Copybara import of the project:

--
e167a6f by Yu-Han Liu <[email protected]>:

feat: regenerate with gapic-generator-python 1.4.4
COPYBARA_INTEGRATE_REVIEW=#1840 from googleapis:regenerate-1.20.0-1 f6fdd20
PiperOrigin-RevId: 494168144

google/cloud/aiplatform_v1/__init__.py

@@ -72,6 +72,7 @@
 from .types.dataset import ImportDataConfig
 from .types.dataset_service import CreateDatasetOperationMetadata
 from .types.dataset_service import CreateDatasetRequest
+from .types.dataset_service import DataItemView
 from .types.dataset_service import DeleteDatasetRequest
 from .types.dataset_service import ExportDataOperationMetadata
 from .types.dataset_service import ExportDataRequest
@@ -89,6 +90,8 @@
 from .types.dataset_service import ListDatasetsResponse
 from .types.dataset_service import ListSavedQueriesRequest
 from .types.dataset_service import ListSavedQueriesResponse
+from .types.dataset_service import SearchDataItemsRequest
+from .types.dataset_service import SearchDataItemsResponse
 from .types.dataset_service import UpdateDatasetRequest
 from .types.deployed_index_ref import DeployedIndexRef
 from .types.deployed_model_ref import DeployedModelRef
@@ -622,6 +625,7 @@
     "CustomJob",
     "CustomJobSpec",
     "DataItem",
+    "DataItemView",
     "DataLabelingJob",
     "Dataset",
     "DatasetServiceClient",
@@ -917,6 +921,8 @@
     "SavedQuery",
     "Scalar",
     "Scheduling",
+    "SearchDataItemsRequest",
+    "SearchDataItemsResponse",
     "SearchFeaturesRequest",
     "SearchFeaturesResponse",
     "SearchMigratableResourcesRequest",

google/cloud/aiplatform_v1/gapic_metadata.json

@@ -60,6 +60,11 @@
                 "list_saved_queries"
               ]
             },
+            "SearchDataItems": {
+              "methods": [
+                "search_data_items"
+              ]
+            },
             "UpdateDataset": {
               "methods": [
                 "update_dataset"
@@ -120,6 +125,11 @@
                 "list_saved_queries"
               ]
             },
+            "SearchDataItems": {
+              "methods": [
+                "search_data_items"
+              ]
+            },
             "UpdateDataset": {
               "methods": [
                 "update_dataset"

google/cloud/aiplatform_v1/services/dataset_service/async_client.py

@@ -1213,6 +1213,100 @@ async def sample_list_data_items():
         # Done; return the response.
         return response
 
+    async def search_data_items(
+        self,
+        request: Union[dataset_service.SearchDataItemsRequest, dict] = None,
+        *,
+        retry: OptionalRetry = gapic_v1.method.DEFAULT,
+        timeout: float = None,
+        metadata: Sequence[Tuple[str, str]] = (),
+    ) -> pagers.SearchDataItemsAsyncPager:
+        r"""Searches DataItems in a Dataset.
+
+        .. code-block:: python
+
+            # This snippet has been automatically generated and should be regarded as a
+            # code template only.
+            # It will require modifications to work:
+            # - It may require correct/in-range values for request initialization.
+            # - It may require specifying regional endpoints when creating the service
+            #   client as shown in:
+            #   https://googleapis.dev/python/google-api-core/latest/client_options.html
+            from google.cloud import aiplatform_v1
+
+            async def sample_search_data_items():
+                # Create a client
+                client = aiplatform_v1.DatasetServiceAsyncClient()
+
+                # Initialize request argument(s)
+                request = aiplatform_v1.SearchDataItemsRequest(
+                    order_by_data_item="order_by_data_item_value",
+                    dataset="dataset_value",
+                )
+
+                # Make the request
+                page_result = client.search_data_items(request=request)
+
+                # Handle the response
+                async for response in page_result:
+                    print(response)
+
+        Args:
+            request (Union[google.cloud.aiplatform_v1.types.SearchDataItemsRequest, dict]):
+                The request object. Request message for
+                [DatasetService.SearchDataItems][google.cloud.aiplatform.v1.DatasetService.SearchDataItems].
+            retry (google.api_core.retry.Retry): Designation of what errors, if any,
+                should be retried.
+            timeout (float): The timeout for this request.
+            metadata (Sequence[Tuple[str, str]]): Strings which should be
+                sent along with the request as metadata.
+
+        Returns:
+            google.cloud.aiplatform_v1.services.dataset_service.pagers.SearchDataItemsAsyncPager:
+                Response message for
+                [DatasetService.SearchDataItems][google.cloud.aiplatform.v1.DatasetService.SearchDataItems].
+
+                Iterating over this object will yield results and
+                resolve additional pages automatically.
+
+        """
+        # Create or coerce a protobuf request object.
+        request = dataset_service.SearchDataItemsRequest(request)
+
+        # Wrap the RPC method; this adds retry and timeout information,
+        # and friendly error handling.
+        rpc = gapic_v1.method_async.wrap_method(
+            self._client._transport.search_data_items,
+            default_timeout=None,
+            client_info=DEFAULT_CLIENT_INFO,
+        )
+
+        # Certain fields should be provided within the metadata header;
+        # add these here.
+        metadata = tuple(metadata) + (
+            gapic_v1.routing_header.to_grpc_metadata((("dataset", request.dataset),)),
+        )
+
+        # Send the request.
+        response = await rpc(
+            request,
+            retry=retry,
+            timeout=timeout,
+            metadata=metadata,
+        )
+
+        # This method is paged; wrap the response in a pager, which provides
+        # an `__aiter__` convenience method.
+        response = pagers.SearchDataItemsAsyncPager(
+            method=rpc,
+            request=request,
+            response=response,
+            metadata=metadata,
+        )
+
+        # Done; return the response.
+        return response
+
     async def list_saved_queries(
         self,
         request: Union[dataset_service.ListSavedQueriesRequest, dict] = None,

google/cloud/aiplatform_v1/services/dataset_service/client.py

@@ -1526,6 +1526,101 @@ def sample_list_data_items():
         # Done; return the response.
         return response
 
+    def search_data_items(
+        self,
+        request: Union[dataset_service.SearchDataItemsRequest, dict] = None,
+        *,
+        retry: OptionalRetry = gapic_v1.method.DEFAULT,
+        timeout: float = None,
+        metadata: Sequence[Tuple[str, str]] = (),
+    ) -> pagers.SearchDataItemsPager:
+        r"""Searches DataItems in a Dataset.
+
+        .. code-block:: python
+
+            # This snippet has been automatically generated and should be regarded as a
+            # code template only.
+            # It will require modifications to work:
+            # - It may require correct/in-range values for request initialization.
+            # - It may require specifying regional endpoints when creating the service
+            #   client as shown in:
+            #   https://googleapis.dev/python/google-api-core/latest/client_options.html
+            from google.cloud import aiplatform_v1
+
+            def sample_search_data_items():
+                # Create a client
+                client = aiplatform_v1.DatasetServiceClient()
+
+                # Initialize request argument(s)
+                request = aiplatform_v1.SearchDataItemsRequest(
+                    order_by_data_item="order_by_data_item_value",
+                    dataset="dataset_value",
+                )
+
+                # Make the request
+                page_result = client.search_data_items(request=request)
+
+                # Handle the response
+                for response in page_result:
+                    print(response)
+
+        Args:
+            request (Union[google.cloud.aiplatform_v1.types.SearchDataItemsRequest, dict]):
+                The request object. Request message for
+                [DatasetService.SearchDataItems][google.cloud.aiplatform.v1.DatasetService.SearchDataItems].
+            retry (google.api_core.retry.Retry): Designation of what errors, if any,
+                should be retried.
+            timeout (float): The timeout for this request.
+            metadata (Sequence[Tuple[str, str]]): Strings which should be
+                sent along with the request as metadata.
+
+        Returns:
+            google.cloud.aiplatform_v1.services.dataset_service.pagers.SearchDataItemsPager:
+                Response message for
+                [DatasetService.SearchDataItems][google.cloud.aiplatform.v1.DatasetService.SearchDataItems].
+
+                Iterating over this object will yield results and
+                resolve additional pages automatically.
+
+        """
+        # Create or coerce a protobuf request object.
+        # Minor optimization to avoid making a copy if the user passes
+        # in a dataset_service.SearchDataItemsRequest.
+        # There's no risk of modifying the input as we've already verified
+        # there are no flattened fields.
+        if not isinstance(request, dataset_service.SearchDataItemsRequest):
+            request = dataset_service.SearchDataItemsRequest(request)
+
+        # Wrap the RPC method; this adds retry and timeout information,
+        # and friendly error handling.
+        rpc = self._transport._wrapped_methods[self._transport.search_data_items]
+
+        # Certain fields should be provided within the metadata header;
+        # add these here.
+        metadata = tuple(metadata) + (
+            gapic_v1.routing_header.to_grpc_metadata((("dataset", request.dataset),)),
+        )
+
+        # Send the request.
+        response = rpc(
+            request,
+            retry=retry,
+            timeout=timeout,
+            metadata=metadata,
+        )
+
+        # This method is paged; wrap the response in a pager, which provides
+        # an `__iter__` convenience method.
+        response = pagers.SearchDataItemsPager(
+            method=rpc,
+            request=request,
+            response=response,
+            metadata=metadata,
+        )
+
+        # Done; return the response.
+        return response
+
     def list_saved_queries(
         self,
         request: Union[dataset_service.ListSavedQueriesRequest, dict] = None,

google/cloud/aiplatform_v1/services/dataset_service/pagers.py

@@ -287,6 +287,134 @@ def __repr__(self) -> str:
         return "{0}<{1!r}>".format(self.__class__.__name__, self._response)
 
 
+class SearchDataItemsPager:
+    """A pager for iterating through ``search_data_items`` requests.
+
+    This class thinly wraps an initial
+    :class:`google.cloud.aiplatform_v1.types.SearchDataItemsResponse` object, and
+    provides an ``__iter__`` method to iterate through its
+    ``data_item_views`` field.
+
+    If there are more pages, the ``__iter__`` method will make additional
+    ``SearchDataItems`` requests and continue to iterate
+    through the ``data_item_views`` field on the
+    corresponding responses.
+
+    All the usual :class:`google.cloud.aiplatform_v1.types.SearchDataItemsResponse`
+    attributes are available on the pager. If multiple requests are made, only
+    the most recent response is retained, and thus used for attribute lookup.
+    """
+
+    def __init__(
+        self,
+        method: Callable[..., dataset_service.SearchDataItemsResponse],
+        request: dataset_service.SearchDataItemsRequest,
+        response: dataset_service.SearchDataItemsResponse,
+        *,
+        metadata: Sequence[Tuple[str, str]] = ()
+    ):
+        """Instantiate the pager.
+
+        Args:
+            method (Callable): The method that was originally called, and
+                which instantiated this pager.
+            request (google.cloud.aiplatform_v1.types.SearchDataItemsRequest):
+                The initial request object.
+            response (google.cloud.aiplatform_v1.types.SearchDataItemsResponse):
+                The initial response object.
+            metadata (Sequence[Tuple[str, str]]): Strings which should be
+                sent along with the request as metadata.
+        """
+        self._method = method
+        self._request = dataset_service.SearchDataItemsRequest(request)
+        self._response = response
+        self._metadata = metadata
+
+    def __getattr__(self, name: str) -> Any:
+        return getattr(self._response, name)
+
+    @property
+    def pages(self) -> Iterator[dataset_service.SearchDataItemsResponse]:
+        yield self._response
+        while self._response.next_page_token:
+            self._request.page_token = self._response.next_page_token
+            self._response = self._method(self._request, metadata=self._metadata)
+            yield self._response
+
+    def __iter__(self) -> Iterator[dataset_service.DataItemView]:
+        for page in self.pages:
+            yield from page.data_item_views
+
+    def __repr__(self) -> str:
+        return "{0}<{1!r}>".format(self.__class__.__name__, self._response)
+
+
+class SearchDataItemsAsyncPager:
+    """A pager for iterating through ``search_data_items`` requests.
+
+    This class thinly wraps an initial
+    :class:`google.cloud.aiplatform_v1.types.SearchDataItemsResponse` object, and
+    provides an ``__aiter__`` method to iterate through its
+    ``data_item_views`` field.
+
+    If there are more pages, the ``__aiter__`` method will make additional
+    ``SearchDataItems`` requests and continue to iterate
+    through the ``data_item_views`` field on the
+    corresponding responses.
+
+    All the usual :class:`google.cloud.aiplatform_v1.types.SearchDataItemsResponse`
+    attributes are available on the pager. If multiple requests are made, only
+    the most recent response is retained, and thus used for attribute lookup.
+    """
+
+    def __init__(
+        self,
+        method: Callable[..., Awaitable[dataset_service.SearchDataItemsResponse]],
+        request: dataset_service.SearchDataItemsRequest,
+        response: dataset_service.SearchDataItemsResponse,
+        *,
+        metadata: Sequence[Tuple[str, str]] = ()
+    ):
+        """Instantiates the pager.
+
+        Args:
+            method (Callable): The method that was originally called, and
+                which instantiated this pager.
+            request (google.cloud.aiplatform_v1.types.SearchDataItemsRequest):
+                The initial request object.
+            response (google.cloud.aiplatform_v1.types.SearchDataItemsResponse):
+                The initial response object.
+            metadata (Sequence[Tuple[str, str]]): Strings which should be
+                sent along with the request as metadata.
+        """
+        self._method = method
+        self._request = dataset_service.SearchDataItemsRequest(request)
+        self._response = response
+        self._metadata = metadata
+
+    def __getattr__(self, name: str) -> Any:
+        return getattr(self._response, name)
+
+    @property
+    async def pages(self) -> AsyncIterator[dataset_service.SearchDataItemsResponse]:
+        yield self._response
+        while self._response.next_page_token:
+            self._request.page_token = self._response.next_page_token
+            self._response = await self._method(self._request, metadata=self._metadata)
+            yield self._response
+
+    def __aiter__(self) -> AsyncIterator[dataset_service.DataItemView]:
+        async def async_generator():
+            async for page in self.pages:
+                for response in page.data_item_views:
+                    yield response
+
+        return async_generator()
+
+    def __repr__(self) -> str:
+        return "{0}<{1!r}>".format(self.__class__.__name__, self._response)
+
+
 class ListSavedQueriesPager:
     """A pager for iterating through ``list_saved_queries`` requests.