创建和管理数据集

本页介绍了如何创建、修改、查看、列出和删除数据集。创建数据集后，您可以创建用于存储电子健康记录和医学影像数据的数据存储区，对数据集进行去标识化等。

准备工作

请参阅 Cloud Healthcare API 数据模型。

创建数据集

以下示例展示了如何创建数据集。

注意 ：如果您对保护数据的密钥有特定的合规性或监管要求，请按照为 Cloud Healthcare API 数据集启用客户管理的加密密钥 (CMEK)中的说明创建数据集。

执行此任务所需的权限

如需执行此任务，您必须已获得以下权限或以下 Identity and Access Management (IAM) 角色：

权限

• healthcare.datasets.create

角色

• Healthcare Dataset Administrator (roles/healthcare.datasetAdmin)

您可以要求管理员为您授予这些 Identity and Access Management 角色。如需了解如何授予角色，请参阅管理访问权限或控制对 Cloud Healthcare API 资源的访问。您也可以通过自定义角色或其他预定义角色来获取所需的权限。

注意：如果您为本指南创建了 Google Cloud 项目，那么作为项目创建者，您会自动获得具有相应权限的 Owner (roles/owner) IAM 角色。您无需获得任何其他 IAM 角色。

控制台gcloudRESTGoJavaNode.jsPython

1. 在 Google Cloud 控制台中，前往浏览器页面。

   转到浏览器

2. 点击 创建数据集。系统随即会显示数据集属性页面。

3. 在名称字段中，输入数据集的标识符，该标识符应符合数据集允许的字符和大小要求。

4. 选择以下某一类型的位置：

   • Region 绑定将多选选项设置为所有记录中 Region 的所有值。数据集永久驻留在一个 Google Cloud 区域中。选择此选项后，在区域字段中输入或选择位置。

   • 多区域。数据集永久驻留在跨多个 Google Cloud 区域的位置中。选择此选项后，在多区域字段中输入或选择多区域位置。

5. 点击创建。系统会显示浏览器页面。新数据集将显示在数据集列表中。

运行 gcloud healthcare datasets create 命令。

在使用下面的命令数据之前，请先进行以下替换：

• LOCATION：数据集的受支持的位置
• DATASET_ID：一个标识符，须遵循数据集允许的字符和大小要求

执行以下命令：

Linux、macOS 或 Cloud Shell

注意：通过运行 gcloud init 或 gcloud auth login 和 gcloud config set project，确保您已使用身份验证和项目初始化了 Google Cloud CLI。

gcloud healthcare datasets create DATASET_ID \
  --location=LOCATION

Windows (PowerShell)

注意：通过运行 gcloud init 或 gcloud auth login 和 gcloud config set project，确保您已使用身份验证和项目初始化了 Google Cloud CLI。

gcloud healthcare datasets create DATASET_ID `
  --location=LOCATION

Windows (cmd.exe)

注意：通过运行 gcloud init 或 gcloud auth login 和 gcloud config set project，确保您已使用身份验证和项目初始化了 Google Cloud CLI。

gcloud healthcare datasets create DATASET_ID ^
  --location=LOCATION

您应该会收到类似如下所示的响应：

Create request issued for: [DATASET_ID]
Created dataset [DATASET_ID].

1. 使用 projects.locations.datasets.create 方法创建数据集。

   在使用任何请求数据之前，请先进行以下替换：

   • PROJECT_ID：您的 Google Cloud 项目的 ID
   • LOCATION：数据集的受支持的位置
   • DATASET_ID：一个标识符，须遵循数据集允许的字符和大小要求

   如需发送请求，请选择以下方式之一：

   curlPowerShellAPI Explorer
   注意：以下命令假定您已使用您的用户账号通过运行 gcloud init 或 gcloud auth login 登录 gcloud CLI，或者使用了 Cloud Shell，这会使您自动登录 gcloud CLI。您可以运行 gcloud auth list 来检查当前活跃的账号。

   执行以下命令：

   curl -X POST \
        -H "Authorization: Bearer $(gcloud auth print-access-token)" \
        -H "Content-Type: application/json; charset=utf-8" \
        -d "" \
        "https://healthcare.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/datasets?datasetId=DATASET_ID"

   注意：以下命令假定您已使用您的用户账号通过运行 gcloud init 或 gcloud auth login 登录 gcloud CLI。您可以运行 gcloud auth list 来检查当前活跃的账号。

   执行以下命令：

   $cred = gcloud auth print-access-token
   $headers = @{ "Authorization" = "Bearer $cred" }
   
   Invoke-WebRequest `
       -Method POST `
       -Headers $headers `
       -Uri "https://healthcare.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/datasets?datasetId=DATASET_ID" | Select-Object -Expand Content

   打开方法参考页面。APIs Explorer 面板会在页面右侧打开。您可以与此工具进行交互以发送请求。 填写所有必填字段，然后点击执行。

   输出如下所示。响应包含长时间运行的操作 (LRO) 的标识符。当方法调用可能需要额外时间才能完成时，会返回长时间运行的操作。记下 OPERATION_ID 的值。下一步中您需要用到该值。

   响应

   {
     "name": "projects/PROJECT_ID/locations/LOCATION/datasets/DATASET_ID/operations/OPERATION_ID"
   }
   
   

2. 使用 projects.locations.datasets.operations.get 方法获取长时间运行的操作的状态。

   在使用任何请求数据之前，请先进行以下替换：

   • PROJECT_ID：您的 Google Cloud 项目的 ID
   • LOCATION：数据集位置
   • DATASET_ID：数据集 ID
   • OPERATION_ID：从长时间运行的操作返回的 ID

   如需发送请求，请选择以下方式之一：

   curlPowerShellAPI Explorer
   注意：以下命令假定您已使用您的用户账号通过运行 gcloud init 或 gcloud auth login 登录 gcloud CLI，或者使用了 Cloud Shell，这会使您自动登录 gcloud CLI。您可以运行 gcloud auth list 来检查当前活跃的账号。

   执行以下命令：

   curl -X GET \
        -H "Authorization: Bearer $(gcloud auth print-access-token)" \
        "https://healthcare.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/datasets/DATASET_ID/operations/OPERATION_ID"

   注意：以下命令假定您已使用您的用户账号通过运行 gcloud init 或 gcloud auth login 登录 gcloud CLI。您可以运行 gcloud auth list 来检查当前活跃的账号。

   执行以下命令：

   $cred = gcloud auth print-access-token
   $headers = @{ "Authorization" = "Bearer $cred" }
   
   Invoke-WebRequest `
       -Method GET `
       -Headers $headers `
       -Uri "https://healthcare.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/datasets/DATASET_ID/operations/OPERATION_ID" | Select-Object -Expand Content

   打开方法参考页面。APIs Explorer 面板会在页面右侧打开。您可以与此工具进行交互以发送请求。 填写所有必填字段，然后点击执行。

   输出如下所示。如果响应包含 "done": true，则表示长时间运行的操作已完成。

   响应

   {
     "name": "projects/PROJECT_ID/locations/LOCATION/datasets/DATASET_ID/operations/OPERATION_ID",
     "metadata": {
       "@type": "type.googleapis.com/google.cloud.healthcare.v1.OperationMetadata",
       "apiMethodName": "google.cloud.healthcare.v1.dataset.DatasetService.CreateDataset",
       "createTime": "YYYY-MM-DDTHH:MM:SS+ZZ:ZZ",
       "endTime": "YYYY-MM-DDTHH:MM:SS+ZZ:ZZ",
       "logsUrl": "https://console.cloud.google.com/CLOUD_LOGGING_URL"
       "counter": {
         "success": "SUCCESS_COUNT",
         // If there were any failures, they display in the `failure` field.
         "failure": "FAILURE_COUNT"
       }
     },
     "done": true,
     // The `response` field only displays if there were no errors.
     "response": {
       "@type": "type.googleapis.com/google.cloud.healthcare.v1.dataset.Dataset",
       "name": "PROJECT_ID/locations/LOCATION/datasets/DATASET_ID",
     },
     // If there were any errors, an `error` field displays instead of a `response` field.
     // See Troubleshooting long-running operations for a list of response codes.
     "error": {
       "code": ERROR_CODE,
       "message": "DESCRIPTION",
       "details": [
         {
           "@type": "...",
           FIELD1: ...,
           ...
         }
       ]
     }
   }
   

import (
	"context"
	"fmt"
	"io"
	"time"

	healthcare "google.golang.org/api/healthcare/v1"
)

// createDataset creates a dataset.
func createDataset(w io.Writer, projectID, location, datasetID string) error {
	// Set a deadline for the dataset to become initialized.
	ctx, cancel := context.WithTimeout(context.Background(), 2*time.Minute)
	defer cancel()

	healthcareService, err := healthcare.NewService(ctx)
	if err != nil {
		return fmt.Errorf("healthcare.NewService: %w", err)
	}

	datasetsService := healthcareService.Projects.Locations.Datasets

	parent := fmt.Sprintf("projects/%s/locations/%s", projectID, location)

	resp, err := datasetsService.Create(parent, &healthcare.Dataset{}).DatasetId(datasetID).Context(ctx).Do()
	if err != nil {
		return fmt.Errorf("Create: %w", err)
	}

	// The dataset is not always ready to use immediately, instead a long-running operation is returned.
	// This is how you might poll the operation to ensure the dataset is fully initialized before proceeding.
	// Initialization usually takes less than a minute.
	for !resp.Done {
		time.Sleep(15 * time.Second)
		resp, err = datasetsService.Operations.Get(resp.Name).Context(ctx).Do()
		if err != nil {
			return fmt.Errorf("Operations.Get(%s): %w", resp.Name, err)
		}
	}

	fmt.Fprintf(w, "Created dataset: %q\n", resp.Name)
	return nil
}

import com.google.api.client.http.HttpRequestInitializer;
import com.google.api.client.http.javanet.NetHttpTransport;
import com.google.api.client.json.JsonFactory;
import com.google.api.client.json.gson.GsonFactory;
import com.google.api.services.healthcare.v1.CloudHealthcare;
import com.google.api.services.healthcare.v1.CloudHealthcare.Projects.Locations.Datasets;
import com.google.api.services.healthcare.v1.CloudHealthcareScopes;
import com.google.api.services.healthcare.v1.model.Dataset;
import com.google.api.services.healthcare.v1.model.Operation;
import com.google.auth.http.HttpCredentialsAdapter;
import com.google.auth.oauth2.GoogleCredentials;
import java.io.IOException;
import java.util.Collections;

public class DatasetCreate {
  private static final String DATASET_NAME = "projects/%s/locations/%s/datasets/%s";
  private static final JsonFactory JSON_FACTORY = new GsonFactory();
  private static final NetHttpTransport HTTP_TRANSPORT = new NetHttpTransport();

  public static void datasetCreate(String projectId, String regionId, String datasetId)
      throws IOException {
    // String projectId = "your-project-id";
    // String regionId = "us-central1";
    // String datasetId = "your-dataset-id";

    // Initialize the client, which will be used to interact with the service.
    CloudHealthcare client = createClient();

    // Configure the dataset to be created.
    Dataset dataset = new Dataset();
    dataset.setTimeZone("America/Chicago");

    // Create request and configure any parameters.
    String parentName = String.format("projects/%s/locations/%s", projectId, regionId);
    Datasets.Create request = client.projects().locations().datasets().create(parentName, dataset);
    request.setDatasetId(datasetId);

    // Execute the request, wait for the operation to complete, and process the results.
    try {
      Operation operation = request.execute();
      System.out.println(operation.toPrettyString());
      while (operation.getDone() == null || !operation.getDone()) {
        // Update the status of the operation with another request.
        Thread.sleep(500); // Pause for 500ms between requests.
        operation =
            client
                .projects()
                .locations()
                .datasets()
                .operations()
                .get(operation.getName())
                .execute();
      }
      System.out.println("Dataset created. Response content: " + operation.getResponse());
    } catch (Exception ex) {
      System.out.printf("Error during request execution: %s\n", ex.toString());
      ex.printStackTrace(System.out);
    }
  }

  private static CloudHealthcare createClient() throws IOException {
    // Use Application Default Credentials (ADC) to authenticate the requests
    // For more information see https://cloud.google.com/docs/authentication/production
    GoogleCredentials credential =
        GoogleCredentials.getApplicationDefault()
            .createScoped(Collections.singleton(CloudHealthcareScopes.CLOUD_PLATFORM));

    // Create a HttpRequestInitializer, which will provide a baseline configuration to all requests.
    HttpRequestInitializer requestInitializer =
        request -> {
          new HttpCredentialsAdapter(credential).initialize(request);
          request.setConnectTimeout(60000); // 1 minute connect timeout
          request.setReadTimeout(60000); // 1 minute read timeout
        };

    // Build the client for interacting with the service.
    return new CloudHealthcare.Builder(HTTP_TRANSPORT, JSON_FACTORY, requestInitializer)
        .setApplicationName("your-application-name")
        .build();
  }
}

const google = require('@googleapis/healthcare');
const healthcare = google.healthcare({
  version: 'v1',
  auth: new google.auth.GoogleAuth({
    scopes: ['https://www.googleapis.com/auth/cloud-platform'],
  }),
});

const createDataset = async () => {
  // TODO(developer): uncomment these lines before running the sample
  // const cloudRegion = 'us-central1';
  // const projectId = 'adjective-noun-123';
  // const datasetId = 'my-dataset';
  const parent = `projects/${projectId}/locations/${cloudRegion}`;
  const request = {parent, datasetId};

  await healthcare.projects.locations.datasets.create(request);
  console.log(`Created dataset: ${datasetId}`);
};

createDataset();

# Imports the Dict type for runtime type hints.
from typing import Dict


def create_dataset(project_id: str, location: str, dataset_id: str) -> Dict[str, str]:
    """Creates a Cloud Healthcare API dataset.

    See
    https://github.com/GoogleCloudPlatform/python-docs-samples/tree/main/healthcare/api-client/v1/datasets
    before running the sample.
    See
    https://googleapis.github.io/google-api-python-client/docs/dyn/healthcare_v1.projects.locations.datasets.html#create
    for the Python API reference.

    Args:
      project_id: The project ID or project number of the Google Cloud project you want
          to use.
      location: The name of the dataset's location.
      dataset_id: The ID of the dataset to create.

    Returns:
      A dictionary representing a long-running operation that results from
      calling the 'CreateDataset' method. Dataset creation is typically fast.
    """
    # Imports the Python built-in time module.
    import time

    # Imports the Google API Discovery Service.
    from googleapiclient import discovery

    # Imports HttpError from the Google Python API client errors module.
    from googleapiclient.errors import HttpError

    api_version = "v1"
    service_name = "healthcare"
    # Returns an authorized API client by discovering the Healthcare API
    # and using GOOGLE_APPLICATION_CREDENTIALS environment variable.
    client = discovery.build(service_name, api_version)

    # TODO(developer): Uncomment these lines and replace with your values.
    # project_id = 'my-project'
    # location = 'us-central1'
    # dataset_id = 'my-dataset'
    dataset_parent = f"projects/{project_id}/locations/{location}"

    request = (
        client.projects()
        .locations()
        .datasets()
        .create(parent=dataset_parent, body={}, datasetId=dataset_id)
    )

    # Wait for operation to complete.
    start_time = time.time()
    max_time = 600  # 10 minutes, but dataset creation is typically only a few seconds.

    try:
        operation = request.execute()
        while not operation.get("done", False):
            # Poll until the operation finishes.
            print("Waiting for operation to finish...")
            if time.time() - start_time > max_time:
                raise TimeoutError("Timed out waiting for operation to finish.")
            operation = (
                client.projects()
                .locations()
                .datasets()
                .operations()
                .get(name=operation["name"])
                .execute()
            )
            # Wait 5 seconds between each poll to the operation.
            time.sleep(5)

        if "error" in operation:
            raise RuntimeError(f"Create dataset operation failed: {operation['error']}")
        else:
            dataset_name = operation["response"]["name"]
            print(f"Created dataset: {dataset_name}")
            return operation

    except HttpError as err:
        # A common error is when the dataset already exists.
        if err.resp.status == 409:
            print(f"Dataset with ID {dataset_id} already exists.")
            return
        else:
            raise err

编辑数据集

以下示例展示了如何修改数据集。

执行此任务所需的权限

如需执行此任务，您必须已获得以下权限或以下 Identity and Access Management (IAM) 角色：

权限

• healthcare.datasets.update

角色

• Healthcare Dataset Administrator (roles/healthcare.datasetAdmin)

您可以要求管理员为您授予这些 Identity and Access Management 角色。如需了解如何授予角色，请参阅管理访问权限或控制对 Cloud Healthcare API 资源的访问。您也可以通过自定义角色或其他预定义角色来获取所需的权限。

注意：如果您为本指南创建了 Google Cloud 项目，那么作为项目创建者，您会自动获得具有相应权限的 Owner (roles/owner) IAM 角色。您无需获得任何其他 IAM 角色。

控制台gcloudRESTGoJavaNode.jsPython

Google Cloud 控制台不支持修改数据集。请改用 Google Cloud CLI 或 REST API。

运行 gcloud healthcare datasets update 命令。

在使用下面的命令数据之前，请先进行以下替换：

• LOCATION：数据集位置
• DATASET_ID：数据集 ID
• TIME_ZONE：支持的时区，例如 UTC

执行以下命令：

Linux、macOS 或 Cloud Shell

注意：通过运行 gcloud init 或 gcloud auth login 和 gcloud config set project，确保您已使用身份验证和项目初始化了 Google Cloud CLI。

gcloud healthcare datasets update DATASET_ID \
  --location=LOCATION \
  --time-zone=TIME_ZONE

Windows (PowerShell)

注意：通过运行 gcloud init 或 gcloud auth login 和 gcloud config set project，确保您已使用身份验证和项目初始化了 Google Cloud CLI。

gcloud healthcare datasets update DATASET_ID `
  --location=LOCATION `
  --time-zone=TIME_ZONE

Windows (cmd.exe)

注意：通过运行 gcloud init 或 gcloud auth login 和 gcloud config set project，确保您已使用身份验证和项目初始化了 Google Cloud CLI。

gcloud healthcare datasets update DATASET_ID ^
  --location=LOCATION ^
  --time-zone=TIME_ZONE

您应该会收到类似如下所示的响应：

Updated dataset [DATASET_ID].
name: projects/PROJECT_ID/locations/LOCATION/datasets/DATASET_ID
timeZone: TIME_ZONE

使用 projects.locations.datasets.patch 方法。

在使用任何请求数据之前，请先进行以下替换：

• PROJECT_ID：您的 Google Cloud 项目的 ID
• LOCATION：数据集位置
• DATASET_ID：数据集 ID
• TIME_ZONE：支持的时区，例如 UTC

请求 JSON 正文：

{
  "timeZone": "TIME_ZONE"
}

如需发送请求，请选择以下方式之一：

curlPowerShellAPI Explorer

注意：以下命令假定您已使用您的用户账号通过运行 gcloud init 或 gcloud auth login 登录 gcloud CLI，或者使用了 Cloud Shell，这会使您自动登录 gcloud CLI。您可以运行 gcloud auth list 来检查当前活跃的账号。

将请求正文保存在名为 request.json 的文件中，然后执行以下命令：

curl -X PATCH \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     -H "Content-Type: application/json; charset=utf-8" \
     -d @request.json \
     "https://healthcare.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/datasets/DATASET_ID?updateMask=timeZone"

注意：以下命令假定您已使用您的用户账号通过运行 gcloud init 或 gcloud auth login 登录 gcloud CLI。您可以运行 gcloud auth list 来检查当前活跃的账号。

将请求正文保存在名为 request.json 的文件中，然后执行以下命令：

$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

Invoke-WebRequest `
    -Method PATCH `
    -Headers $headers `
    -ContentType: "application/json; charset=utf-8" `
    -InFile request.json `
    -Uri "https://healthcare.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/datasets/DATASET_ID?updateMask=timeZone" | Select-Object -Expand Content

复制请求正文并打开方法参考页面。APIs Explorer 面板会在页面右侧打开。您可以与此工具进行交互以发送请求。 将请求正文粘贴到此工具中，填写任何其他必填字段，然后点击执行。

您应该收到类似以下内容的 JSON 响应：

响应

{
  "name": "projects/PROJECT_ID/locations/LOCATION/datasets/DATASET_ID"
  "timeZone": "TIME_ZONE"
}

import (
	"context"
	"fmt"
	"io"

	healthcare "google.golang.org/api/healthcare/v1"
)

// patchDataset updates (patches) a dataset by updating its timezone..
func patchDataset(w io.Writer, projectID, location, datasetID, newTimeZone string) error {
	ctx := context.Background()

	healthcareService, err := healthcare.NewService(ctx)
	if err != nil {
		return fmt.Errorf("healthcare.NewService: %w", err)
	}

	datasetsService := healthcareService.Projects.Locations.Datasets

	name := fmt.Sprintf("projects/%s/locations/%s/datasets/%s", projectID, location, datasetID)

	if _, err := datasetsService.Patch(name, &healthcare.Dataset{
		TimeZone: newTimeZone,
	}).UpdateMask("timeZone").Do(); err != nil {
		return fmt.Errorf("Patch: %w", err)
	}

	fmt.Fprintf(w, "Patched dataset %s with timeZone %s\n", datasetID, newTimeZone)

	return nil
}

import com.google.api.client.http.HttpRequestInitializer;
import com.google.api.client.http.javanet.NetHttpTransport;
import com.google.api.client.json.JsonFactory;
import com.google.api.client.json.gson.GsonFactory;
import com.google.api.services.healthcare.v1.CloudHealthcare;
import com.google.api.services.healthcare.v1.CloudHealthcare.Projects.Locations.Datasets;
import com.google.api.services.healthcare.v1.CloudHealthcareScopes;
import com.google.api.services.healthcare.v1.model.Dataset;
import com.google.auth.http.HttpCredentialsAdapter;
import com.google.auth.oauth2.GoogleCredentials;
import java.io.IOException;
import java.util.Collections;

public class DatasetPatch {
  private static final String DATASET_NAME = "projects/%s/locations/%s/datasets/%s";
  private static final JsonFactory JSON_FACTORY = new GsonFactory();
  private static final NetHttpTransport HTTP_TRANSPORT = new NetHttpTransport();

  public static void datasetPatch(String datasetName) throws IOException {
    // String datasetName =
    //     String.format(DATASET_NAME, "your-project-id", "your-region-id", "your-dataset-id");

    // Initialize the client, which will be used to interact with the service.
    CloudHealthcare client = createClient();

    // Fetch the initial state of the dataset.
    Datasets.Get getRequest = client.projects().locations().datasets().get(datasetName);
    Dataset dataset = getRequest.execute();

    // Update the Dataset fields as needed as needed. For a full list of dataset fields, see:
    // https://cloud.google.com/healthcare/docs/reference/rest/v1beta1/projects.locations.datasets#Dataset
    dataset.setTimeZone("America/New_York");

    // Create request and configure any parameters.
    Datasets.Patch request =
        client
            .projects()
            .locations()
            .datasets()
            .patch(datasetName, dataset)
            .setUpdateMask("timeZone");

    // Execute the request and process the results.
    dataset = request.execute();
    System.out.println("Dataset patched: \n" + dataset.toPrettyString());
  }

  private static CloudHealthcare createClient() throws IOException {
    // Use Application Default Credentials (ADC) to authenticate the requests
    // For more information see https://cloud.google.com/docs/authentication/production
    GoogleCredentials credential =
        GoogleCredentials.getApplicationDefault()
            .createScoped(Collections.singleton(CloudHealthcareScopes.CLOUD_PLATFORM));

    // Create a HttpRequestInitializer, which will provide a baseline configuration to all requests.
    HttpRequestInitializer requestInitializer =
        request -> {
          new HttpCredentialsAdapter(credential).initialize(request);
          request.setConnectTimeout(60000); // 1 minute connect timeout
          request.setReadTimeout(60000); // 1 minute read timeout
        };

    // Build the client for interacting with the service.
    return new CloudHealthcare.Builder(HTTP_TRANSPORT, JSON_FACTORY, requestInitializer)
        .setApplicationName("your-application-name")
        .build();
  }
}

const google = require('@googleapis/healthcare');
const healthcare = google.healthcare({
  version: 'v1',
  auth: new google.auth.GoogleAuth({
    scopes: ['https://www.googleapis.com/auth/cloud-platform'],
  }),
});

const patchDataset = async () => {
  // TODO(developer): uncomment these lines before running the sample
  // const cloudRegion = 'us-central1';
  // const projectId = 'adjective-noun-123';
  // const datasetId = 'my-dataset';
  // const timeZone = 'UTC';
  const name = `projects/${projectId}/locations/${cloudRegion}/datasets/${datasetId}`;
  const request = {
    name,
    updateMask: 'timeZone',
    resource: {timeZone: timeZone},
  };

  await healthcare.projects.locations.datasets.patch(request);
  console.log(`Dataset ${datasetId} patched with time zone ${timeZone}`);
};

patchDataset();

# Imports the Dict type for runtime type hints.
from typing import Dict

def patch_dataset(
    project_id: str, location: str, dataset_id: str, time_zone: str
) -> Dict[str, str]:
    """Updates dataset metadata.

    See
    https://github.com/GoogleCloudPlatform/python-docs-samples/tree/main/healthcare/api-client/v1/datasets
    before running the sample.
    See https://googleapis.github.io/google-api-python-client/docs/dyn/healthcare_v1.projects.locations.datasets.html#patch
    for the Python API reference.

    Args:
      project_id: The project ID or project number of the Google Cloud project you want
          to use.
      location: The name of the dataset's location.
      dataset_id: The ID of the dataset to patch.
      time_zone: The default timezone used by the dataset.

    Returns:
      A dictionary representing the patched Dataset resource.
    """
    # Imports the Google API Discovery Service.
    from googleapiclient import discovery

    # Imports HttpError from the Google Python API client errors module.
    from googleapiclient.errors import HttpError

    api_version = "v1"
    service_name = "healthcare"
    # Returns an authorized API client by discovering the Healthcare API
    # and using GOOGLE_APPLICATION_CREDENTIALS environment variable.
    client = discovery.build(service_name, api_version)

    # TODO(developer): Uncomment these lines and replace with your values.
    # project_id = 'my-project'
    # location = 'us-central1'
    # dataset_id = 'my-dataset'
    # time_zone = 'GMT'
    dataset_parent = f"projects/{project_id}/locations/{location}"
    dataset_name = f"{dataset_parent}/datasets/{dataset_id}"

    # Sets the time zone
    patch = {"timeZone": time_zone}

    request = (
        client.projects()
        .locations()
        .datasets()
        .patch(name=dataset_name, updateMask="timeZone", body=patch)
    )

    try:
        response = request.execute()
        print(f"Patched dataset {dataset_id} with time zone: {time_zone}")
        return response
    except HttpError as err:
        raise err

获取数据集详情

以下示例展示了如何获取有关数据集的详细信息。

执行此任务所需的权限

如需执行此任务，您必须已获得以下权限或以下 Identity and Access Management (IAM) 角色：

权限

• healthcare.datasets.get

角色

• Healthcare Dataset Viewer (roles/healthcare.datasetViewer)
• Healthcare Dataset Administrator (roles/healthcare.datasetAdmin)

您可以要求管理员为您授予这些 Identity and Access Management 角色。如需了解如何授予角色，请参阅管理访问权限或控制对 Cloud Healthcare API 资源的访问。您也可以通过自定义角色或其他预定义角色来获取所需的权限。

注意：如果您为本指南创建了 Google Cloud 项目，那么作为项目创建者，您会自动获得具有相应权限的 Owner (roles/owner) IAM 角色。您无需获得任何其他 IAM 角色。

控制台gcloudRESTGoJavaNode.jsPython

1. 在 Google Cloud 控制台中，前往浏览器页面。

   转到浏览器

2. 选择数据集。系统会显示数据集页面以及数据集中的数据存储区。

运行 gcloud healthcare datasets describe 命令。

在使用下面的命令数据之前，请先进行以下替换：

• LOCATION：数据集位置
• DATASET_ID：数据集 ID

执行以下命令：

Linux、macOS 或 Cloud Shell

注意：通过运行 gcloud init 或 gcloud auth login 和 gcloud config set project，确保您已使用身份验证和项目初始化了 Google Cloud CLI。

gcloud healthcare datasets describe DATASET_ID \
  --location=LOCATION

Windows (PowerShell)

注意：通过运行 gcloud init 或 gcloud auth login 和 gcloud config set project，确保您已使用身份验证和项目初始化了 Google Cloud CLI。

gcloud healthcare datasets describe DATASET_ID `
  --location=LOCATION

Windows (cmd.exe)

注意：通过运行 gcloud init 或 gcloud auth login 和 gcloud config set project，确保您已使用身份验证和项目初始化了 Google Cloud CLI。

gcloud healthcare datasets describe DATASET_ID ^
  --location=LOCATION

您应该会收到类似如下所示的响应：

name: projects/PROJECT_ID/locations/LOCATION/datasets/DATASET_ID
timeZone: TIME_ZONE

使用 projects.locations.datasets.get 方法。

在使用任何请求数据之前，请先进行以下替换：

• PROJECT_ID：您的 Google Cloud 项目的 ID
• LOCATION：数据集位置
• DATASET_ID：数据集 ID

如需发送请求，请选择以下方式之一：

curlPowerShellAPI Explorer

注意：以下命令假定您已使用您的用户账号通过运行 gcloud init 或 gcloud auth login 登录 gcloud CLI，或者使用了 Cloud Shell，这会使您自动登录 gcloud CLI。您可以运行 gcloud auth list 来检查当前活跃的账号。

执行以下命令：

curl -X GET \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     "https://healthcare.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/datasets/DATASET_ID"

注意：以下命令假定您已使用您的用户账号通过运行 gcloud init 或 gcloud auth login 登录 gcloud CLI。您可以运行 gcloud auth list 来检查当前活跃的账号。

执行以下命令：

$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

Invoke-WebRequest `
    -Method GET `
    -Headers $headers `
    -Uri "https://healthcare.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/datasets/DATASET_ID" | Select-Object -Expand Content

打开方法参考页面。APIs Explorer 面板会在页面右侧打开。您可以与此工具进行交互以发送请求。 填写所有必填字段，然后点击执行。

您应该收到类似以下内容的 JSON 响应：

响应

{
  "name": "projects/PROJECT_ID/locations/LOCATION/datasets/DATASET_ID"
  "timeZone": "TIME_ZONE"
}

import (
	"context"
	"fmt"
	"io"

	healthcare "google.golang.org/api/healthcare/v1"
)

// getDataset gets a dataset.
func getDataset(w io.Writer, projectID, location, datasetID string) error {
	ctx := context.Background()

	healthcareService, err := healthcare.NewService(ctx)
	if err != nil {
		return fmt.Errorf("healthcare.NewService: %w", err)
	}

	datasetsService := healthcareService.Projects.Locations.Datasets

	name := fmt.Sprintf("projects/%s/locations/%s/datasets/%s", projectID, location, datasetID)

	resp, err := datasetsService.Get(name).Do()
	if err != nil {
		return fmt.Errorf("Get: %w", err)
	}

	fmt.Fprintf(w, "Name: %s\n", resp.Name)
	fmt.Fprintf(w, "Time zone: %s\n", resp.TimeZone)

	return nil
}

import com.google.api.client.http.HttpRequestInitializer;
import com.google.api.client.http.javanet.NetHttpTransport;
import com.google.api.client.json.JsonFactory;
import com.google.api.client.json.gson.GsonFactory;
import com.google.api.services.healthcare.v1.CloudHealthcare;
import com.google.api.services.healthcare.v1.CloudHealthcare.Projects.Locations.Datasets;
import com.google.api.services.healthcare.v1.CloudHealthcareScopes;
import com.google.api.services.healthcare.v1.model.Dataset;
import com.google.auth.http.HttpCredentialsAdapter;
import com.google.auth.oauth2.GoogleCredentials;
import java.io.IOException;
import java.util.Collections;

public class DatasetGet {
  private static final String DATASET_NAME = "projects/%s/locations/%s/datasets/%s";
  private static final JsonFactory JSON_FACTORY = new GsonFactory();
  private static final NetHttpTransport HTTP_TRANSPORT = new NetHttpTransport();

  public static void datasetGet(String datasetName) throws IOException {
    // String datasetName =
    //     String.format(DATASET_NAME, "your-project-id", "your-region-id", "your-dataset-id");

    // Initialize the client, which will be used to interact with the service.
    CloudHealthcare client = createClient();

    // Create request and configure any parameters.
    Datasets.Get request = client.projects().locations().datasets().get(datasetName);

    // Execute the request and process the results.
    Dataset dataset = request.execute();
    System.out.println("Dataset retrieved: \n" + dataset.toPrettyString());
  }

  private static CloudHealthcare createClient() throws IOException {
    // Use Application Default Credentials (ADC) to authenticate the requests
    // For more information see https://cloud.google.com/docs/authentication/production
    GoogleCredentials credential =
        GoogleCredentials.getApplicationDefault()
            .createScoped(Collections.singleton(CloudHealthcareScopes.CLOUD_PLATFORM));

    // Create a HttpRequestInitializer, which will provide a baseline configuration to all requests.
    HttpRequestInitializer requestInitializer =
        request -> {
          new HttpCredentialsAdapter(credential).initialize(request);
          request.setConnectTimeout(60000); // 1 minute connect timeout
          request.setReadTimeout(60000); // 1 minute read timeout
        };

    // Build the client for interacting with the service.
    return new CloudHealthcare.Builder(HTTP_TRANSPORT, JSON_FACTORY, requestInitializer)
        .setApplicationName("your-application-name")
        .build();
  }
}

const google = require('@googleapis/healthcare');
const healthcare = google.healthcare({
  version: 'v1',
  auth: new google.auth.GoogleAuth({
    scopes: ['https://www.googleapis.com/auth/cloud-platform'],
  }),
});

const getDataset = async () => {
  // TODO(developer): uncomment these lines before running the sample
  // const cloudRegion = 'us-central1';
  // const projectId = 'adjective-noun-123';
  // const datasetId = 'my-dataset';
  const parent = `projects/${projectId}/locations/${cloudRegion}/datasets/${datasetId}`;
  const request = {name: parent};

  const dataset = await healthcare.projects.locations.datasets.get(request);
  console.log(dataset.data);
};

getDataset();

# Imports the Dict type for runtime type hints.
from typing import Dict


def get_dataset(project_id: str, location: str, dataset_id: str) -> Dict[str, str]:
    """Gets any metadata associated with a dataset.

    See
    https://github.com/GoogleCloudPlatform/python-docs-samples/tree/main/healthcare/api-client/v1/datasets
    before running the sample.
    See https://googleapis.github.io/google-api-python-client/docs/dyn/healthcare_v1.projects.locations.datasets.html#get
    for the Python API reference.

    Args:
      project_id: The project ID or project number of the Google Cloud project you want
          to use.
      location: The name of the dataset's location.
      dataset_id: The name of the dataset to get.

    Returns:
      A dictionary representing a Dataset resource.
    """
    # Imports HttpError from the Google Python API client errors module.
    # Imports the Google API Discovery Service.
    from googleapiclient import discovery
    from googleapiclient.errors import HttpError

    api_version = "v1"
    service_name = "healthcare"
    # Returns an authorized API client by discovering the Healthcare API
    # and using GOOGLE_APPLICATION_CREDENTIALS environment variable.
    client = discovery.build(service_name, api_version)

    # TODO(developer): Uncomment these lines and replace with your values.
    # project_id = 'my-project'
    # location = 'us-central1'
    # dataset_id = 'my-dataset'
    dataset_name = f"projects/{project_id}/locations/{location}/datasets/{dataset_id}"

    request = client.projects().locations().datasets()

    try:
        dataset = request.get(name=dataset_name).execute()
        print(f"Name: {dataset.get('name')}")
        return dataset
    except HttpError as err:
        raise err

列出数据集

以下示例展示了如何列出项目中的数据集。

执行此任务所需的权限

如需执行此任务，您必须已获得以下权限或以下 Identity and Access Management (IAM) 角色：

权限

• healthcare.datasets.list

角色

• Healthcare Dataset Viewer (roles/healthcare.datasetViewer)
• Healthcare Dataset Administrator (roles/healthcare.datasetAdmin)

您可以要求管理员为您授予这些 Identity and Access Management 角色。如需了解如何授予角色，请参阅管理访问权限或控制对 Cloud Healthcare API 资源的访问。您也可以通过自定义角色或其他预定义角色来获取所需的权限。

注意：如果您为本指南创建了 Google Cloud 项目，那么作为项目创建者，您会自动获得具有相应权限的 Owner (roles/owner) IAM 角色。您无需获得任何其他 IAM 角色。

控制台gcloudRESTGoJavaNode.jsPython

在 Google Cloud 控制台中，前往浏览器页面。

转到浏览器

运行 gcloud healthcare datasets list 命令。

在使用下面的命令数据之前，请先进行以下替换：

• LOCATION：数据集位置

执行以下命令：

Linux、macOS 或 Cloud Shell

注意：通过运行 gcloud init 或 gcloud auth login 和 gcloud config set project，确保您已使用身份验证和项目初始化了 Google Cloud CLI。

gcloud healthcare datasets list --location=LOCATION

Windows (PowerShell)

注意：通过运行 gcloud init 或 gcloud auth login 和 gcloud config set project，确保您已使用身份验证和项目初始化了 Google Cloud CLI。

gcloud healthcare datasets list --location=LOCATION

Windows (cmd.exe)

注意：通过运行 gcloud init 或 gcloud auth login 和 gcloud config set project，确保您已使用身份验证和项目初始化了 Google Cloud CLI。

gcloud healthcare datasets list --location=LOCATION

您应该会收到类似如下所示的响应：

ID           LOCATION     TIMEZONE
DATASET_ID   LOCATION       TIME_ZONE

使用 projects.locations.datasets.list 方法。

在使用任何请求数据之前，请先进行以下替换：

• PROJECT_ID：您的 Google Cloud 项目的 ID
• LOCATION：数据集位置

如需发送请求，请选择以下方式之一：

curlPowerShellAPI Explorer

注意：以下命令假定您已使用您的用户账号通过运行 gcloud init 或 gcloud auth login 登录 gcloud CLI，或者使用了 Cloud Shell，这会使您自动登录 gcloud CLI。您可以运行 gcloud auth list 来检查当前活跃的账号。

执行以下命令：

curl -X GET \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     "https://healthcare.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/datasets"

注意：以下命令假定您已使用您的用户账号通过运行 gcloud init 或 gcloud auth login 登录 gcloud CLI。您可以运行 gcloud auth list 来检查当前活跃的账号。

执行以下命令：

$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

Invoke-WebRequest `
    -Method GET `
    -Headers $headers `
    -Uri "https://healthcare.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/datasets" | Select-Object -Expand Content

打开方法参考页面。APIs Explorer 面板会在页面右侧打开。您可以与此工具进行交互以发送请求。 填写所有必填字段，然后点击执行。

您应该收到类似以下内容的 JSON 响应：

响应

{
  "datasets": [
    {
      "name": "projects/PROJECT_ID/locations/LOCATION/datasets/DATASET_ID",
      "timeZone": "TIME_ZONE"
    },
    {
      ...
    }
  ]
}

import (
	"context"
	"fmt"
	"io"

	healthcare "google.golang.org/api/healthcare/v1"
)

// listDatasets prints a list of datasets to w.
func listDatasets(w io.Writer, projectID string, location string) error {
	ctx := context.Background()

	healthcareService, err := healthcare.NewService(ctx)
	if err != nil {
		return fmt.Errorf("healthcare.NewService: %w", err)
	}

	datasetsService := healthcareService.Projects.Locations.Datasets

	parent := fmt.Sprintf("projects/%s/locations/%s", projectID, location)

	resp, err := datasetsService.List(parent).Do()
	if err != nil {
		return fmt.Errorf("List: %w", err)
	}

	fmt.Fprintln(w, "Datasets:")
	for _, d := range resp.Datasets {
		fmt.Fprintln(w, d.Name)
	}

	return nil
}

import com.google.api.client.http.HttpRequestInitializer;
import com.google.api.client.http.javanet.NetHttpTransport;
import com.google.api.client.json.JsonFactory;
import com.google.api.client.json.gson.GsonFactory;
import com.google.api.services.healthcare.v1.CloudHealthcare;
import com.google.api.services.healthcare.v1.CloudHealthcare.Projects.Locations.Datasets;
import com.google.api.services.healthcare.v1.CloudHealthcareScopes;
import com.google.api.services.healthcare.v1.model.Dataset;
import com.google.api.services.healthcare.v1.model.ListDatasetsResponse;
import com.google.auth.http.HttpCredentialsAdapter;
import com.google.auth.oauth2.GoogleCredentials;
import java.io.IOException;
import java.util.ArrayList;
import java.util.Collections;
import java.util.List;

public class DatasetList {
  private static final JsonFactory JSON_FACTORY = new GsonFactory();
  private static final NetHttpTransport HTTP_TRANSPORT = new NetHttpTransport();

  public static void datasetList(String projectId, String regionId) throws IOException {
    // String projectId = "your-project-id";
    // String regionId = "us-central1";

    // Initialize the client, which will be used to interact with the service.
    CloudHealthcare client = createClient();

    // Results are paginated, so multiple queries may be required.
    String parentName = String.format("projects/%s/locations/%s", projectId, regionId);
    String pageToken = null;
    List<Dataset> datasets = new ArrayList<>();
    do {
      // Create request and configure any parameters.
      Datasets.List request =
          client
              .projects()
              .locations()
              .datasets()
              .list(parentName)
              .setPageSize(100) // Specify pageSize up to 1000
              .setPageToken(pageToken);

      // Execute response and collect results.
      ListDatasetsResponse response = request.execute();
      datasets.addAll(response.getDatasets());

      // Update the page token for the next request.
      pageToken = response.getNextPageToken();
    } while (pageToken != null);

    // Print results.
    System.out.printf("Retrieved %s datasets: \n", datasets.size());
    for (Dataset data : datasets) {
      System.out.println("\t" + data.toPrettyString());
    }
  }

  private static CloudHealthcare createClient() throws IOException {
    // Use Application Default Credentials (ADC) to authenticate the requests
    // For more information see https://cloud.google.com/docs/authentication/production
    GoogleCredentials credential =
        GoogleCredentials.getApplicationDefault()
            .createScoped(Collections.singleton(CloudHealthcareScopes.CLOUD_PLATFORM));

    // Create a HttpRequestInitializer, which will provide a baseline configuration to all requests.
    HttpRequestInitializer requestInitializer =
        request -> {
          new HttpCredentialsAdapter(credential).initialize(request);
          request.setConnectTimeout(60000); // 1 minute connect timeout
          request.setReadTimeout(60000); // 1 minute read timeout
        };

    // Build the client for interacting with the service.
    return new CloudHealthcare.Builder(HTTP_TRANSPORT, JSON_FACTORY, requestInitializer)
        .setApplicationName("your-application-name")
        .build();
  }
}

const google = require('@googleapis/healthcare');
const healthcare = google.healthcare({
  version: 'v1',
  auth: new google.auth.GoogleAuth({
    scopes: ['https://www.googleapis.com/auth/cloud-platform'],
  }),
});

const listDatasets = async () => {
  // TODO(developer): uncomment these lines before running the sample
  // const cloudRegion = 'us-central1';
  // const projectId = 'adjective-noun-123';
  const parent = `projects/${projectId}/locations/${cloudRegion}`;
  const request = {parent};

  const dataset = await healthcare.projects.locations.datasets.list(request);
  console.log(dataset.data);
};

listDatasets();

# Imports the Dict and List types for runtime type hints.
from typing import Dict, List


def list_datasets(project_id: str, location: str) -> List[Dict[str, str]]:
    """Lists the datasets in the project.

    See
    https://github.com/GoogleCloudPlatform/python-docs-samples/tree/main/healthcare/api-client/v1/datasets
    before running the sample.
    See https://googleapis.github.io/google-api-python-client/docs/dyn/healthcare_v1.projects.locations.datasets.html#list
    for the Python API reference.

    Args:
      project_id: The project ID or project number of the Google Cloud project you want
          to use.
      location: The name of the location where the datasets are located.

    Returns:
      A list of Dataset resources.
    """
    # Imports HttpError from the Google Python API client errors module.
    # Imports the Google API Discovery Service.
    from googleapiclient import discovery
    from googleapiclient.errors import HttpError

    api_version = "v1"
    service_name = "healthcare"
    # Returns an authorized API client by discovering the Healthcare API
    # and using GOOGLE_APPLICATION_CREDENTIALS environment variable.
    client = discovery.build(service_name, api_version)

    # TODO(developer): Uncomment these lines and replace with your values.
    # project_id = 'my-project'
    # location = 'us-central1'
    dataset_parent = f"projects/{project_id}/locations/{location}"

    datasets = []
    request = client.projects().locations().datasets().list(parent=dataset_parent)
    while request is not None:
        try:
            response = request.execute()
            if response and "datasets" in response:
                datasets.extend(response["datasets"])
            # Paginate over results until the list_next() function returns None.
            request = (
                client.projects()
                .locations()
                .datasets()
                .list_next(previous_request=request, previous_response=response)
            )

            for dataset in datasets:
                print(
                    f"Dataset: {dataset.get('name')}\nTime zone: {dataset.get('timeZone')}"
                )

            return datasets

        except HttpError as err:
            raise err

删除数据集

注意：删除数据集时，数据集中存储的数据及其关联数据也会一并删除。这些数据一旦删除将无法恢复。

以下示例展示了如何删除数据集。

执行此任务所需的权限

如需执行此任务，您必须已获得以下权限或以下 Identity and Access Management (IAM) 角色：

权限

• healthcare.datasets.delete

角色

• Healthcare Dataset Administrator (roles/healthcare.datasetAdmin)

您可以要求管理员为您授予这些 Identity and Access Management 角色。如需了解如何授予角色，请参阅管理访问权限或控制对 Cloud Healthcare API 资源的访问。您也可以通过自定义角色或其他预定义角色来获取所需的权限。

注意：如果您为本指南创建了 Google Cloud 项目，那么作为项目创建者，您会自动获得具有相应权限的 Owner (roles/owner) IAM 角色。您无需获得任何其他 IAM 角色。

控制台gcloudRESTGoJavaNode.jsPython

1. 在 Google Cloud 控制台中，前往浏览器页面。

   转到浏览器

2. 在数据集所在的行中，点击 操作选项，然后选择删除。

3. 在确认对话框中，输入数据集 ID，然后点击删除。

运行 gcloud healthcare datasets delete 命令。

在使用下面的命令数据之前，请先进行以下替换：

• LOCATION：数据集位置
• DATASET_ID：数据集 ID

执行以下命令：

Linux、macOS 或 Cloud Shell

注意：通过运行 gcloud init 或 gcloud auth login 和 gcloud config set project，确保您已使用身份验证和项目初始化了 Google Cloud CLI。

gcloud healthcare datasets delete DATASET_ID \
  --location=LOCATION

Windows (PowerShell)

注意：通过运行 gcloud init 或 gcloud auth login 和 gcloud config set project，确保您已使用身份验证和项目初始化了 Google Cloud CLI。

gcloud healthcare datasets delete DATASET_ID `
  --location=LOCATION

Windows (cmd.exe)

注意：通过运行 gcloud init 或 gcloud auth login 和 gcloud config set project，确保您已使用身份验证和项目初始化了 Google Cloud CLI。

gcloud healthcare datasets delete DATASET_ID ^
  --location=LOCATION

要确认，请键入 Y。

输出如下所示：

Deleted dataset [DATASET_ID]

使用 projects.locations.datasets.delete 方法。

在使用任何请求数据之前，请先进行以下替换：

• PROJECT_ID：您的 Google Cloud 项目的 ID
• LOCATION：数据集位置
• DATASET_ID：数据集 ID

如需发送请求，请选择以下方式之一：

curlPowerShellAPI Explorer

注意：以下命令假定您已使用您的用户账号通过运行 gcloud init 或 gcloud auth login 登录 gcloud CLI，或者使用了 Cloud Shell，这会使您自动登录 gcloud CLI。您可以运行 gcloud auth list 来检查当前活跃的账号。

执行以下命令：

curl -X DELETE \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     "https://healthcare.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/datasets/DATASET_ID"

注意：以下命令假定您已使用您的用户账号通过运行 gcloud init 或 gcloud auth login 登录 gcloud CLI。您可以运行 gcloud auth list 来检查当前活跃的账号。

执行以下命令：

$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

Invoke-WebRequest `
    -Method DELETE `
    -Headers $headers `
    -Uri "https://healthcare.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/datasets/DATASET_ID" | Select-Object -Expand Content

打开方法参考页面。APIs Explorer 面板会在页面右侧打开。您可以与此工具进行交互以发送请求。 填写所有必填字段，然后点击执行。

您应该会收到一个成功的状态代码 (2xx) 和一个空响应。

import (
	"context"
	"fmt"
	"io"

	healthcare "google.golang.org/api/healthcare/v1"
)

// deleteDataset deletes the given dataset.
func deleteDataset(w io.Writer, projectID, location, datasetID string) error {
	ctx := context.Background()

	healthcareService, err := healthcare.NewService(ctx)
	if err != nil {
		return fmt.Errorf("healthcare.NewService: %w", err)
	}

	datasetsService := healthcareService.Projects.Locations.Datasets

	name := fmt.Sprintf("projects/%s/locations/%s/datasets/%s", projectID, location, datasetID)
	if _, err := datasetsService.Delete(name).Do(); err != nil {
		return fmt.Errorf("Delete: %w", err)
	}

	fmt.Fprintf(w, "Deleted dataset: %q\n", name)
	return nil
}

import com.google.api.client.http.HttpRequestInitializer;
import com.google.api.client.http.javanet.NetHttpTransport;
import com.google.api.client.json.JsonFactory;
import com.google.api.client.json.gson.GsonFactory;
import com.google.api.services.healthcare.v1.CloudHealthcare;
import com.google.api.services.healthcare.v1.CloudHealthcare.Projects.Locations.Datasets;
import com.google.api.services.healthcare.v1.CloudHealthcareScopes;
import com.google.auth.http.HttpCredentialsAdapter;
import com.google.auth.oauth2.GoogleCredentials;
import java.io.IOException;
import java.util.Collections;

public class DatasetDelete {
  private static final String DATASET_NAME = "projects/%s/locations/%s/datasets/%s";
  private static final JsonFactory JSON_FACTORY = new GsonFactory();
  private static final NetHttpTransport HTTP_TRANSPORT = new NetHttpTransport();

  public static void datasetDelete(String datasetName) throws IOException {
    // String datasetName =
    //     String.format(DATASET_NAME, "your-project-id", "your-region-id", "your-dataset-id");

    // Initialize the client, which will be used to interact with the service.
    CloudHealthcare client = createClient();

    // Create request and configure any parameters.
    Datasets.Delete request = client.projects().locations().datasets().delete(datasetName);

    // Execute the request and process the results.
    request.execute();
    System.out.println("Dataset deleted.");
  }

  private static CloudHealthcare createClient() throws IOException {
    // Use Application Default Credentials (ADC) to authenticate the requests
    // For more information see https://cloud.google.com/docs/authentication/production
    GoogleCredentials credential =
        GoogleCredentials.getApplicationDefault()
            .createScoped(Collections.singleton(CloudHealthcareScopes.CLOUD_PLATFORM));

    // Create a HttpRequestInitializer, which will provide a baseline configuration to all requests.
    HttpRequestInitializer requestInitializer =
        request -> {
          new HttpCredentialsAdapter(credential).initialize(request);
          request.setConnectTimeout(60000); // 1 minute connect timeout
          request.setReadTimeout(60000); // 1 minute read timeout
        };

    // Build the client for interacting with the service.
    return new CloudHealthcare.Builder(HTTP_TRANSPORT, JSON_FACTORY, requestInitializer)
        .setApplicationName("your-application-name")
        .build();
  }
}

const google = require('@googleapis/healthcare');
const healthcare = google.healthcare({
  version: 'v1',
  auth: new google.auth.GoogleAuth({
    scopes: ['https://www.googleapis.com/auth/cloud-platform'],
  }),
});

const deleteDataset = async () => {
  // TODO(developer): uncomment these lines before running the sample
  // const cloudRegion = 'us-central1';
  // const projectId = 'adjective-noun-123';
  // const datasetId = 'my-dataset';
  const parent = `projects/${projectId}/locations/${cloudRegion}/datasets/${datasetId}`;
  const request = {name: parent};

  await healthcare.projects.locations.datasets.delete(request);
  console.log(`Deleted dataset: ${datasetId}`);
};

deleteDataset();

def delete_dataset(project_id: str, location: str, dataset_id: str) -> None:
    """Deletes a dataset.

    See
    https://github.com/GoogleCloudPlatform/python-docs-samples/tree/main/healthcare/api-client/v1/datasets
    before running the sample.
    See https://googleapis.github.io/google-api-python-client/docs/dyn/healthcare_v1.projects.locations.datasets.html#delete
    for the Python API reference.

    Args:
      project_id: The project ID or project number of the Google Cloud project you want
          to use.
      location: The name of the dataset's location.
      dataset_id: The name of the dataset to delete.

    Returns:
      An empty response body.
    """
    # Imports HttpError from the Google Python API client errors module.
    # Imports the Google API Discovery Service.
    from googleapiclient import discovery
    from googleapiclient.errors import HttpError

    api_version = "v1"
    service_name = "healthcare"
    # Returns an authorized API client by discovering the Healthcare API
    # and using GOOGLE_APPLICATION_CREDENTIALS environment variable.
    client = discovery.build(service_name, api_version)

    # TODO(developer): Uncomment these lines and replace with your values.
    # project_id = 'my-project'
    # location = 'us-central1'
    # dataset_id = 'my-dataset'
    dataset_name = f"projects/{project_id}/locations/{location}/datasets/{dataset_id}"

    request = client.projects().locations().datasets().delete(name=dataset_name)

    try:
        request.execute()
        print(f"Deleted dataset: {dataset_id}")
    except HttpError as err:
        raise err

后续步骤

• 敏感数据去标识化
• 创建和管理 DICOM 存储区
• 创建和管理 FHIR 存储区
• 创建和管理 HL7v2 商店