports/grpc_asyncio.py index b1373afa..0464e415 100644 --- a/google/cloud/automl_v1beta1/services/prediction_service/transports/grpc_asyncio.py +++ b/google/cloud/automl_v1beta1/services/prediction_service/transports/grpc_asyncio.py @@ -16,9 +16,9 @@ import warnings from typing import Awaitable, Callable, Dict, Optional, Sequence, Tuple, Union -from google.api_core import gapic_v1 # type: ignore -from google.api_core import grpc_helpers_async # type: ignore -from google.api_core import operations_v1 # type: ignore +from google.api_core import gapic_v1 +from google.api_core import grpc_helpers_async +from google.api_core import operations_v1 from google.auth import credentials as ga_credentials # type: ignore from google.auth.transport.grpc import SslCredentials # type: ignore diff --git a/google/cloud/automl_v1beta1/services/tables/tables_client.py b/google/cloud/automl_v1beta1/services/tables/tables_client.py index 86a22c09..dcf2be40 100644 --- a/google/cloud/automl_v1beta1/services/tables/tables_client.py +++ b/google/cloud/automl_v1beta1/services/tables/tables_client.py @@ -38,12 +38,12 @@ def to_proto_value(value): """translates a Python value to a google.protobuf.Value. - Args: - value: The Python value to be translated. + Args: + value: The Python value to be translated. - Returns: - Tuple of the translated google.protobuf.Value and error if any. - """ + Returns: + Tuple of the translated google.protobuf.Value and error if any. + """ # possible Python types (this is a Python3 module): # https://simplejson.readthedocs.io/en/latest/#encoders-and-decoders # JSON Python 2 Python 3 @@ -158,8 +158,8 @@ def __init__( to use for requests. client_options (Union[dict, google.api_core.client_options.ClientOptions]): Custom options for the client. - client_info (google.api_core.gapic_v1.client_info.ClientInfo): - The client info used to send a user-agent string along with + client_info (google.api_core.gapic_v1.client_info.ClientInfo): + The client info used to send a user-agent string along with API requests. """ version = _GAPIC_LIBRARY_VERSION @@ -1247,7 +1247,8 @@ def update_column_spec( ... project='my-project', region='us-central1') ... >>> client.update_column_spec(dataset_display_name='my_dataset', - ... column_spec_display_name='Outcome', type_code='CATEGORY') + ... column_spec_display_name='Outcome', + ... type_code=automl_v1beta1.TypeCode.CATEGORY) ... Args: diff --git a/google/cloud/automl_v1beta1/types/annotation_payload.py b/google/cloud/automl_v1beta1/types/annotation_payload.py index bf9c1146..fb53ae83 100644 --- a/google/cloud/automl_v1beta1/types/annotation_payload.py +++ b/google/cloud/automl_v1beta1/types/annotation_payload.py @@ -41,30 +41,38 @@ class AnnotationPayload(proto.Message): Attributes: translation (google.cloud.automl_v1beta1.types.TranslationAnnotation): Annotation details for translation. + This field is a member of `oneof`_ ``detail``. classification (google.cloud.automl_v1beta1.types.ClassificationAnnotation): Annotation details for content or image classification. + This field is a member of `oneof`_ ``detail``. image_object_detection (google.cloud.automl_v1beta1.types.ImageObjectDetectionAnnotation): Annotation details for image object detection. + This field is a member of `oneof`_ ``detail``. video_classification (google.cloud.automl_v1beta1.types.VideoClassificationAnnotation): Annotation details for video classification. Returned for Video Classification predictions. + This field is a member of `oneof`_ ``detail``. video_object_tracking (google.cloud.automl_v1beta1.types.VideoObjectTrackingAnnotation): Annotation details for video object tracking. + This field is a member of `oneof`_ ``detail``. text_extraction (google.cloud.automl_v1beta1.types.TextExtractionAnnotation): Annotation details for text extraction. + This field is a member of `oneof`_ ``detail``. text_sentiment (google.cloud.automl_v1beta1.types.TextSentimentAnnotation): Annotation details for text sentiment. + This field is a member of `oneof`_ ``detail``. tables (google.cloud.automl_v1beta1.types.TablesAnnotation): Annotation details for Tables. + This field is a member of `oneof`_ ``detail``. annotation_spec_id (str): Output only . The resource ID of the diff --git a/google/cloud/automl_v1beta1/types/data_items.py b/google/cloud/automl_v1beta1/types/data_items.py index f97cd13b..bb22d9fb 100644 --- a/google/cloud/automl_v1beta1/types/data_items.py +++ b/google/cloud/automl_v1beta1/types/data_items.py @@ -50,10 +50,12 @@ class Image(proto.Message): Image content represented as a stream of bytes. Note: As with all ``bytes`` fields, protobuffers use a pure binary representation, whereas JSON representations use base64. + This field is a member of `oneof`_ ``data``. input_config (google.cloud.automl_v1beta1.types.InputConfig): An input config specifying the content of the image. + This field is a member of `oneof`_ ``data``. thumbnail_uri (str): Output only. HTTP URI to the thumbnail image. @@ -238,15 +240,19 @@ class ExamplePayload(proto.Message): Attributes: image (google.cloud.automl_v1beta1.types.Image): Example image. + This field is a member of `oneof`_ ``payload``. text_snippet (google.cloud.automl_v1beta1.types.TextSnippet): Example text. + This field is a member of `oneof`_ ``payload``. document (google.cloud.automl_v1beta1.types.Document): Example document. + This field is a member of `oneof`_ ``payload``. row (google.cloud.automl_v1beta1.types.Row): Example relational table row. + This field is a member of `oneof`_ ``payload``. """ diff --git a/google/cloud/automl_v1beta1/types/data_stats.py b/google/cloud/automl_v1beta1/types/data_stats.py index fecc4584..094f36b8 100644 --- a/google/cloud/automl_v1beta1/types/data_stats.py +++ b/google/cloud/automl_v1beta1/types/data_stats.py @@ -45,21 +45,27 @@ class DataStats(proto.Message): Attributes: float64_stats (google.cloud.automl_v1beta1.types.Float64Stats): The statistics for FLOAT64 DataType. + This field is a member of `oneof`_ ``stats``. string_stats (google.cloud.automl_v1beta1.types.StringStats): The statistics for STRING DataType. + This field is a member of `oneof`_ ``stats``. timestamp_stats (google.cloud.automl_v1beta1.types.TimestampStats): The statistics for TIMESTAMP DataType. + This field is a member of `oneof`_ ``stats``. array_stats (google.cloud.automl_v1beta1.types.ArrayStats): The statistics for ARRAY DataType. + This field is a member of `oneof`_ ``stats``. struct_stats (google.cloud.automl_v1beta1.types.StructStats): The statistics for STRUCT DataType. + This field is a member of `oneof`_ ``stats``. category_stats (google.cloud.automl_v1beta1.types.CategoryStats): The statistics for CATEGORY DataType. + This field is a member of `oneof`_ ``stats``. distinct_value_count (int): The number of distinct values. diff --git a/google/cloud/automl_v1beta1/types/data_types.py b/google/cloud/automl_v1beta1/types/data_types.py index 3e98e018..0c6f25eb 100644 --- a/google/cloud/automl_v1beta1/types/data_types.py +++ b/google/cloud/automl_v1beta1/types/data_types.py @@ -52,6 +52,7 @@ class DataType(proto.Message): [type_code][google.cloud.automl.v1beta1.DataType.type_code] == [ARRAY][google.cloud.automl.v1beta1.TypeCode.ARRAY], then ``list_element_type`` is the type of the elements. + This field is a member of `oneof`_ ``details``. struct_type (google.cloud.automl_v1beta1.types.StructType): If @@ -59,6 +60,7 @@ class DataType(proto.Message): == [STRUCT][google.cloud.automl.v1beta1.TypeCode.STRUCT], then ``struct_type`` provides type information for the struct's fields. + This field is a member of `oneof`_ ``details``. time_format (str): If @@ -76,6 +78,7 @@ class DataType(proto.Message): the Unix epoch); or be written in ``strftime`` syntax. If time_format is not set, then the default format as described on the type_code is used. + This field is a member of `oneof`_ ``details``. type_code (google.cloud.automl_v1beta1.types.TypeCode): Required. The diff --git a/google/cloud/automl_v1beta1/types/dataset.py b/google/cloud/automl_v1beta1/types/dataset.py index f9e086b1..d8ab7506 100644 --- a/google/cloud/automl_v1beta1/types/dataset.py +++ b/google/cloud/automl_v1beta1/types/dataset.py @@ -43,37 +43,46 @@ class Dataset(proto.Message): Attributes: translation_dataset_metadata (google.cloud.automl_v1beta1.types.TranslationDatasetMetadata): Metadata for a dataset used for translation. + This field is a member of `oneof`_ ``dataset_metadata``. image_classification_dataset_metadata (google.cloud.automl_v1beta1.types.ImageClassificationDatasetMetadata): Metadata for a dataset used for image classification. + This field is a member of `oneof`_ ``dataset_metadata``. text_classification_dataset_metadata (google.cloud.automl_v1beta1.types.TextClassificationDatasetMetadata): Metadata for a dataset used for text classification. + This field is a member of `oneof`_ ``dataset_metadata``. image_object_detection_dataset_metadata (google.cloud.automl_v1beta1.types.ImageObjectDetectionDatasetMetadata): Metadata for a dataset used for image object detection. + This field is a member of `oneof`_ ``dataset_metadata``. video_classification_dataset_metadata (google.cloud.automl_v1beta1.types.VideoClassificationDatasetMetadata): Metadata for a dataset used for video classification. + This field is a member of `oneof`_ ``dataset_metadata``. video_object_tracking_dataset_metadata (google.cloud.automl_v1beta1.types.VideoObjectTrackingDatasetMetadata): Metadata for a dataset used for video object tracking. + This field is a member of `oneof`_ ``dataset_metadata``. text_extraction_dataset_metadata (google.cloud.automl_v1beta1.types.TextExtractionDatasetMetadata): Metadata for a dataset used for text extraction. + This field is a member of `oneof`_ ``dataset_metadata``. text_sentiment_dataset_metadata (google.cloud.automl_v1beta1.types.TextSentimentDatasetMetadata): Metadata for a dataset used for text sentiment. + This field is a member of `oneof`_ ``dataset_metadata``. tables_dataset_metadata (google.cloud.automl_v1beta1.types.TablesDatasetMetadata): Metadata for a dataset used for Tables. + This field is a member of `oneof`_ ``dataset_metadata``. name (str): Output only. The resource name of the dataset. Form: diff --git a/google/cloud/automl_v1beta1/types/io.py b/google/cloud/automl_v1beta1/types/io.py index 44f29a97..57629283 100644 --- a/google/cloud/automl_v1beta1/types/io.py +++ b/google/cloud/automl_v1beta1/types/io.py @@ -347,9 +347,11 @@ class InputConfig(proto.Message): The Google Cloud Storage location for the input content. In ImportData, the gcs_source points to a csv with structure described in the comment. + This field is a member of `oneof`_ ``source``. bigquery_source (google.cloud.automl_v1beta1.types.BigQuerySource): The BigQuery location for the input content. + This field is a member of `oneof`_ ``source``. params (Sequence[google.cloud.automl_v1beta1.types.InputConfig.ParamsEntry]): Additional domain-specific parameters describing the @@ -536,9 +538,11 @@ class BatchPredictInputConfig(proto.Message): gcs_source (google.cloud.automl_v1beta1.types.GcsSource): The Google Cloud Storage location for the input content. + This field is a member of `oneof`_ ``source``. bigquery_source (google.cloud.automl_v1beta1.types.BigQuerySource): The BigQuery location for the input content. + This field is a member of `oneof`_ ``source``. """ @@ -607,10 +611,12 @@ class OutputConfig(proto.Message): new directory will be created with name: export_data-- where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format. All export output will be written into that directory. + This field is a member of `oneof`_ ``destination``. bigquery_destination (google.cloud.automl_v1beta1.types.BigQueryDestination): The BigQuery location where the output is to be written to. + This field is a member of `oneof`_ ``destination``. """ @@ -921,10 +927,12 @@ class BatchPredictOutputConfig(proto.Message): gcs_destination (google.cloud.automl_v1beta1.types.GcsDestination): The Google Cloud Storage location of the directory where the output is to be written to. + This field is a member of `oneof`_ ``destination``. bigquery_destination (google.cloud.automl_v1beta1.types.BigQueryDestination): The BigQuery location where the output is to be written to. + This field is a member of `oneof`_ ``destination``. """ @@ -958,6 +966,7 @@ class ModelExportOutputConfig(proto.Message): YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format, will be created. Inside the model and any of its supporting files will be written. + This field is a member of `oneof`_ ``destination``. gcr_destination (google.cloud.automl_v1beta1.types.GcrDestination): The GCR location where model image is to be @@ -966,6 +975,7 @@ class ModelExportOutputConfig(proto.Message): The model image will be created under the given URI. + This field is a member of `oneof`_ ``destination``. model_format (str): The format in which the model must be exported. The @@ -1081,6 +1091,7 @@ class ExportEvaluatedExamplesOutputConfig(proto.Message): bigquery_destination (google.cloud.automl_v1beta1.types.BigQueryDestination): The BigQuery location where the output is to be written to. + This field is a member of `oneof`_ ``destination``. """ diff --git a/google/cloud/automl_v1beta1/types/model.py b/google/cloud/automl_v1beta1/types/model.py index 34851363..1b70043d 100644 --- a/google/cloud/automl_v1beta1/types/model.py +++ b/google/cloud/automl_v1beta1/types/model.py @@ -39,30 +39,39 @@ class Model(proto.Message): Attributes: translation_model_metadata (google.cloud.automl_v1beta1.types.TranslationModelMetadata): Metadata for translation models. + This field is a member of `oneof`_ ``model_metadata``. image_classification_model_metadata (google.cloud.automl_v1beta1.types.ImageClassificationModelMetadata): Metadata for image classification models. + This field is a member of `oneof`_ ``model_metadata``. text_classification_model_metadata (google.cloud.automl_v1beta1.types.TextClassificationModelMetadata): Metadata for text classification models. + This field is a member of `oneof`_ ``model_metadata``. image_object_detection_model_metadata (google.cloud.automl_v1beta1.types.ImageObjectDetectionModelMetadata): Metadata for image object detection models. + This field is a member of `oneof`_ ``model_metadata``. video_classification_model_metadata (google.cloud.automl_v1beta1.types.VideoClassificationModelMetadata): Metadata for video classification models. + This field is a member of `oneof`_ ``model_metadata``. video_object_tracking_model_metadata (google.cloud.automl_v1beta1.types.VideoObjectTrackingModelMetadata): Metadata for video object tracking models. + This field is a member of `oneof`_ ``model_metadata``. text_extraction_model_metadata (google.cloud.automl_v1beta1.types.TextExtractionModelMetadata): Metadata for text extraction models. + This field is a member of `oneof`_ ``model_metadata``. tables_model_metadata (google.cloud.automl_v1beta1.types.TablesModelMetadata): Metadata for Tables models. + This field is a member of `oneof`_ ``model_metadata``. text_sentiment_model_metadata (google.cloud.automl_v1beta1.types.TextSentimentModelMetadata): Metadata for text sentiment models. + This field is a member of `oneof`_ ``model_metadata``. name (str): Output only. Resource name of the model. Format: diff --git a/google/cloud/automl_v1beta1/types/model_evaluation.py b/google/cloud/automl_v1beta1/types/model_evaluation.py index 0d9b31df..c44519a0 100644 --- a/google/cloud/automl_v1beta1/types/model_evaluation.py +++ b/google/cloud/automl_v1beta1/types/model_evaluation.py @@ -45,30 +45,37 @@ class ModelEvaluation(proto.Message): video and tables classification. Tables problem is considered a classification when the target column is CATEGORY DataType. + This field is a member of `oneof`_ ``metrics``. regression_evaluation_metrics (google.cloud.automl_v1beta1.types.RegressionEvaluationMetrics): Model evaluation metrics for Tables regression. Tables problem is considered a regression when the target column has FLOAT64 DataType. + This field is a member of `oneof`_ ``metrics``. translation_evaluation_metrics (google.cloud.automl_v1beta1.types.TranslationEvaluationMetrics): Model evaluation metrics for translation. + This field is a member of `oneof`_ ``metrics``. image_object_detection_evaluation_metrics (google.cloud.automl_v1beta1.types.ImageObjectDetectionEvaluationMetrics): Model evaluation metrics for image object detection. + This field is a member of `oneof`_ ``metrics``. video_object_tracking_evaluation_metrics (google.cloud.automl_v1beta1.types.VideoObjectTrackingEvaluationMetrics): Model evaluation metrics for video object tracking. + This field is a member of `oneof`_ ``metrics``. text_sentiment_evaluation_metrics (google.cloud.automl_v1beta1.types.TextSentimentEvaluationMetrics): Evaluation metrics for text sentiment models. + This field is a member of `oneof`_ ``metrics``. text_extraction_evaluation_metrics (google.cloud.automl_v1beta1.types.TextExtractionEvaluationMetrics): Evaluation metrics for text extraction models. + This field is a member of `oneof`_ ``metrics``. name (str): Output only. Resource name of the model evaluation. Format: diff --git a/google/cloud/automl_v1beta1/types/operations.py b/google/cloud/automl_v1beta1/types/operations.py index 2384ceeb..5611902d 100644 --- a/google/cloud/automl_v1beta1/types/operations.py +++ b/google/cloud/automl_v1beta1/types/operations.py @@ -51,30 +51,39 @@ class OperationMetadata(proto.Message): Attributes: delete_details (google.cloud.automl_v1beta1.types.DeleteOperationMetadata): Details of a Delete operation. + This field is a member of `oneof`_ ``details``. deploy_model_details (google.cloud.automl_v1beta1.types.DeployModelOperationMetadata): Details of a DeployModel operation. + This field is a member of `oneof`_ ``details``. undeploy_model_details (google.cloud.automl_v1beta1.types.UndeployModelOperationMetadata): Details of an UndeployModel operation. + This field is a member of `oneof`_ ``details``. create_model_details (google.cloud.automl_v1beta1.types.CreateModelOperationMetadata): Details of CreateModel operation. + This field is a member of `oneof`_ ``details``. import_data_details (google.cloud.automl_v1beta1.types.ImportDataOperationMetadata): Details of ImportData operation. + This field is a member of `oneof`_ ``details``. batch_predict_details (google.cloud.automl_v1beta1.types.BatchPredictOperationMetadata): Details of BatchPredict operation. + This field is a member of `oneof`_ ``details``. export_data_details (google.cloud.automl_v1beta1.types.ExportDataOperationMetadata): Details of ExportData operation. + This field is a member of `oneof`_ ``details``. export_model_details (google.cloud.automl_v1beta1.types.ExportModelOperationMetadata): Details of ExportModel operation. + This field is a member of `oneof`_ ``details``. export_evaluated_examples_details (google.cloud.automl_v1beta1.types.ExportEvaluatedExamplesOperationMetadata): Details of ExportEvaluatedExamples operation. + This field is a member of `oneof`_ ``details``. progress_percent (int): Output only. Progress of operation. Range: [0, 100]. Not @@ -202,11 +211,13 @@ class ExportDataOutputInfo(proto.Message): The full path of the Google Cloud Storage directory created, into which the exported data is written. + This field is a member of `oneof`_ ``output_location``. bigquery_output_dataset (str): The path of the BigQuery dataset created, in bq://projectId.bqDatasetId format, into which the exported data is written. + This field is a member of `oneof`_ ``output_location``. """ @@ -249,11 +260,13 @@ class BatchPredictOutputInfo(proto.Message): The full path of the Google Cloud Storage directory created, into which the prediction output is written. + This field is a member of `oneof`_ ``output_location``. bigquery_output_dataset (str): The path of the BigQuery dataset created, in bq://projectId.bqDatasetId format, into which the prediction output is written. + This field is a member of `oneof`_ ``output_location``. """ diff --git a/google/cloud/automl_v1beta1/types/service.py b/google/cloud/automl_v1beta1/types/service.py index 2487e9eb..0bc90ef8 100644 --- a/google/cloud/automl_v1beta1/types/service.py +++ b/google/cloud/automl_v1beta1/types/service.py @@ -102,11 +102,11 @@ class ListDatasetsRequest(proto.Message): An expression for filtering the results of the request. - ``dataset_metadata`` - for existence of the case (e.g. - image_classification_dataset_metadata:*). Some examples - of using the filter are: + ``image_classification_dataset_metadata:*``). Some + examples of using the filter are: - ``translation_dataset_metadata:*`` --> The dataset has - translation_dataset_metadata. + ``translation_dataset_metadata``. page_size (int): Requested page size. Server may return fewer results than requested. If unspecified, server @@ -446,13 +446,13 @@ class ListModelsRequest(proto.Message): An expression for filtering the results of the request. - ``model_metadata`` - for existence of the case (e.g. - video_classification_model_metadata:*). + ``video_classification_model_metadata:*``). - ``dataset_id`` - for = or !=. Some examples of using the filter are: - ``image_classification_model_metadata:*`` --> The model - has image_classification_model_metadata. + has ``image_classification_model_metadata``. - ``dataset_id=5`` --> The model was created from a dataset with ID 5. @@ -522,10 +522,12 @@ class DeployModelRequest(proto.Message): image_object_detection_model_deployment_metadata (google.cloud.automl_v1beta1.types.ImageObjectDetectionModelDeploymentMetadata): Model deployment metadata specific to Image Object Detection. + This field is a member of `oneof`_ ``model_deployment_metadata``. image_classification_model_deployment_metadata (google.cloud.automl_v1beta1.types.ImageClassificationModelDeploymentMetadata): Model deployment metadata specific to Image Classification. + This field is a member of `oneof`_ ``model_deployment_metadata``. name (str): Required. Resource name of the model to diff --git a/google/cloud/automl_v1beta1/types/tables.py b/google/cloud/automl_v1beta1/types/tables.py index f24af474..8dd51d62 100644 --- a/google/cloud/automl_v1beta1/types/tables.py +++ b/google/cloud/automl_v1beta1/types/tables.py @@ -129,11 +129,13 @@ class TablesModelMetadata(proto.Message): Required when optimization_objective is "MAXIMIZE_PRECISION_AT_RECALL". Must be between 0 and 1, inclusive. + This field is a member of `oneof`_ ``additional_optimization_objective_config``. optimization_objective_precision_value (float): Required when optimization_objective is "MAXIMIZE_RECALL_AT_PRECISION". Must be between 0 and 1, inclusive. + This field is a member of `oneof`_ ``additional_optimization_objective_config``. target_column_spec (google.cloud.automl_v1beta1.types.ColumnSpec): Column spec of the dataset's primary table's column the diff --git a/google/cloud/automl_v1beta1/types/text_extraction.py b/google/cloud/automl_v1beta1/types/text_extraction.py index cf8f811f..3de19a94 100644 --- a/google/cloud/automl_v1beta1/types/text_extraction.py +++ b/google/cloud/automl_v1beta1/types/text_extraction.py @@ -34,6 +34,7 @@ class TextExtractionAnnotation(proto.Message): An entity annotation will set this, which is the part of the original text to which the annotation pertains. + This field is a member of `oneof`_ ``annotation``. score (float): Output only. A confidence estimate between diff --git a/noxfile.py b/noxfile.py index c9b1d885..8e1a3af2 100644 --- a/noxfile.py +++ b/noxfile.py @@ -190,6 +190,7 @@ def docs(session): shutil.rmtree(os.path.join("docs", "_build"), ignore_errors=True) session.run( "sphinx-build", + "-W", # warnings as errors "-T", # show full traceback on exception "-N", # no colors "-b", diff --git a/owlbot.py b/owlbot.py index fa21da1a..204c8ba0 100644 --- a/owlbot.py +++ b/owlbot.py @@ -71,12 +71,4 @@ python.py_samples(skip_readmes=True) -# This is being added to AutoML because the proto comments are long and -# regex replaces are a brittle temporary solution. -s.replace( -"noxfile.py", -""""-W", # warnings as errors -\s+"-T", \# show full traceback on exception""", -""""-T", # show full traceback on exception""") - s.shell.run(["nox", "-s", "blacken"], hide_output=False) diff --git a/samples/AUTHORING_GUIDE.md b/samples/AUTHORING_GUIDE.md index 55c97b32..8249522f 100644 --- a/samples/AUTHORING_GUIDE.md +++ b/samples/AUTHORING_GUIDE.md @@ -1 +1 @@ -See https://github.com/GoogleCloudPlatform/python-docs-samples/blob/master/AUTHORING_GUIDE.md \ No newline at end of file +See https://github.com/GoogleCloudPlatform/python-docs-samples/blob/main/AUTHORING_GUIDE.md \ No newline at end of file diff --git a/samples/CONTRIBUTING.md b/samples/CONTRIBUTING.md index 34c882b6..f5fe2e6b 100644 --- a/samples/CONTRIBUTING.md +++ b/samples/CONTRIBUTING.md @@ -1 +1 @@ -See https://github.com/GoogleCloudPlatform/python-docs-samples/blob/master/CONTRIBUTING.md \ No newline at end of file +See https://github.com/GoogleCloudPlatform/python-docs-samples/blob/main/CONTRIBUTING.md \ No newline at end of file diff --git a/samples/beta/noxfile.py b/samples/beta/noxfile.py index 93a9122c..3bbef5d5 100644 --- a/samples/beta/noxfile.py +++ b/samples/beta/noxfile.py @@ -14,6 +14,7 @@ from __future__ import print_function +import glob import os from pathlib import Path import sys @@ -184,37 +185,44 @@ def blacken(session: nox.sessions.Session) -> None: def _session_tests( session: nox.sessions.Session, post_install: Callable = None ) -> None: - if TEST_CONFIG["pip_version_override"]: - pip_version = TEST_CONFIG["pip_version_override"] - session.install(f"pip=={pip_version}") - """Runs py.test for a particular project.""" - if os.path.exists("requirements.txt"): - if os.path.exists("constraints.txt"): - session.install("-r", "requirements.txt", "-c", "constraints.txt") - else: - session.install("-r", "requirements.txt") - - if os.path.exists("requirements-test.txt"): - if os.path.exists("constraints-test.txt"): - session.install("-r", "requirements-test.txt", "-c", "constraints-test.txt") - else: - session.install("-r", "requirements-test.txt") - - if INSTALL_LIBRARY_FROM_SOURCE: - session.install("-e", _get_repo_root()) - - if post_install: - post_install(session) - - session.run( - "pytest", - *(PYTEST_COMMON_ARGS + session.posargs), - # Pytest will return 5 when no tests are collected. This can happen - # on travis where slow and flaky tests are excluded. - # See http://doc.pytest.org/en/latest/_modules/_pytest/main.html - success_codes=[0, 5], - env=get_pytest_env_vars(), - ) + # check for presence of tests + test_list = glob.glob("*_test.py") + glob.glob("test_*.py") + if len(test_list) == 0: + print("No tests found, skipping directory.") + else: + if TEST_CONFIG["pip_version_override"]: + pip_version = TEST_CONFIG["pip_version_override"] + session.install(f"pip=={pip_version}") + """Runs py.test for a particular project.""" + if os.path.exists("requirements.txt"): + if os.path.exists("constraints.txt"): + session.install("-r", "requirements.txt", "-c", "constraints.txt") + else: + session.install("-r", "requirements.txt") + + if os.path.exists("requirements-test.txt"): + if os.path.exists("constraints-test.txt"): + session.install( + "-r", "requirements-test.txt", "-c", "constraints-test.txt" + ) + else: + session.install("-r", "requirements-test.txt") + + if INSTALL_LIBRARY_FROM_SOURCE: + session.install("-e", _get_repo_root()) + + if post_install: + post_install(session) + + session.run( + "pytest", + *(PYTEST_COMMON_ARGS + session.posargs), + # Pytest will return 5 when no tests are collected. This can happen + # on travis where slow and flaky tests are excluded. + # See http://doc.pytest.org/en/latest/_modules/_pytest/main.html + success_codes=[0, 5], + env=get_pytest_env_vars(), + ) @nox.session(python=ALL_VERSIONS) diff --git a/samples/beta/requirements.txt b/samples/beta/requirements.txt index 9bea146f..22ec816c 100644 --- a/samples/beta/requirements.txt +++ b/samples/beta/requirements.txt @@ -1 +1 @@ -google-cloud-automl==2.5.1 +google-cloud-automl==2.5.2 diff --git a/samples/snippets/noxfile.py b/samples/snippets/noxfile.py index 93a9122c..3bbef5d5 100644 --- a/samples/snippets/noxfile.py +++ b/samples/snippets/noxfile.py @@ -14,6 +14,7 @@ from __future__ import print_function +import glob import os from pathlib import Path import sys @@ -184,37 +185,44 @@ def blacken(session: nox.sessions.Session) -> None: def _session_tests( session: nox.sessions.Session, post_install: Callable = None ) -> None: - if TEST_CONFIG["pip_version_override"]: - pip_version = TEST_CONFIG["pip_version_override"] - session.install(f"pip=={pip_version}") - """Runs py.test for a particular project.""" - if os.path.exists("requirements.txt"): - if os.path.exists("constraints.txt"): - session.install("-r", "requirements.txt", "-c", "constraints.txt") - else: - session.install("-r", "requirements.txt") - - if os.path.exists("requirements-test.txt"): - if os.path.exists("constraints-test.txt"): - session.install("-r", "requirements-test.txt", "-c", "constraints-test.txt") - else: - session.install("-r", "requirements-test.txt") - - if INSTALL_LIBRARY_FROM_SOURCE: - session.install("-e", _get_repo_root()) - - if post_install: - post_install(session) - - session.run( - "pytest", - *(PYTEST_COMMON_ARGS + session.posargs), - # Pytest will return 5 when no tests are collected. This can happen - # on travis where slow and flaky tests are excluded. - # See http://doc.pytest.org/en/latest/_modules/_pytest/main.html - success_codes=[0, 5], - env=get_pytest_env_vars(), - ) + # check for presence of tests + test_list = glob.glob("*_test.py") + glob.glob("test_*.py") + if len(test_list) == 0: + print("No tests found, skipping directory.") + else: + if TEST_CONFIG["pip_version_override"]: + pip_version = TEST_CONFIG["pip_version_override"] + session.install(f"pip=={pip_version}") + """Runs py.test for a particular project.""" + if os.path.exists("requirements.txt"): + if os.path.exists("constraints.txt"): + session.install("-r", "requirements.txt", "-c", "constraints.txt") + else: + session.install("-r", "requirements.txt") + + if os.path.exists("requirements-test.txt"): + if os.path.exists("constraints-test.txt"): + session.install( + "-r", "requirements-test.txt", "-c", "constraints-test.txt" + ) + else: + session.install("-r", "requirements-test.txt") + + if INSTALL_LIBRARY_FROM_SOURCE: + session.install("-e", _get_repo_root()) + + if post_install: + post_install(session) + + session.run( + "pytest", + *(PYTEST_COMMON_ARGS + session.posargs), + # Pytest will return 5 when no tests are collected. This can happen + # on travis where slow and flaky tests are excluded. + # See http://doc.pytest.org/en/latest/_modules/_pytest/main.html + success_codes=[0, 5], + env=get_pytest_env_vars(), + ) @nox.session(python=ALL_VERSIONS) diff --git a/samples/snippets/requirements.txt b/samples/snippets/requirements.txt index ffc9d62b..390316bb 100644 --- a/samples/snippets/requirements.txt +++ b/samples/snippets/requirements.txt @@ -1,3 +1,3 @@ -google-cloud-translate==3.6.0 -google-cloud-storage==1.42.3 -google-cloud-automl==2.5.1 +google-cloud-translate==3.6.1 +google-cloud-storage==2.0.0 +google-cloud-automl==2.5.2 diff --git a/samples/snippets/translate_create_model.py b/samples/snippets/translate_create_model.py index 47304d4d..fecdb022 100644 --- a/samples/snippets/translate_create_model.py +++ b/samples/snippets/translate_create_model.py @@ -27,7 +27,6 @@ def create_model(project_id, dataset_id, display_name): # A resource that represents Google Cloud Platform location. project_location = f"projects/{project_id}/locations/us-central1" - # Leave model unset to use the default base model provided by Google translation_model_metadata = automl.TranslationModelMetadata() model = automl.Model( display_name=display_name, diff --git a/samples/snippets/translate_create_model_test.py b/samples/snippets/translate_create_model_test.py index f03de69e..933a45d2 100644 --- a/samples/snippets/translate_create_model_test.py +++ b/samples/snippets/translate_create_model_test.py @@ -26,6 +26,10 @@ def test_translate_create_model(capsys): PROJECT_ID, DATASET_ID, "translate_test_create_model" ) out, _ = capsys.readouterr() + # After setting DATASET_ID, change line below to + # assert "Training started..." in out assert "Dataset does not exist." in out except Exception as e: + # After setting DATASET_ID, change line below to + # assert "Training started..." in e.message assert "Dataset does not exist." in e.message diff --git a/samples/tables/noxfile.py b/samples/tables/noxfile.py index 93a9122c..3bbef5d5 100644 --- a/samples/tables/noxfile.py +++ b/samples/tables/noxfile.py @@ -14,6 +14,7 @@ from __future__ import print_function +import glob import os from pathlib import Path import sys @@ -184,37 +185,44 @@ def blacken(session: nox.sessions.Session) -> None: def _session_tests( session: nox.sessions.Session, post_install: Callable = None ) -> None: - if TEST_CONFIG["pip_version_override"]: - pip_version = TEST_CONFIG["pip_version_override"] - session.install(f"pip=={pip_version}") - """Runs py.test for a particular project.""" - if os.path.exists("requirements.txt"): - if os.path.exists("constraints.txt"): - session.install("-r", "requirements.txt", "-c", "constraints.txt") - else: - session.install("-r", "requirements.txt") - - if os.path.exists("requirements-test.txt"): - if os.path.exists("constraints-test.txt"): - session.install("-r", "requirements-test.txt", "-c", "constraints-test.txt") - else: - session.install("-r", "requirements-test.txt") - - if INSTALL_LIBRARY_FROM_SOURCE: - session.install("-e", _get_repo_root()) - - if post_install: - post_install(session) - - session.run( - "pytest", - *(PYTEST_COMMON_ARGS + session.posargs), - # Pytest will return 5 when no tests are collected. This can happen - # on travis where slow and flaky tests are excluded. - # See http://doc.pytest.org/en/latest/_modules/_pytest/main.html - success_codes=[0, 5], - env=get_pytest_env_vars(), - ) + # check for presence of tests + test_list = glob.glob("*_test.py") + glob.glob("test_*.py") + if len(test_list) == 0: + print("No tests found, skipping directory.") + else: + if TEST_CONFIG["pip_version_override"]: + pip_version = TEST_CONFIG["pip_version_override"] + session.install(f"pip=={pip_version}") + """Runs py.test for a particular project.""" + if os.path.exists("requirements.txt"): + if os.path.exists("constraints.txt"): + session.install("-r", "requirements.txt", "-c", "constraints.txt") + else: + session.install("-r", "requirements.txt") + + if os.path.exists("requirements-test.txt"): + if os.path.exists("constraints-test.txt"): + session.install( + "-r", "requirements-test.txt", "-c", "constraints-test.txt" + ) + else: + session.install("-r", "requirements-test.txt") + + if INSTALL_LIBRARY_FROM_SOURCE: + session.install("-e", _get_repo_root()) + + if post_install: + post_install(session) + + session.run( + "pytest", + *(PYTEST_COMMON_ARGS + session.posargs), + # Pytest will return 5 when no tests are collected. This can happen + # on travis where slow and flaky tests are excluded. + # See http://doc.pytest.org/en/latest/_modules/_pytest/main.html + success_codes=[0, 5], + env=get_pytest_env_vars(), + ) @nox.session(python=ALL_VERSIONS) diff --git a/samples/tables/predict_test.py b/samples/tables/predict_test.py index 1da6bfc2..5530e6eb 100644 --- a/samples/tables/predict_test.py +++ b/samples/tables/predict_test.py @@ -16,18 +16,23 @@ import os +import backoff + from google.cloud.automl_v1beta1 import Model import automl_tables_model import automl_tables_predict import model_test - PROJECT = os.environ["GOOGLE_CLOUD_PROJECT"] REGION = "us-central1" STATIC_MODEL = model_test.STATIC_MODEL +MAX_TIMEOUT = 200 +@backoff.on_exception( + wait_gen=lambda: iter([50, 150, MAX_TIMEOUT]), exception=Exception, max_tries=3 +) def test_predict(capsys): inputs = { "Age": 31, diff --git a/samples/tables/requirements-test.txt b/samples/tables/requirements-test.txt index 92709451..0f6247f7 100644 --- a/samples/tables/requirements-test.txt +++ b/samples/tables/requirements-test.txt @@ -1 +1,2 @@ pytest==6.2.5 +backoff==1.11.1 \ No newline at end of file diff --git a/samples/tables/requirements.txt b/samples/tables/requirements.txt index 9bea146f..22ec816c 100644 --- a/samples/tables/requirements.txt +++ b/samples/tables/requirements.txt @@ -1 +1 @@ -google-cloud-automl==2.5.1 +google-cloud-automl==2.5.2 diff --git a/setup.py b/setup.py index b1a189af..2a501217 100644 --- a/setup.py +++ b/setup.py @@ -19,7 +19,7 @@ name = "google-cloud-automl" description = "Cloud AutoML API client library" -version = "2.5.2" +version = "2.6.0" release_status = "Development Status :: 5 - Production/Stable" dependencies = [ # NOTE: Maintainers, please do not require google-api-core>=2.x.x @@ -31,7 +31,7 @@ extras = { "libcst": "libcst >= 0.2.5", "pandas": ["pandas>=0.23.0"], - "storage": ["google-cloud-storage >= 1.18.0, < 2.0.0dev"], + "storage": ["google-cloud-storage >=1.18.0, <3.0.0dev"], } package_root = os.path.abspath(os.path.dirname(__file__)) @@ -68,6 +68,8 @@ "Programming Language :: Python :: 3.6", "Programming Language :: Python :: 3.7", "Programming Language :: Python :: 3.8", + "Programming Language :: Python :: 3.9", + "Programming Language :: Python :: 3.10", "Operating System :: OS Independent", "Topic :: Internet", ], diff --git a/tests/unit/gapic/automl_v1/test_auto_ml.py b/tests/unit/gapic/automl_v1/test_auto_ml.py index 94431974..2267ee42 100644 --- a/tests/unit/gapic/automl_v1/test_auto_ml.py +++ b/tests/unit/gapic/automl_v1/test_auto_ml.py @@ -245,20 +245,20 @@ def test_auto_ml_client_client_options(client_class, transport_class, transport_ # unsupported value. with mock.patch.dict(os.environ, {"GOOGLE_API_USE_MTLS_ENDPOINT": "Unsupported"}): with pytest.raises(MutualTLSChannelError): - client = client_class() + client = client_class(transport=transport_name) # Check the case GOOGLE_API_USE_CLIENT_CERTIFICATE has unsupported value. with mock.patch.dict( os.environ, {"GOOGLE_API_USE_CLIENT_CERTIFICATE": "Unsupported"} ): with pytest.raises(ValueError): - client = client_class() + client = client_class(transport=transport_name) # Check the case quota_project_id is provided options = client_options.ClientOptions(quota_project_id="octopus") with mock.patch.object(transport_class, "__init__") as patched: patched.return_value = None - client = client_class(transport=transport_name, client_options=options) + client = client_class(client_options=options, transport=transport_name) patched.assert_called_once_with( credentials=None, credentials_file=None, @@ -313,7 +313,7 @@ def test_auto_ml_client_mtls_env_auto( ) with mock.patch.object(transport_class, "__init__") as patched: patched.return_value = None - client = client_class(transport=transport_name, client_options=options) + client = client_class(client_options=options, transport=transport_name) if use_client_cert_env == "false": expected_client_cert_source = None @@ -404,7 +404,7 @@ def test_auto_ml_client_client_options_scopes( options = client_options.ClientOptions(scopes=["1", "2"],) with mock.patch.object(transport_class, "__init__") as patched: patched.return_value = None - client = client_class(transport=transport_name, client_options=options) + client = client_class(client_options=options, transport=transport_name) patched.assert_called_once_with( credentials=None, credentials_file=None, @@ -431,7 +431,7 @@ def test_auto_ml_client_client_options_credentials_file( options = client_options.ClientOptions(credentials_file="credentials.json") with mock.patch.object(transport_class, "__init__") as patched: patched.return_value = None - client = client_class(transport=transport_name, client_options=options) + client = client_class(client_options=options, transport=transport_name) patched.assert_called_once_with( credentials=None, credentials_file="credentials.json", @@ -462,9 +462,8 @@ def test_auto_ml_client_client_options_from_dict(): ) -def test_create_dataset( - transport: str = "grpc", request_type=service.CreateDatasetRequest -): +@pytest.mark.parametrize("request_type", [service.CreateDatasetRequest, dict,]) +def test_create_dataset(request_type, transport: str = "grpc"): client = AutoMlClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) @@ -488,10 +487,6 @@ def test_create_dataset( assert isinstance(response, future.Future) -def test_create_dataset_from_dict(): - test_create_dataset(request_type=dict) - - def test_create_dataset_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. @@ -614,12 +609,16 @@ def test_create_dataset_flattened(): # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] - assert args[0].parent == "parent_value" - assert args[0].dataset == gca_dataset.Dataset( + arg = args[0].parent + mock_val = "parent_value" + assert arg == mock_val + arg = args[0].dataset + mock_val = gca_dataset.Dataset( translation_dataset_metadata=translation.TranslationDatasetMetadata( source_language_code="source_language_code_value" ) ) + assert arg == mock_val def test_create_dataset_flattened_error(): @@ -666,12 +665,16 @@ async def test_create_dataset_flattened_async(): # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] - assert args[0].parent == "parent_value" - assert args[0].dataset == gca_dataset.Dataset( + arg = args[0].parent + mock_val = "parent_value" + assert arg == mock_val + arg = args[0].dataset + mock_val = gca_dataset.Dataset( translation_dataset_metadata=translation.TranslationDatasetMetadata( source_language_code="source_language_code_value" ) ) + assert arg == mock_val @pytest.mark.asyncio @@ -692,7 +695,8 @@ async def test_create_dataset_flattened_error_async(): ) -def test_get_dataset(transport: str = "grpc", request_type=service.GetDatasetRequest): +@pytest.mark.parametrize("request_type", [service.GetDatasetRequest, dict,]) +def test_get_dataset(request_type, transport: str = "grpc"): client = AutoMlClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) @@ -730,10 +734,6 @@ def test_get_dataset(transport: str = "grpc", request_type=service.GetDatasetReq assert response.etag == "etag_value" -def test_get_dataset_from_dict(): - test_get_dataset(request_type=dict) - - def test_get_dataset_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. @@ -858,7 +858,9 @@ def test_get_dataset_flattened(): # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val def test_get_dataset_flattened_error(): @@ -890,7 +892,9 @@ async def test_get_dataset_flattened_async(): # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val @pytest.mark.asyncio @@ -905,9 +909,8 @@ async def test_get_dataset_flattened_error_async(): ) -def test_list_datasets( - transport: str = "grpc", request_type=service.ListDatasetsRequest -): +@pytest.mark.parametrize("request_type", [service.ListDatasetsRequest, dict,]) +def test_list_datasets(request_type, transport: str = "grpc"): client = AutoMlClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) @@ -934,10 +937,6 @@ def test_list_datasets( assert response.next_page_token == "next_page_token_value" -def test_list_datasets_from_dict(): - test_list_datasets(request_type=dict) - - def test_list_datasets_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. @@ -1054,7 +1053,9 @@ def test_list_datasets_flattened(): # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] - assert args[0].parent == "parent_value" + arg = args[0].parent + mock_val = "parent_value" + assert arg == mock_val def test_list_datasets_flattened_error(): @@ -1088,7 +1089,9 @@ async def test_list_datasets_flattened_async(): # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] - assert args[0].parent == "parent_value" + arg = args[0].parent + mock_val = "parent_value" + assert arg == mock_val @pytest.mark.asyncio @@ -1103,8 +1106,10 @@ async def test_list_datasets_flattened_error_async(): ) -def test_list_datasets_pager(): - client = AutoMlClient(credentials=ga_credentials.AnonymousCredentials,) +def test_list_datasets_pager(transport_name: str = "grpc"): + client = AutoMlClient( + credentials=ga_credentials.AnonymousCredentials, transport=transport_name, + ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.list_datasets), "__call__") as call: @@ -1137,8 +1142,10 @@ def test_list_datasets_pager(): assert all(isinstance(i, dataset.Dataset) for i in results) -def test_list_datasets_pages(): - client = AutoMlClient(credentials=ga_credentials.AnonymousCredentials,) +def test_list_datasets_pages(transport_name: str = "grpc"): + client = AutoMlClient( + credentials=ga_credentials.AnonymousCredentials, transport=transport_name, + ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.list_datasets), "__call__") as call: @@ -1225,9 +1232,8 @@ async def test_list_datasets_async_pages(): assert page_.raw_page.next_page_token == token -def test_update_dataset( - transport: str = "grpc", request_type=service.UpdateDatasetRequest -): +@pytest.mark.parametrize("request_type", [service.UpdateDatasetRequest, dict,]) +def test_update_dataset(request_type, transport: str = "grpc"): client = AutoMlClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) @@ -1265,10 +1271,6 @@ def test_update_dataset( assert response.etag == "etag_value" -def test_update_dataset_from_dict(): - test_update_dataset(request_type=dict) - - def test_update_dataset_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. @@ -1404,12 +1406,16 @@ def test_update_dataset_flattened(): # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] - assert args[0].dataset == gca_dataset.Dataset( + arg = args[0].dataset + mock_val = gca_dataset.Dataset( translation_dataset_metadata=translation.TranslationDatasetMetadata( source_language_code="source_language_code_value" ) ) - assert args[0].update_mask == field_mask_pb2.FieldMask(paths=["paths_value"]) + assert arg == mock_val + arg = args[0].update_mask + mock_val = field_mask_pb2.FieldMask(paths=["paths_value"]) + assert arg == mock_val def test_update_dataset_flattened_error(): @@ -1454,12 +1460,16 @@ async def test_update_dataset_flattened_async(): # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] - assert args[0].dataset == gca_dataset.Dataset( + arg = args[0].dataset + mock_val = gca_dataset.Dataset( translation_dataset_metadata=translation.TranslationDatasetMetadata( source_language_code="source_language_code_value" ) ) - assert args[0].update_mask == field_mask_pb2.FieldMask(paths=["paths_value"]) + assert arg == mock_val + arg = args[0].update_mask + mock_val = field_mask_pb2.FieldMask(paths=["paths_value"]) + assert arg == mock_val @pytest.mark.asyncio @@ -1480,9 +1490,8 @@ async def test_update_dataset_flattened_error_async(): ) -def test_delete_dataset( - transport: str = "grpc", request_type=service.DeleteDatasetRequest -): +@pytest.mark.parametrize("request_type", [service.DeleteDatasetRequest, dict,]) +def test_delete_dataset(request_type, transport: str = "grpc"): client = AutoMlClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) @@ -1506,10 +1515,6 @@ def test_delete_dataset( assert isinstance(response, future.Future) -def test_delete_dataset_from_dict(): - test_delete_dataset(request_type=dict) - - def test_delete_dataset_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. @@ -1625,7 +1630,9 @@ def test_delete_dataset_flattened(): # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val def test_delete_dataset_flattened_error(): @@ -1659,7 +1666,9 @@ async def test_delete_dataset_flattened_async(): # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val @pytest.mark.asyncio @@ -1674,7 +1683,8 @@ async def test_delete_dataset_flattened_error_async(): ) -def test_import_data(transport: str = "grpc", request_type=service.ImportDataRequest): +@pytest.mark.parametrize("request_type", [service.ImportDataRequest, dict,]) +def test_import_data(request_type, transport: str = "grpc"): client = AutoMlClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) @@ -1698,10 +1708,6 @@ def test_import_data(transport: str = "grpc", request_type=service.ImportDataReq assert isinstance(response, future.Future) -def test_import_data_from_dict(): - test_import_data(request_type=dict) - - def test_import_data_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. @@ -1822,10 +1828,14 @@ def test_import_data_flattened(): # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" - assert args[0].input_config == io.InputConfig( + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val + arg = args[0].input_config + mock_val = io.InputConfig( gcs_source=io.GcsSource(input_uris=["input_uris_value"]) ) + assert arg == mock_val def test_import_data_flattened_error(): @@ -1868,10 +1878,14 @@ async def test_import_data_flattened_async(): # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" - assert args[0].input_config == io.InputConfig( + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val + arg = args[0].input_config + mock_val = io.InputConfig( gcs_source=io.GcsSource(input_uris=["input_uris_value"]) ) + assert arg == mock_val @pytest.mark.asyncio @@ -1890,7 +1904,8 @@ async def test_import_data_flattened_error_async(): ) -def test_export_data(transport: str = "grpc", request_type=service.ExportDataRequest): +@pytest.mark.parametrize("request_type", [service.ExportDataRequest, dict,]) +def test_export_data(request_type, transport: str = "grpc"): client = AutoMlClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) @@ -1914,10 +1929,6 @@ def test_export_data(transport: str = "grpc", request_type=service.ExportDataReq assert isinstance(response, future.Future) -def test_export_data_from_dict(): - test_export_data(request_type=dict) - - def test_export_data_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. @@ -2040,12 +2051,16 @@ def test_export_data_flattened(): # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" - assert args[0].output_config == io.OutputConfig( + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val + arg = args[0].output_config + mock_val = io.OutputConfig( gcs_destination=io.GcsDestination( output_uri_prefix="output_uri_prefix_value" ) ) + assert arg == mock_val def test_export_data_flattened_error(): @@ -2092,12 +2107,16 @@ async def test_export_data_flattened_async(): # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" - assert args[0].output_config == io.OutputConfig( + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val + arg = args[0].output_config + mock_val = io.OutputConfig( gcs_destination=io.GcsDestination( output_uri_prefix="output_uri_prefix_value" ) ) + assert arg == mock_val @pytest.mark.asyncio @@ -2118,9 +2137,8 @@ async def test_export_data_flattened_error_async(): ) -def test_get_annotation_spec( - transport: str = "grpc", request_type=service.GetAnnotationSpecRequest -): +@pytest.mark.parametrize("request_type", [service.GetAnnotationSpecRequest, dict,]) +def test_get_annotation_spec(request_type, transport: str = "grpc"): client = AutoMlClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) @@ -2151,10 +2169,6 @@ def test_get_annotation_spec( assert response.example_count == 1396 -def test_get_annotation_spec_from_dict(): - test_get_annotation_spec(request_type=dict) - - def test_get_annotation_spec_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. @@ -2287,7 +2301,9 @@ def test_get_annotation_spec_flattened(): # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val def test_get_annotation_spec_flattened_error(): @@ -2323,7 +2339,9 @@ async def test_get_annotation_spec_flattened_async(): # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val @pytest.mark.asyncio @@ -2338,7 +2356,8 @@ async def test_get_annotation_spec_flattened_error_async(): ) -def test_create_model(transport: str = "grpc", request_type=service.CreateModelRequest): +@pytest.mark.parametrize("request_type", [service.CreateModelRequest, dict,]) +def test_create_model(request_type, transport: str = "grpc"): client = AutoMlClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) @@ -2362,10 +2381,6 @@ def test_create_model(transport: str = "grpc", request_type=service.CreateModelR assert isinstance(response, future.Future) -def test_create_model_from_dict(): - test_create_model(request_type=dict) - - def test_create_model_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. @@ -2488,12 +2503,16 @@ def test_create_model_flattened(): # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] - assert args[0].parent == "parent_value" - assert args[0].model == gca_model.Model( + arg = args[0].parent + mock_val = "parent_value" + assert arg == mock_val + arg = args[0].model + mock_val = gca_model.Model( translation_model_metadata=translation.TranslationModelMetadata( base_model="base_model_value" ) ) + assert arg == mock_val def test_create_model_flattened_error(): @@ -2540,12 +2559,16 @@ async def test_create_model_flattened_async(): # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] - assert args[0].parent == "parent_value" - assert args[0].model == gca_model.Model( + arg = args[0].parent + mock_val = "parent_value" + assert arg == mock_val + arg = args[0].model + mock_val = gca_model.Model( translation_model_metadata=translation.TranslationModelMetadata( base_model="base_model_value" ) ) + assert arg == mock_val @pytest.mark.asyncio @@ -2566,7 +2589,8 @@ async def test_create_model_flattened_error_async(): ) -def test_get_model(transport: str = "grpc", request_type=service.GetModelRequest): +@pytest.mark.parametrize("request_type", [service.GetModelRequest, dict,]) +def test_get_model(request_type, transport: str = "grpc"): client = AutoMlClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) @@ -2604,10 +2628,6 @@ def test_get_model(transport: str = "grpc", request_type=service.GetModelRequest assert response.etag == "etag_value" -def test_get_model_from_dict(): - test_get_model(request_type=dict) - - def test_get_model_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. @@ -2732,7 +2752,9 @@ def test_get_model_flattened(): # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val def test_get_model_flattened_error(): @@ -2764,7 +2786,9 @@ async def test_get_model_flattened_async(): # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val @pytest.mark.asyncio @@ -2779,7 +2803,8 @@ async def test_get_model_flattened_error_async(): ) -def test_list_models(transport: str = "grpc", request_type=service.ListModelsRequest): +@pytest.mark.parametrize("request_type", [service.ListModelsRequest, dict,]) +def test_list_models(request_type, transport: str = "grpc"): client = AutoMlClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) @@ -2806,10 +2831,6 @@ def test_list_models(transport: str = "grpc", request_type=service.ListModelsReq assert response.next_page_token == "next_page_token_value" -def test_list_models_from_dict(): - test_list_models(request_type=dict) - - def test_list_models_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. @@ -2926,7 +2947,9 @@ def test_list_models_flattened(): # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] - assert args[0].parent == "parent_value" + arg = args[0].parent + mock_val = "parent_value" + assert arg == mock_val def test_list_models_flattened_error(): @@ -2960,7 +2983,9 @@ async def test_list_models_flattened_async(): # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] - assert args[0].parent == "parent_value" + arg = args[0].parent + mock_val = "parent_value" + assert arg == mock_val @pytest.mark.asyncio @@ -2975,8 +3000,10 @@ async def test_list_models_flattened_error_async(): ) -def test_list_models_pager(): - client = AutoMlClient(credentials=ga_credentials.AnonymousCredentials,) +def test_list_models_pager(transport_name: str = "grpc"): + client = AutoMlClient( + credentials=ga_credentials.AnonymousCredentials, transport=transport_name, + ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.list_models), "__call__") as call: @@ -3005,8 +3032,10 @@ def test_list_models_pager(): assert all(isinstance(i, model.Model) for i in results) -def test_list_models_pages(): - client = AutoMlClient(credentials=ga_credentials.AnonymousCredentials,) +def test_list_models_pages(transport_name: str = "grpc"): + client = AutoMlClient( + credentials=ga_credentials.AnonymousCredentials, transport=transport_name, + ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.list_models), "__call__") as call: @@ -3081,7 +3110,8 @@ async def test_list_models_async_pages(): assert page_.raw_page.next_page_token == token -def test_delete_model(transport: str = "grpc", request_type=service.DeleteModelRequest): +@pytest.mark.parametrize("request_type", [service.DeleteModelRequest, dict,]) +def test_delete_model(request_type, transport: str = "grpc"): client = AutoMlClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) @@ -3105,10 +3135,6 @@ def test_delete_model(transport: str = "grpc", request_type=service.DeleteModelR assert isinstance(response, future.Future) -def test_delete_model_from_dict(): - test_delete_model(request_type=dict) - - def test_delete_model_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. @@ -3224,7 +3250,9 @@ def test_delete_model_flattened(): # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val def test_delete_model_flattened_error(): @@ -3258,7 +3286,9 @@ async def test_delete_model_flattened_async(): # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val @pytest.mark.asyncio @@ -3273,7 +3303,8 @@ async def test_delete_model_flattened_error_async(): ) -def test_update_model(transport: str = "grpc", request_type=service.UpdateModelRequest): +@pytest.mark.parametrize("request_type", [service.UpdateModelRequest, dict,]) +def test_update_model(request_type, transport: str = "grpc"): client = AutoMlClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) @@ -3311,10 +3342,6 @@ def test_update_model(transport: str = "grpc", request_type=service.UpdateModelR assert response.etag == "etag_value" -def test_update_model_from_dict(): - test_update_model(request_type=dict) - - def test_update_model_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. @@ -3446,12 +3473,16 @@ def test_update_model_flattened(): # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] - assert args[0].model == gca_model.Model( + arg = args[0].model + mock_val = gca_model.Model( translation_model_metadata=translation.TranslationModelMetadata( base_model="base_model_value" ) ) - assert args[0].update_mask == field_mask_pb2.FieldMask(paths=["paths_value"]) + assert arg == mock_val + arg = args[0].update_mask + mock_val = field_mask_pb2.FieldMask(paths=["paths_value"]) + assert arg == mock_val def test_update_model_flattened_error(): @@ -3496,12 +3527,16 @@ async def test_update_model_flattened_async(): # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] - assert args[0].model == gca_model.Model( + arg = args[0].model + mock_val = gca_model.Model( translation_model_metadata=translation.TranslationModelMetadata( base_model="base_model_value" ) ) - assert args[0].update_mask == field_mask_pb2.FieldMask(paths=["paths_value"]) + assert arg == mock_val + arg = args[0].update_mask + mock_val = field_mask_pb2.FieldMask(paths=["paths_value"]) + assert arg == mock_val @pytest.mark.asyncio @@ -3522,7 +3557,8 @@ async def test_update_model_flattened_error_async(): ) -def test_deploy_model(transport: str = "grpc", request_type=service.DeployModelRequest): +@pytest.mark.parametrize("request_type", [service.DeployModelRequest, dict,]) +def test_deploy_model(request_type, transport: str = "grpc"): client = AutoMlClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) @@ -3546,10 +3582,6 @@ def test_deploy_model(transport: str = "grpc", request_type=service.DeployModelR assert isinstance(response, future.Future) -def test_deploy_model_from_dict(): - test_deploy_model(request_type=dict) - - def test_deploy_model_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. @@ -3665,7 +3697,9 @@ def test_deploy_model_flattened(): # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val def test_deploy_model_flattened_error(): @@ -3699,7 +3733,9 @@ async def test_deploy_model_flattened_async(): # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val @pytest.mark.asyncio @@ -3714,9 +3750,8 @@ async def test_deploy_model_flattened_error_async(): ) -def test_undeploy_model( - transport: str = "grpc", request_type=service.UndeployModelRequest -): +@pytest.mark.parametrize("request_type", [service.UndeployModelRequest, dict,]) +def test_undeploy_model(request_type, transport: str = "grpc"): client = AutoMlClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) @@ -3740,10 +3775,6 @@ def test_undeploy_model( assert isinstance(response, future.Future) -def test_undeploy_model_from_dict(): - test_undeploy_model(request_type=dict) - - def test_undeploy_model_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. @@ -3859,7 +3890,9 @@ def test_undeploy_model_flattened(): # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val def test_undeploy_model_flattened_error(): @@ -3893,7 +3926,9 @@ async def test_undeploy_model_flattened_async(): # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val @pytest.mark.asyncio @@ -3908,7 +3943,8 @@ async def test_undeploy_model_flattened_error_async(): ) -def test_export_model(transport: str = "grpc", request_type=service.ExportModelRequest): +@pytest.mark.parametrize("request_type", [service.ExportModelRequest, dict,]) +def test_export_model(request_type, transport: str = "grpc"): client = AutoMlClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) @@ -3932,10 +3968,6 @@ def test_export_model(transport: str = "grpc", request_type=service.ExportModelR assert isinstance(response, future.Future) -def test_export_model_from_dict(): - test_export_model(request_type=dict) - - def test_export_model_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. @@ -4058,12 +4090,16 @@ def test_export_model_flattened(): # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" - assert args[0].output_config == io.ModelExportOutputConfig( + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val + arg = args[0].output_config + mock_val = io.ModelExportOutputConfig( gcs_destination=io.GcsDestination( output_uri_prefix="output_uri_prefix_value" ) ) + assert arg == mock_val def test_export_model_flattened_error(): @@ -4110,12 +4146,16 @@ async def test_export_model_flattened_async(): # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" - assert args[0].output_config == io.ModelExportOutputConfig( + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val + arg = args[0].output_config + mock_val = io.ModelExportOutputConfig( gcs_destination=io.GcsDestination( output_uri_prefix="output_uri_prefix_value" ) ) + assert arg == mock_val @pytest.mark.asyncio @@ -4136,9 +4176,8 @@ async def test_export_model_flattened_error_async(): ) -def test_get_model_evaluation( - transport: str = "grpc", request_type=service.GetModelEvaluationRequest -): +@pytest.mark.parametrize("request_type", [service.GetModelEvaluationRequest, dict,]) +def test_get_model_evaluation(request_type, transport: str = "grpc"): client = AutoMlClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) @@ -4176,10 +4215,6 @@ def test_get_model_evaluation( assert response.evaluated_example_count == 2446 -def test_get_model_evaluation_from_dict(): - test_get_model_evaluation(request_type=dict) - - def test_get_model_evaluation_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. @@ -4314,7 +4349,9 @@ def test_get_model_evaluation_flattened(): # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val def test_get_model_evaluation_flattened_error(): @@ -4350,7 +4387,9 @@ async def test_get_model_evaluation_flattened_async(): # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val @pytest.mark.asyncio @@ -4365,9 +4404,8 @@ async def test_get_model_evaluation_flattened_error_async(): ) -def test_list_model_evaluations( - transport: str = "grpc", request_type=service.ListModelEvaluationsRequest -): +@pytest.mark.parametrize("request_type", [service.ListModelEvaluationsRequest, dict,]) +def test_list_model_evaluations(request_type, transport: str = "grpc"): client = AutoMlClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) @@ -4396,10 +4434,6 @@ def test_list_model_evaluations( assert response.next_page_token == "next_page_token_value" -def test_list_model_evaluations_from_dict(): - test_list_model_evaluations(request_type=dict) - - def test_list_model_evaluations_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. @@ -4530,8 +4564,12 @@ def test_list_model_evaluations_flattened(): # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] - assert args[0].parent == "parent_value" - assert args[0].filter == "filter_value" + arg = args[0].parent + mock_val = "parent_value" + assert arg == mock_val + arg = args[0].filter + mock_val = "filter_value" + assert arg == mock_val def test_list_model_evaluations_flattened_error(): @@ -4571,8 +4609,12 @@ async def test_list_model_evaluations_flattened_async(): # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] - assert args[0].parent == "parent_value" - assert args[0].filter == "filter_value" + arg = args[0].parent + mock_val = "parent_value" + assert arg == mock_val + arg = args[0].filter + mock_val = "filter_value" + assert arg == mock_val @pytest.mark.asyncio @@ -4589,8 +4631,10 @@ async def test_list_model_evaluations_flattened_error_async(): ) -def test_list_model_evaluations_pager(): - client = AutoMlClient(credentials=ga_credentials.AnonymousCredentials,) +def test_list_model_evaluations_pager(transport_name: str = "grpc"): + client = AutoMlClient( + credentials=ga_credentials.AnonymousCredentials, transport=transport_name, + ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( @@ -4635,8 +4679,10 @@ def test_list_model_evaluations_pager(): assert all(isinstance(i, model_evaluation.ModelEvaluation) for i in results) -def test_list_model_evaluations_pages(): - client = AutoMlClient(credentials=ga_credentials.AnonymousCredentials,) +def test_list_model_evaluations_pages(transport_name: str = "grpc"): + client = AutoMlClient( + credentials=ga_credentials.AnonymousCredentials, transport=transport_name, + ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( @@ -5390,7 +5436,7 @@ def test_parse_common_location_path(): assert expected == actual -def test_client_withDEFAULT_CLIENT_INFO(): +def test_client_with_default_client_info(): client_info = gapic_v1.client_info.ClientInfo() with mock.patch.object( diff --git a/tests/unit/gapic/automl_v1/test_prediction_service.py b/tests/unit/gapic/automl_v1/test_prediction_service.py index bbcfb3e4..08f6bd1f 100644 --- a/tests/unit/gapic/automl_v1/test_prediction_service.py +++ b/tests/unit/gapic/automl_v1/test_prediction_service.py @@ -258,20 +258,20 @@ def test_prediction_service_client_client_options( # unsupported value. with mock.patch.dict(os.environ, {"GOOGLE_API_USE_MTLS_ENDPOINT": "Unsupported"}): with pytest.raises(MutualTLSChannelError): - client = client_class() + client = client_class(transport=transport_name) # Check the case GOOGLE_API_USE_CLIENT_CERTIFICATE has unsupported value. with mock.patch.dict( os.environ, {"GOOGLE_API_USE_CLIENT_CERTIFICATE": "Unsupported"} ): with pytest.raises(ValueError): - client = client_class() + client = client_class(transport=transport_name) # Check the case quota_project_id is provided options = client_options.ClientOptions(quota_project_id="octopus") with mock.patch.object(transport_class, "__init__") as patched: patched.return_value = None - client = client_class(transport=transport_name, client_options=options) + client = client_class(client_options=options, transport=transport_name) patched.assert_called_once_with( credentials=None, credentials_file=None, @@ -340,7 +340,7 @@ def test_prediction_service_client_mtls_env_auto( ) with mock.patch.object(transport_class, "__init__") as patched: patched.return_value = None - client = client_class(transport=transport_name, client_options=options) + client = client_class(client_options=options, transport=transport_name) if use_client_cert_env == "false": expected_client_cert_source = None @@ -435,7 +435,7 @@ def test_prediction_service_client_client_options_scopes( options = client_options.ClientOptions(scopes=["1", "2"],) with mock.patch.object(transport_class, "__init__") as patched: patched.return_value = None - client = client_class(transport=transport_name, client_options=options) + client = client_class(client_options=options, transport=transport_name) patched.assert_called_once_with( credentials=None, credentials_file=None, @@ -466,7 +466,7 @@ def test_prediction_service_client_client_options_credentials_file( options = client_options.ClientOptions(credentials_file="credentials.json") with mock.patch.object(transport_class, "__init__") as patched: patched.return_value = None - client = client_class(transport=transport_name, client_options=options) + client = client_class(client_options=options, transport=transport_name) patched.assert_called_once_with( credentials=None, credentials_file="credentials.json", @@ -499,9 +499,8 @@ def test_prediction_service_client_client_options_from_dict(): ) -def test_predict( - transport: str = "grpc", request_type=prediction_service.PredictRequest -): +@pytest.mark.parametrize("request_type", [prediction_service.PredictRequest, dict,]) +def test_predict(request_type, transport: str = "grpc"): client = PredictionServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) @@ -525,10 +524,6 @@ def test_predict( assert isinstance(response, prediction_service.PredictResponse) -def test_predict_from_dict(): - test_predict(request_type=dict) - - def test_predict_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. @@ -652,11 +647,17 @@ def test_predict_flattened(): # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" - assert args[0].payload == data_items.ExamplePayload( + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val + arg = args[0].payload + mock_val = data_items.ExamplePayload( image=data_items.Image(image_bytes=b"image_bytes_blob") ) - assert args[0].params == {"key_value": "value_value"} + assert arg == mock_val + arg = args[0].params + mock_val = {"key_value": "value_value"} + assert arg == mock_val def test_predict_flattened_error(): @@ -703,11 +704,17 @@ async def test_predict_flattened_async(): # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" - assert args[0].payload == data_items.ExamplePayload( + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val + arg = args[0].payload + mock_val = data_items.ExamplePayload( image=data_items.Image(image_bytes=b"image_bytes_blob") ) - assert args[0].params == {"key_value": "value_value"} + assert arg == mock_val + arg = args[0].params + mock_val = {"key_value": "value_value"} + assert arg == mock_val @pytest.mark.asyncio @@ -729,9 +736,10 @@ async def test_predict_flattened_error_async(): ) -def test_batch_predict( - transport: str = "grpc", request_type=prediction_service.BatchPredictRequest -): +@pytest.mark.parametrize( + "request_type", [prediction_service.BatchPredictRequest, dict,] +) +def test_batch_predict(request_type, transport: str = "grpc"): client = PredictionServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) @@ -755,10 +763,6 @@ def test_batch_predict( assert isinstance(response, future.Future) -def test_batch_predict_from_dict(): - test_batch_predict(request_type=dict) - - def test_batch_predict_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. @@ -887,16 +891,24 @@ def test_batch_predict_flattened(): # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" - assert args[0].input_config == io.BatchPredictInputConfig( + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val + arg = args[0].input_config + mock_val = io.BatchPredictInputConfig( gcs_source=io.GcsSource(input_uris=["input_uris_value"]) ) - assert args[0].output_config == io.BatchPredictOutputConfig( + assert arg == mock_val + arg = args[0].output_config + mock_val = io.BatchPredictOutputConfig( gcs_destination=io.GcsDestination( output_uri_prefix="output_uri_prefix_value" ) ) - assert args[0].params == {"key_value": "value_value"} + assert arg == mock_val + arg = args[0].params + mock_val = {"key_value": "value_value"} + assert arg == mock_val def test_batch_predict_flattened_error(): @@ -953,16 +965,24 @@ async def test_batch_predict_flattened_async(): # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" - assert args[0].input_config == io.BatchPredictInputConfig( + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val + arg = args[0].input_config + mock_val = io.BatchPredictInputConfig( gcs_source=io.GcsSource(input_uris=["input_uris_value"]) ) - assert args[0].output_config == io.BatchPredictOutputConfig( + assert arg == mock_val + arg = args[0].output_config + mock_val = io.BatchPredictOutputConfig( gcs_destination=io.GcsDestination( output_uri_prefix="output_uri_prefix_value" ) ) - assert args[0].params == {"key_value": "value_value"} + assert arg == mock_val + arg = args[0].params + mock_val = {"key_value": "value_value"} + assert arg == mock_val @pytest.mark.asyncio @@ -1535,7 +1555,7 @@ def test_parse_common_location_path(): assert expected == actual -def test_client_withDEFAULT_CLIENT_INFO(): +def test_client_with_default_client_info(): client_info = gapic_v1.client_info.ClientInfo() with mock.patch.object( diff --git a/tests/unit/gapic/automl_v1beta1/test_auto_ml.py b/tests/unit/gapic/automl_v1beta1/test_auto_ml.py index 5be6ec51..4a36cc1f 100644 --- a/tests/unit/gapic/automl_v1beta1/test_auto_ml.py +++ b/tests/unit/gapic/automl_v1beta1/test_auto_ml.py @@ -254,20 +254,20 @@ def test_auto_ml_client_client_options(client_class, transport_class, transport_ # unsupported value. with mock.patch.dict(os.environ, {"GOOGLE_API_USE_MTLS_ENDPOINT": "Unsupported"}): with pytest.raises(MutualTLSChannelError): - client = client_class() + client = client_class(transport=transport_name) # Check the case GOOGLE_API_USE_CLIENT_CERTIFICATE has unsupported value. with mock.patch.dict( os.environ, {"GOOGLE_API_USE_CLIENT_CERTIFICATE": "Unsupported"} ): with pytest.raises(ValueError): - client = client_class() + client = client_class(transport=transport_name) # Check the case quota_project_id is provided options = client_options.ClientOptions(quota_project_id="octopus") with mock.patch.object(transport_class, "__init__") as patched: patched.return_value = None - client = client_class(transport=transport_name, client_options=options) + client = client_class(client_options=options, transport=transport_name) patched.assert_called_once_with( credentials=None, credentials_file=None, @@ -322,7 +322,7 @@ def test_auto_ml_client_mtls_env_auto( ) with mock.patch.object(transport_class, "__init__") as patched: patched.return_value = None - client = client_class(transport=transport_name, client_options=options) + client = client_class(client_options=options, transport=transport_name) if use_client_cert_env == "false": expected_client_cert_source = None @@ -413,7 +413,7 @@ def test_auto_ml_client_client_options_scopes( options = client_options.ClientOptions(scopes=["1", "2"],) with mock.patch.object(transport_class, "__init__") as patched: patched.return_value = None - client = client_class(transport=transport_name, client_options=options) + client = client_class(client_options=options, transport=transport_name) patched.assert_called_once_with( credentials=None, credentials_file=None, @@ -440,7 +440,7 @@ def test_auto_ml_client_client_options_credentials_file( options = client_options.ClientOptions(credentials_file="credentials.json") with mock.patch.object(transport_class, "__init__") as patched: patched.return_value = None - client = client_class(transport=transport_name, client_options=options) + client = client_class(client_options=options, transport=transport_name) patched.assert_called_once_with( credentials=None, credentials_file="credentials.json", @@ -471,9 +471,8 @@ def test_auto_ml_client_client_options_from_dict(): ) -def test_create_dataset( - transport: str = "grpc", request_type=service.CreateDatasetRequest -): +@pytest.mark.parametrize("request_type", [service.CreateDatasetRequest, dict,]) +def test_create_dataset(request_type, transport: str = "grpc"): client = AutoMlClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) @@ -511,10 +510,6 @@ def test_create_dataset( assert response.etag == "etag_value" -def test_create_dataset_from_dict(): - test_create_dataset(request_type=dict) - - def test_create_dataset_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. @@ -646,12 +641,16 @@ def test_create_dataset_flattened(): # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] - assert args[0].parent == "parent_value" - assert args[0].dataset == gca_dataset.Dataset( + arg = args[0].parent + mock_val = "parent_value" + assert arg == mock_val + arg = args[0].dataset + mock_val = gca_dataset.Dataset( translation_dataset_metadata=translation.TranslationDatasetMetadata( source_language_code="source_language_code_value" ) ) + assert arg == mock_val def test_create_dataset_flattened_error(): @@ -696,12 +695,16 @@ async def test_create_dataset_flattened_async(): # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] - assert args[0].parent == "parent_value" - assert args[0].dataset == gca_dataset.Dataset( + arg = args[0].parent + mock_val = "parent_value" + assert arg == mock_val + arg = args[0].dataset + mock_val = gca_dataset.Dataset( translation_dataset_metadata=translation.TranslationDatasetMetadata( source_language_code="source_language_code_value" ) ) + assert arg == mock_val @pytest.mark.asyncio @@ -722,7 +725,8 @@ async def test_create_dataset_flattened_error_async(): ) -def test_get_dataset(transport: str = "grpc", request_type=service.GetDatasetRequest): +@pytest.mark.parametrize("request_type", [service.GetDatasetRequest, dict,]) +def test_get_dataset(request_type, transport: str = "grpc"): client = AutoMlClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) @@ -760,10 +764,6 @@ def test_get_dataset(transport: str = "grpc", request_type=service.GetDatasetReq assert response.etag == "etag_value" -def test_get_dataset_from_dict(): - test_get_dataset(request_type=dict) - - def test_get_dataset_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. @@ -888,7 +888,9 @@ def test_get_dataset_flattened(): # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val def test_get_dataset_flattened_error(): @@ -920,7 +922,9 @@ async def test_get_dataset_flattened_async(): # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val @pytest.mark.asyncio @@ -935,9 +939,8 @@ async def test_get_dataset_flattened_error_async(): ) -def test_list_datasets( - transport: str = "grpc", request_type=service.ListDatasetsRequest -): +@pytest.mark.parametrize("request_type", [service.ListDatasetsRequest, dict,]) +def test_list_datasets(request_type, transport: str = "grpc"): client = AutoMlClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) @@ -964,10 +967,6 @@ def test_list_datasets( assert response.next_page_token == "next_page_token_value" -def test_list_datasets_from_dict(): - test_list_datasets(request_type=dict) - - def test_list_datasets_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. @@ -1084,7 +1083,9 @@ def test_list_datasets_flattened(): # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] - assert args[0].parent == "parent_value" + arg = args[0].parent + mock_val = "parent_value" + assert arg == mock_val def test_list_datasets_flattened_error(): @@ -1118,7 +1119,9 @@ async def test_list_datasets_flattened_async(): # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] - assert args[0].parent == "parent_value" + arg = args[0].parent + mock_val = "parent_value" + assert arg == mock_val @pytest.mark.asyncio @@ -1133,8 +1136,10 @@ async def test_list_datasets_flattened_error_async(): ) -def test_list_datasets_pager(): - client = AutoMlClient(credentials=ga_credentials.AnonymousCredentials,) +def test_list_datasets_pager(transport_name: str = "grpc"): + client = AutoMlClient( + credentials=ga_credentials.AnonymousCredentials, transport=transport_name, + ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.list_datasets), "__call__") as call: @@ -1167,8 +1172,10 @@ def test_list_datasets_pager(): assert all(isinstance(i, dataset.Dataset) for i in results) -def test_list_datasets_pages(): - client = AutoMlClient(credentials=ga_credentials.AnonymousCredentials,) +def test_list_datasets_pages(transport_name: str = "grpc"): + client = AutoMlClient( + credentials=ga_credentials.AnonymousCredentials, transport=transport_name, + ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.list_datasets), "__call__") as call: @@ -1255,9 +1262,8 @@ async def test_list_datasets_async_pages(): assert page_.raw_page.next_page_token == token -def test_update_dataset( - transport: str = "grpc", request_type=service.UpdateDatasetRequest -): +@pytest.mark.parametrize("request_type", [service.UpdateDatasetRequest, dict,]) +def test_update_dataset(request_type, transport: str = "grpc"): client = AutoMlClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) @@ -1295,10 +1301,6 @@ def test_update_dataset( assert response.etag == "etag_value" -def test_update_dataset_from_dict(): - test_update_dataset(request_type=dict) - - def test_update_dataset_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. @@ -1433,11 +1435,13 @@ def test_update_dataset_flattened(): # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] - assert args[0].dataset == gca_dataset.Dataset( + arg = args[0].dataset + mock_val = gca_dataset.Dataset( translation_dataset_metadata=translation.TranslationDatasetMetadata( source_language_code="source_language_code_value" ) ) + assert arg == mock_val def test_update_dataset_flattened_error(): @@ -1480,11 +1484,13 @@ async def test_update_dataset_flattened_async(): # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] - assert args[0].dataset == gca_dataset.Dataset( + arg = args[0].dataset + mock_val = gca_dataset.Dataset( translation_dataset_metadata=translation.TranslationDatasetMetadata( source_language_code="source_language_code_value" ) ) + assert arg == mock_val @pytest.mark.asyncio @@ -1504,9 +1510,8 @@ async def test_update_dataset_flattened_error_async(): ) -def test_delete_dataset( - transport: str = "grpc", request_type=service.DeleteDatasetRequest -): +@pytest.mark.parametrize("request_type", [service.DeleteDatasetRequest, dict,]) +def test_delete_dataset(request_type, transport: str = "grpc"): client = AutoMlClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) @@ -1530,10 +1535,6 @@ def test_delete_dataset( assert isinstance(response, future.Future) -def test_delete_dataset_from_dict(): - test_delete_dataset(request_type=dict) - - def test_delete_dataset_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. @@ -1649,7 +1650,9 @@ def test_delete_dataset_flattened(): # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val def test_delete_dataset_flattened_error(): @@ -1683,7 +1686,9 @@ async def test_delete_dataset_flattened_async(): # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val @pytest.mark.asyncio @@ -1698,7 +1703,8 @@ async def test_delete_dataset_flattened_error_async(): ) -def test_import_data(transport: str = "grpc", request_type=service.ImportDataRequest): +@pytest.mark.parametrize("request_type", [service.ImportDataRequest, dict,]) +def test_import_data(request_type, transport: str = "grpc"): client = AutoMlClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) @@ -1722,10 +1728,6 @@ def test_import_data(transport: str = "grpc", request_type=service.ImportDataReq assert isinstance(response, future.Future) -def test_import_data_from_dict(): - test_import_data(request_type=dict) - - def test_import_data_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. @@ -1846,10 +1848,14 @@ def test_import_data_flattened(): # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" - assert args[0].input_config == io.InputConfig( + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val + arg = args[0].input_config + mock_val = io.InputConfig( gcs_source=io.GcsSource(input_uris=["input_uris_value"]) ) + assert arg == mock_val def test_import_data_flattened_error(): @@ -1892,10 +1898,14 @@ async def test_import_data_flattened_async(): # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" - assert args[0].input_config == io.InputConfig( + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val + arg = args[0].input_config + mock_val = io.InputConfig( gcs_source=io.GcsSource(input_uris=["input_uris_value"]) ) + assert arg == mock_val @pytest.mark.asyncio @@ -1914,7 +1924,8 @@ async def test_import_data_flattened_error_async(): ) -def test_export_data(transport: str = "grpc", request_type=service.ExportDataRequest): +@pytest.mark.parametrize("request_type", [service.ExportDataRequest, dict,]) +def test_export_data(request_type, transport: str = "grpc"): client = AutoMlClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) @@ -1938,10 +1949,6 @@ def test_export_data(transport: str = "grpc", request_type=service.ExportDataReq assert isinstance(response, future.Future) -def test_export_data_from_dict(): - test_export_data(request_type=dict) - - def test_export_data_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. @@ -2064,12 +2071,16 @@ def test_export_data_flattened(): # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" - assert args[0].output_config == io.OutputConfig( + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val + arg = args[0].output_config + mock_val = io.OutputConfig( gcs_destination=io.GcsDestination( output_uri_prefix="output_uri_prefix_value" ) ) + assert arg == mock_val def test_export_data_flattened_error(): @@ -2116,12 +2127,16 @@ async def test_export_data_flattened_async(): # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" - assert args[0].output_config == io.OutputConfig( + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val + arg = args[0].output_config + mock_val = io.OutputConfig( gcs_destination=io.GcsDestination( output_uri_prefix="output_uri_prefix_value" ) ) + assert arg == mock_val @pytest.mark.asyncio @@ -2142,9 +2157,8 @@ async def test_export_data_flattened_error_async(): ) -def test_get_annotation_spec( - transport: str = "grpc", request_type=service.GetAnnotationSpecRequest -): +@pytest.mark.parametrize("request_type", [service.GetAnnotationSpecRequest, dict,]) +def test_get_annotation_spec(request_type, transport: str = "grpc"): client = AutoMlClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) @@ -2175,10 +2189,6 @@ def test_get_annotation_spec( assert response.example_count == 1396 -def test_get_annotation_spec_from_dict(): - test_get_annotation_spec(request_type=dict) - - def test_get_annotation_spec_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. @@ -2311,7 +2321,9 @@ def test_get_annotation_spec_flattened(): # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val def test_get_annotation_spec_flattened_error(): @@ -2347,7 +2359,9 @@ async def test_get_annotation_spec_flattened_async(): # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val @pytest.mark.asyncio @@ -2362,9 +2376,8 @@ async def test_get_annotation_spec_flattened_error_async(): ) -def test_get_table_spec( - transport: str = "grpc", request_type=service.GetTableSpecRequest -): +@pytest.mark.parametrize("request_type", [service.GetTableSpecRequest, dict,]) +def test_get_table_spec(request_type, transport: str = "grpc"): client = AutoMlClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) @@ -2401,10 +2414,6 @@ def test_get_table_spec( assert response.etag == "etag_value" -def test_get_table_spec_from_dict(): - test_get_table_spec(request_type=dict) - - def test_get_table_spec_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. @@ -2533,7 +2542,9 @@ def test_get_table_spec_flattened(): # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val def test_get_table_spec_flattened_error(): @@ -2567,7 +2578,9 @@ async def test_get_table_spec_flattened_async(): # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val @pytest.mark.asyncio @@ -2582,9 +2595,8 @@ async def test_get_table_spec_flattened_error_async(): ) -def test_list_table_specs( - transport: str = "grpc", request_type=service.ListTableSpecsRequest -): +@pytest.mark.parametrize("request_type", [service.ListTableSpecsRequest, dict,]) +def test_list_table_specs(request_type, transport: str = "grpc"): client = AutoMlClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) @@ -2611,10 +2623,6 @@ def test_list_table_specs( assert response.next_page_token == "next_page_token_value" -def test_list_table_specs_from_dict(): - test_list_table_specs(request_type=dict) - - def test_list_table_specs_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. @@ -2731,7 +2739,9 @@ def test_list_table_specs_flattened(): # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] - assert args[0].parent == "parent_value" + arg = args[0].parent + mock_val = "parent_value" + assert arg == mock_val def test_list_table_specs_flattened_error(): @@ -2765,7 +2775,9 @@ async def test_list_table_specs_flattened_async(): # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] - assert args[0].parent == "parent_value" + arg = args[0].parent + mock_val = "parent_value" + assert arg == mock_val @pytest.mark.asyncio @@ -2780,8 +2792,10 @@ async def test_list_table_specs_flattened_error_async(): ) -def test_list_table_specs_pager(): - client = AutoMlClient(credentials=ga_credentials.AnonymousCredentials,) +def test_list_table_specs_pager(transport_name: str = "grpc"): + client = AutoMlClient( + credentials=ga_credentials.AnonymousCredentials, transport=transport_name, + ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.list_table_specs), "__call__") as call: @@ -2818,8 +2832,10 @@ def test_list_table_specs_pager(): assert all(isinstance(i, table_spec.TableSpec) for i in results) -def test_list_table_specs_pages(): - client = AutoMlClient(credentials=ga_credentials.AnonymousCredentials,) +def test_list_table_specs_pages(transport_name: str = "grpc"): + client = AutoMlClient( + credentials=ga_credentials.AnonymousCredentials, transport=transport_name, + ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.list_table_specs), "__call__") as call: @@ -2918,9 +2934,8 @@ async def test_list_table_specs_async_pages(): assert page_.raw_page.next_page_token == token -def test_update_table_spec( - transport: str = "grpc", request_type=service.UpdateTableSpecRequest -): +@pytest.mark.parametrize("request_type", [service.UpdateTableSpecRequest, dict,]) +def test_update_table_spec(request_type, transport: str = "grpc"): client = AutoMlClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) @@ -2959,10 +2974,6 @@ def test_update_table_spec( assert response.etag == "etag_value" -def test_update_table_spec_from_dict(): - test_update_table_spec(request_type=dict) - - def test_update_table_spec_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. @@ -3107,7 +3118,9 @@ def test_update_table_spec_flattened(): # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] - assert args[0].table_spec == gca_table_spec.TableSpec(name="name_value") + arg = args[0].table_spec + mock_val = gca_table_spec.TableSpec(name="name_value") + assert arg == mock_val def test_update_table_spec_flattened_error(): @@ -3146,7 +3159,9 @@ async def test_update_table_spec_flattened_async(): # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] - assert args[0].table_spec == gca_table_spec.TableSpec(name="name_value") + arg = args[0].table_spec + mock_val = gca_table_spec.TableSpec(name="name_value") + assert arg == mock_val @pytest.mark.asyncio @@ -3162,9 +3177,8 @@ async def test_update_table_spec_flattened_error_async(): ) -def test_get_column_spec( - transport: str = "grpc", request_type=service.GetColumnSpecRequest -): +@pytest.mark.parametrize("request_type", [service.GetColumnSpecRequest, dict,]) +def test_get_column_spec(request_type, transport: str = "grpc"): client = AutoMlClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) @@ -3193,10 +3207,6 @@ def test_get_column_spec( assert response.etag == "etag_value" -def test_get_column_spec_from_dict(): - test_get_column_spec(request_type=dict) - - def test_get_column_spec_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. @@ -3317,7 +3327,9 @@ def test_get_column_spec_flattened(): # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val def test_get_column_spec_flattened_error(): @@ -3351,7 +3363,9 @@ async def test_get_column_spec_flattened_async(): # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val @pytest.mark.asyncio @@ -3366,9 +3380,8 @@ async def test_get_column_spec_flattened_error_async(): ) -def test_list_column_specs( - transport: str = "grpc", request_type=service.ListColumnSpecsRequest -): +@pytest.mark.parametrize("request_type", [service.ListColumnSpecsRequest, dict,]) +def test_list_column_specs(request_type, transport: str = "grpc"): client = AutoMlClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) @@ -3397,10 +3410,6 @@ def test_list_column_specs( assert response.next_page_token == "next_page_token_value" -def test_list_column_specs_from_dict(): - test_list_column_specs(request_type=dict) - - def test_list_column_specs_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. @@ -3527,7 +3536,9 @@ def test_list_column_specs_flattened(): # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] - assert args[0].parent == "parent_value" + arg = args[0].parent + mock_val = "parent_value" + assert arg == mock_val def test_list_column_specs_flattened_error(): @@ -3563,7 +3574,9 @@ async def test_list_column_specs_flattened_async(): # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] - assert args[0].parent == "parent_value" + arg = args[0].parent + mock_val = "parent_value" + assert arg == mock_val @pytest.mark.asyncio @@ -3578,8 +3591,10 @@ async def test_list_column_specs_flattened_error_async(): ) -def test_list_column_specs_pager(): - client = AutoMlClient(credentials=ga_credentials.AnonymousCredentials,) +def test_list_column_specs_pager(transport_name: str = "grpc"): + client = AutoMlClient( + credentials=ga_credentials.AnonymousCredentials, transport=transport_name, + ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( @@ -3618,8 +3633,10 @@ def test_list_column_specs_pager(): assert all(isinstance(i, column_spec.ColumnSpec) for i in results) -def test_list_column_specs_pages(): - client = AutoMlClient(credentials=ga_credentials.AnonymousCredentials,) +def test_list_column_specs_pages(transport_name: str = "grpc"): + client = AutoMlClient( + credentials=ga_credentials.AnonymousCredentials, transport=transport_name, + ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( @@ -3724,9 +3741,8 @@ async def test_list_column_specs_async_pages(): assert page_.raw_page.next_page_token == token -def test_update_column_spec( - transport: str = "grpc", request_type=service.UpdateColumnSpecRequest -): +@pytest.mark.parametrize("request_type", [service.UpdateColumnSpecRequest, dict,]) +def test_update_column_spec(request_type, transport: str = "grpc"): client = AutoMlClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) @@ -3757,10 +3773,6 @@ def test_update_column_spec( assert response.etag == "etag_value" -def test_update_column_spec_from_dict(): - test_update_column_spec(request_type=dict) - - def test_update_column_spec_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. @@ -3897,7 +3909,9 @@ def test_update_column_spec_flattened(): # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] - assert args[0].column_spec == gca_column_spec.ColumnSpec(name="name_value") + arg = args[0].column_spec + mock_val = gca_column_spec.ColumnSpec(name="name_value") + assert arg == mock_val def test_update_column_spec_flattened_error(): @@ -3936,7 +3950,9 @@ async def test_update_column_spec_flattened_async(): # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] - assert args[0].column_spec == gca_column_spec.ColumnSpec(name="name_value") + arg = args[0].column_spec + mock_val = gca_column_spec.ColumnSpec(name="name_value") + assert arg == mock_val @pytest.mark.asyncio @@ -3952,7 +3968,8 @@ async def test_update_column_spec_flattened_error_async(): ) -def test_create_model(transport: str = "grpc", request_type=service.CreateModelRequest): +@pytest.mark.parametrize("request_type", [service.CreateModelRequest, dict,]) +def test_create_model(request_type, transport: str = "grpc"): client = AutoMlClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) @@ -3976,10 +3993,6 @@ def test_create_model(transport: str = "grpc", request_type=service.CreateModelR assert isinstance(response, future.Future) -def test_create_model_from_dict(): - test_create_model(request_type=dict) - - def test_create_model_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. @@ -4102,12 +4115,16 @@ def test_create_model_flattened(): # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] - assert args[0].parent == "parent_value" - assert args[0].model == gca_model.Model( + arg = args[0].parent + mock_val = "parent_value" + assert arg == mock_val + arg = args[0].model + mock_val = gca_model.Model( translation_model_metadata=translation.TranslationModelMetadata( base_model="base_model_value" ) ) + assert arg == mock_val def test_create_model_flattened_error(): @@ -4154,12 +4171,16 @@ async def test_create_model_flattened_async(): # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] - assert args[0].parent == "parent_value" - assert args[0].model == gca_model.Model( + arg = args[0].parent + mock_val = "parent_value" + assert arg == mock_val + arg = args[0].model + mock_val = gca_model.Model( translation_model_metadata=translation.TranslationModelMetadata( base_model="base_model_value" ) ) + assert arg == mock_val @pytest.mark.asyncio @@ -4180,7 +4201,8 @@ async def test_create_model_flattened_error_async(): ) -def test_get_model(transport: str = "grpc", request_type=service.GetModelRequest): +@pytest.mark.parametrize("request_type", [service.GetModelRequest, dict,]) +def test_get_model(request_type, transport: str = "grpc"): client = AutoMlClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) @@ -4216,10 +4238,6 @@ def test_get_model(transport: str = "grpc", request_type=service.GetModelRequest assert response.deployment_state == model.Model.DeploymentState.DEPLOYED -def test_get_model_from_dict(): - test_get_model(request_type=dict) - - def test_get_model_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. @@ -4342,7 +4360,9 @@ def test_get_model_flattened(): # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val def test_get_model_flattened_error(): @@ -4374,7 +4394,9 @@ async def test_get_model_flattened_async(): # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val @pytest.mark.asyncio @@ -4389,7 +4411,8 @@ async def test_get_model_flattened_error_async(): ) -def test_list_models(transport: str = "grpc", request_type=service.ListModelsRequest): +@pytest.mark.parametrize("request_type", [service.ListModelsRequest, dict,]) +def test_list_models(request_type, transport: str = "grpc"): client = AutoMlClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) @@ -4416,10 +4439,6 @@ def test_list_models(transport: str = "grpc", request_type=service.ListModelsReq assert response.next_page_token == "next_page_token_value" -def test_list_models_from_dict(): - test_list_models(request_type=dict) - - def test_list_models_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. @@ -4536,7 +4555,9 @@ def test_list_models_flattened(): # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] - assert args[0].parent == "parent_value" + arg = args[0].parent + mock_val = "parent_value" + assert arg == mock_val def test_list_models_flattened_error(): @@ -4570,7 +4591,9 @@ async def test_list_models_flattened_async(): # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] - assert args[0].parent == "parent_value" + arg = args[0].parent + mock_val = "parent_value" + assert arg == mock_val @pytest.mark.asyncio @@ -4585,8 +4608,10 @@ async def test_list_models_flattened_error_async(): ) -def test_list_models_pager(): - client = AutoMlClient(credentials=ga_credentials.AnonymousCredentials,) +def test_list_models_pager(transport_name: str = "grpc"): + client = AutoMlClient( + credentials=ga_credentials.AnonymousCredentials, transport=transport_name, + ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.list_models), "__call__") as call: @@ -4615,8 +4640,10 @@ def test_list_models_pager(): assert all(isinstance(i, model.Model) for i in results) -def test_list_models_pages(): - client = AutoMlClient(credentials=ga_credentials.AnonymousCredentials,) +def test_list_models_pages(transport_name: str = "grpc"): + client = AutoMlClient( + credentials=ga_credentials.AnonymousCredentials, transport=transport_name, + ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.list_models), "__call__") as call: @@ -4691,7 +4718,8 @@ async def test_list_models_async_pages(): assert page_.raw_page.next_page_token == token -def test_delete_model(transport: str = "grpc", request_type=service.DeleteModelRequest): +@pytest.mark.parametrize("request_type", [service.DeleteModelRequest, dict,]) +def test_delete_model(request_type, transport: str = "grpc"): client = AutoMlClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) @@ -4715,10 +4743,6 @@ def test_delete_model(transport: str = "grpc", request_type=service.DeleteModelR assert isinstance(response, future.Future) -def test_delete_model_from_dict(): - test_delete_model(request_type=dict) - - def test_delete_model_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. @@ -4834,7 +4858,9 @@ def test_delete_model_flattened(): # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val def test_delete_model_flattened_error(): @@ -4868,7 +4894,9 @@ async def test_delete_model_flattened_async(): # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val @pytest.mark.asyncio @@ -4883,7 +4911,8 @@ async def test_delete_model_flattened_error_async(): ) -def test_deploy_model(transport: str = "grpc", request_type=service.DeployModelRequest): +@pytest.mark.parametrize("request_type", [service.DeployModelRequest, dict,]) +def test_deploy_model(request_type, transport: str = "grpc"): client = AutoMlClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) @@ -4907,10 +4936,6 @@ def test_deploy_model(transport: str = "grpc", request_type=service.DeployModelR assert isinstance(response, future.Future) -def test_deploy_model_from_dict(): - test_deploy_model(request_type=dict) - - def test_deploy_model_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. @@ -5026,7 +5051,9 @@ def test_deploy_model_flattened(): # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val def test_deploy_model_flattened_error(): @@ -5060,7 +5087,9 @@ async def test_deploy_model_flattened_async(): # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val @pytest.mark.asyncio @@ -5075,9 +5104,8 @@ async def test_deploy_model_flattened_error_async(): ) -def test_undeploy_model( - transport: str = "grpc", request_type=service.UndeployModelRequest -): +@pytest.mark.parametrize("request_type", [service.UndeployModelRequest, dict,]) +def test_undeploy_model(request_type, transport: str = "grpc"): client = AutoMlClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) @@ -5101,10 +5129,6 @@ def test_undeploy_model( assert isinstance(response, future.Future) -def test_undeploy_model_from_dict(): - test_undeploy_model(request_type=dict) - - def test_undeploy_model_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. @@ -5220,7 +5244,9 @@ def test_undeploy_model_flattened(): # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val def test_undeploy_model_flattened_error(): @@ -5254,7 +5280,9 @@ async def test_undeploy_model_flattened_async(): # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val @pytest.mark.asyncio @@ -5269,7 +5297,8 @@ async def test_undeploy_model_flattened_error_async(): ) -def test_export_model(transport: str = "grpc", request_type=service.ExportModelRequest): +@pytest.mark.parametrize("request_type", [service.ExportModelRequest, dict,]) +def test_export_model(request_type, transport: str = "grpc"): client = AutoMlClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) @@ -5293,10 +5322,6 @@ def test_export_model(transport: str = "grpc", request_type=service.ExportModelR assert isinstance(response, future.Future) -def test_export_model_from_dict(): - test_export_model(request_type=dict) - - def test_export_model_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. @@ -5419,12 +5444,16 @@ def test_export_model_flattened(): # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" - assert args[0].output_config == io.ModelExportOutputConfig( + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val + arg = args[0].output_config + mock_val = io.ModelExportOutputConfig( gcs_destination=io.GcsDestination( output_uri_prefix="output_uri_prefix_value" ) ) + assert arg == mock_val def test_export_model_flattened_error(): @@ -5471,12 +5500,16 @@ async def test_export_model_flattened_async(): # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" - assert args[0].output_config == io.ModelExportOutputConfig( + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val + arg = args[0].output_config + mock_val = io.ModelExportOutputConfig( gcs_destination=io.GcsDestination( output_uri_prefix="output_uri_prefix_value" ) ) + assert arg == mock_val @pytest.mark.asyncio @@ -5497,9 +5530,10 @@ async def test_export_model_flattened_error_async(): ) -def test_export_evaluated_examples( - transport: str = "grpc", request_type=service.ExportEvaluatedExamplesRequest -): +@pytest.mark.parametrize( + "request_type", [service.ExportEvaluatedExamplesRequest, dict,] +) +def test_export_evaluated_examples(request_type, transport: str = "grpc"): client = AutoMlClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) @@ -5525,10 +5559,6 @@ def test_export_evaluated_examples( assert isinstance(response, future.Future) -def test_export_evaluated_examples_from_dict(): - test_export_evaluated_examples(request_type=dict) - - def test_export_evaluated_examples_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. @@ -5661,10 +5691,14 @@ def test_export_evaluated_examples_flattened(): # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" - assert args[0].output_config == io.ExportEvaluatedExamplesOutputConfig( + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val + arg = args[0].output_config + mock_val = io.ExportEvaluatedExamplesOutputConfig( bigquery_destination=io.BigQueryDestination(output_uri="output_uri_value") ) + assert arg == mock_val def test_export_evaluated_examples_flattened_error(): @@ -5713,10 +5747,14 @@ async def test_export_evaluated_examples_flattened_async(): # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" - assert args[0].output_config == io.ExportEvaluatedExamplesOutputConfig( + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val + arg = args[0].output_config + mock_val = io.ExportEvaluatedExamplesOutputConfig( bigquery_destination=io.BigQueryDestination(output_uri="output_uri_value") ) + assert arg == mock_val @pytest.mark.asyncio @@ -5737,9 +5775,8 @@ async def test_export_evaluated_examples_flattened_error_async(): ) -def test_get_model_evaluation( - transport: str = "grpc", request_type=service.GetModelEvaluationRequest -): +@pytest.mark.parametrize("request_type", [service.GetModelEvaluationRequest, dict,]) +def test_get_model_evaluation(request_type, transport: str = "grpc"): client = AutoMlClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) @@ -5777,10 +5814,6 @@ def test_get_model_evaluation( assert response.evaluated_example_count == 2446 -def test_get_model_evaluation_from_dict(): - test_get_model_evaluation(request_type=dict) - - def test_get_model_evaluation_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. @@ -5915,7 +5948,9 @@ def test_get_model_evaluation_flattened(): # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val def test_get_model_evaluation_flattened_error(): @@ -5951,7 +5986,9 @@ async def test_get_model_evaluation_flattened_async(): # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val @pytest.mark.asyncio @@ -5966,9 +6003,8 @@ async def test_get_model_evaluation_flattened_error_async(): ) -def test_list_model_evaluations( - transport: str = "grpc", request_type=service.ListModelEvaluationsRequest -): +@pytest.mark.parametrize("request_type", [service.ListModelEvaluationsRequest, dict,]) +def test_list_model_evaluations(request_type, transport: str = "grpc"): client = AutoMlClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) @@ -5997,10 +6033,6 @@ def test_list_model_evaluations( assert response.next_page_token == "next_page_token_value" -def test_list_model_evaluations_from_dict(): - test_list_model_evaluations(request_type=dict) - - def test_list_model_evaluations_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. @@ -6129,7 +6161,9 @@ def test_list_model_evaluations_flattened(): # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] - assert args[0].parent == "parent_value" + arg = args[0].parent + mock_val = "parent_value" + assert arg == mock_val def test_list_model_evaluations_flattened_error(): @@ -6165,7 +6199,9 @@ async def test_list_model_evaluations_flattened_async(): # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] - assert args[0].parent == "parent_value" + arg = args[0].parent + mock_val = "parent_value" + assert arg == mock_val @pytest.mark.asyncio @@ -6180,8 +6216,10 @@ async def test_list_model_evaluations_flattened_error_async(): ) -def test_list_model_evaluations_pager(): - client = AutoMlClient(credentials=ga_credentials.AnonymousCredentials,) +def test_list_model_evaluations_pager(transport_name: str = "grpc"): + client = AutoMlClient( + credentials=ga_credentials.AnonymousCredentials, transport=transport_name, + ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( @@ -6226,8 +6264,10 @@ def test_list_model_evaluations_pager(): assert all(isinstance(i, model_evaluation.ModelEvaluation) for i in results) -def test_list_model_evaluations_pages(): - client = AutoMlClient(credentials=ga_credentials.AnonymousCredentials,) +def test_list_model_evaluations_pages(transport_name: str = "grpc"): + client = AutoMlClient( + credentials=ga_credentials.AnonymousCredentials, transport=transport_name, + ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( @@ -7047,7 +7087,7 @@ def test_parse_common_location_path(): assert expected == actual -def test_client_withDEFAULT_CLIENT_INFO(): +def test_client_with_default_client_info(): client_info = gapic_v1.client_info.ClientInfo() with mock.patch.object( diff --git a/tests/unit/gapic/automl_v1beta1/test_prediction_service.py b/tests/unit/gapic/automl_v1beta1/test_prediction_service.py index 8dfca224..7032ef5e 100644 --- a/tests/unit/gapic/automl_v1beta1/test_prediction_service.py +++ b/tests/unit/gapic/automl_v1beta1/test_prediction_service.py @@ -261,20 +261,20 @@ def test_prediction_service_client_client_options( # unsupported value. with mock.patch.dict(os.environ, {"GOOGLE_API_USE_MTLS_ENDPOINT": "Unsupported"}): with pytest.raises(MutualTLSChannelError): - client = client_class() + client = client_class(transport=transport_name) # Check the case GOOGLE_API_USE_CLIENT_CERTIFICATE has unsupported value. with mock.patch.dict( os.environ, {"GOOGLE_API_USE_CLIENT_CERTIFICATE": "Unsupported"} ): with pytest.raises(ValueError): - client = client_class() + client = client_class(transport=transport_name) # Check the case quota_project_id is provided options = client_options.ClientOptions(quota_project_id="octopus") with mock.patch.object(transport_class, "__init__") as patched: patched.return_value = None - client = client_class(transport=transport_name, client_options=options) + client = client_class(client_options=options, transport=transport_name) patched.assert_called_once_with( credentials=None, credentials_file=None, @@ -343,7 +343,7 @@ def test_prediction_service_client_mtls_env_auto( ) with mock.patch.object(transport_class, "__init__") as patched: patched.return_value = None - client = client_class(transport=transport_name, client_options=options) + client = client_class(client_options=options, transport=transport_name) if use_client_cert_env == "false": expected_client_cert_source = None @@ -438,7 +438,7 @@ def test_prediction_service_client_client_options_scopes( options = client_options.ClientOptions(scopes=["1", "2"],) with mock.patch.object(transport_class, "__init__") as patched: patched.return_value = None - client = client_class(transport=transport_name, client_options=options) + client = client_class(client_options=options, transport=transport_name) patched.assert_called_once_with( credentials=None, credentials_file=None, @@ -469,7 +469,7 @@ def test_prediction_service_client_client_options_credentials_file( options = client_options.ClientOptions(credentials_file="credentials.json") with mock.patch.object(transport_class, "__init__") as patched: patched.return_value = None - client = client_class(transport=transport_name, client_options=options) + client = client_class(client_options=options, transport=transport_name) patched.assert_called_once_with( credentials=None, credentials_file="credentials.json", @@ -502,9 +502,8 @@ def test_prediction_service_client_client_options_from_dict(): ) -def test_predict( - transport: str = "grpc", request_type=prediction_service.PredictRequest -): +@pytest.mark.parametrize("request_type", [prediction_service.PredictRequest, dict,]) +def test_predict(request_type, transport: str = "grpc"): client = PredictionServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) @@ -528,10 +527,6 @@ def test_predict( assert isinstance(response, prediction_service.PredictResponse) -def test_predict_from_dict(): - test_predict(request_type=dict) - - def test_predict_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. @@ -655,11 +650,17 @@ def test_predict_flattened(): # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" - assert args[0].payload == data_items.ExamplePayload( + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val + arg = args[0].payload + mock_val = data_items.ExamplePayload( image=data_items.Image(image_bytes=b"image_bytes_blob") ) - assert args[0].params == {"key_value": "value_value"} + assert arg == mock_val + arg = args[0].params + mock_val = {"key_value": "value_value"} + assert arg == mock_val def test_predict_flattened_error(): @@ -706,11 +707,17 @@ async def test_predict_flattened_async(): # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" - assert args[0].payload == data_items.ExamplePayload( + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val + arg = args[0].payload + mock_val = data_items.ExamplePayload( image=data_items.Image(image_bytes=b"image_bytes_blob") ) - assert args[0].params == {"key_value": "value_value"} + assert arg == mock_val + arg = args[0].params + mock_val = {"key_value": "value_value"} + assert arg == mock_val @pytest.mark.asyncio @@ -732,9 +739,10 @@ async def test_predict_flattened_error_async(): ) -def test_batch_predict( - transport: str = "grpc", request_type=prediction_service.BatchPredictRequest -): +@pytest.mark.parametrize( + "request_type", [prediction_service.BatchPredictRequest, dict,] +) +def test_batch_predict(request_type, transport: str = "grpc"): client = PredictionServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) @@ -758,10 +766,6 @@ def test_batch_predict( assert isinstance(response, future.Future) -def test_batch_predict_from_dict(): - test_batch_predict(request_type=dict) - - def test_batch_predict_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. @@ -890,16 +894,24 @@ def test_batch_predict_flattened(): # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" - assert args[0].input_config == io.BatchPredictInputConfig( + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val + arg = args[0].input_config + mock_val = io.BatchPredictInputConfig( gcs_source=io.GcsSource(input_uris=["input_uris_value"]) ) - assert args[0].output_config == io.BatchPredictOutputConfig( + assert arg == mock_val + arg = args[0].output_config + mock_val = io.BatchPredictOutputConfig( gcs_destination=io.GcsDestination( output_uri_prefix="output_uri_prefix_value" ) ) - assert args[0].params == {"key_value": "value_value"} + assert arg == mock_val + arg = args[0].params + mock_val = {"key_value": "value_value"} + assert arg == mock_val def test_batch_predict_flattened_error(): @@ -956,16 +968,24 @@ async def test_batch_predict_flattened_async(): # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] - assert args[0].name == "name_value" - assert args[0].input_config == io.BatchPredictInputConfig( + arg = args[0].name + mock_val = "name_value" + assert arg == mock_val + arg = args[0].input_config + mock_val = io.BatchPredictInputConfig( gcs_source=io.GcsSource(input_uris=["input_uris_value"]) ) - assert args[0].output_config == io.BatchPredictOutputConfig( + assert arg == mock_val + arg = args[0].output_config + mock_val = io.BatchPredictOutputConfig( gcs_destination=io.GcsDestination( output_uri_prefix="output_uri_prefix_value" ) ) - assert args[0].params == {"key_value": "value_value"} + assert arg == mock_val + arg = args[0].params + mock_val = {"key_value": "value_value"} + assert arg == mock_val @pytest.mark.asyncio @@ -1538,7 +1558,7 @@ def test_parse_common_location_path(): assert expected == actual -def test_client_withDEFAULT_CLIENT_INFO(): +def test_client_with_default_client_info(): client_info = gapic_v1.client_info.ClientInfo() with mock.patch.object(