데이터 세트 만들기 및 관리

이 페이지에서는 데이터 세트를 생성, 수정, 보기, 나열, 삭제하는 방법을 설명합니다. 데이터 세트를 만든 후에는 전자 건강 기록과 의료 영상 데이터를 저장하는 데이터 저장소를 만들고 데이터 세트를 익명화하는 등의 작업을 수행할 수 있습니다.

시작하기 전에

Cloud Healthcare API 데이터 모델을 참조하세요.

데이터 세트 생성

다음 샘플에서는 데이터 세트를 만드는 방법을 보여줍니다.

콘솔

  1. Google Cloud 콘솔에서 브라우저 페이지로 이동합니다.

    브라우저로 이동

  2. 데이터 세트 만들기를 클릭합니다. 데이터 세트 속성 페이지가 표시됩니다.

  3. 이름 필드에 데이터 세트 허용 문자 및 크기 요구사항에 따라 데이터 세트 식별자를 입력합니다.

  4. 다음 위치 유형 중 하나를 선택합니다.

    • Region 사용). 데이터 세트가 Google Cloud 리전 하나 내에 영구적으로 있습니다. 이 옵션을 선택한 후 리전 필드에 위치를 입력하거나 선택합니다.

    • 멀티 리전. 데이터 세트는 여러 Google Cloud 리전에 걸쳐 있는 위치 내에 영구적으로 있습니다. 이 옵션을 선택한 후 멀티 리전 필드에 멀티 리전 위치를 입력하거나 선택합니다.

  5. 만들기를 클릭합니다. 브라우저 페이지가 표시됩니다. 새 데이터 세트가 데이터 세트 목록에 표시됩니다.

gcloud

gcloud healthcare datasets create 명령어를 실행합니다.

아래의 명령어 데이터를 사용하기 전에 다음을 바꿉니다.

다음 명령어를 실행합니다.

Linux, macOS 또는 Cloud Shell

gcloud healthcare datasets create DATASET_ID \
  --location=LOCATION

Windows(PowerShell)

gcloud healthcare datasets create DATASET_ID `
  --location=LOCATION

Windows(cmd.exe)

gcloud healthcare datasets create DATASET_ID ^
  --location=LOCATION

다음과 비슷한 응답이 표시됩니다.

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

REST

projects.locations.datasets.create 메서드를 사용합니다.

  1. 데이터 세트를 만듭니다.

    요청 데이터를 사용하기 전에 다음을 바꿉니다.

    요청을 보내려면 다음 옵션 중 하나를 선택합니다.

    curl

    다음 명령어를 실행합니다.

    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"

    PowerShell

    다음 명령어를 실행합니다.

    $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

    API 탐색기

    메서드 참조 페이지를 엽니다. 페이지 오른쪽에 API 탐색기 패널이 열립니다. 이 도구를 사용하여 요청을 보낼 수 있습니다. 모든 필수 필드를 입력하고 실행을 클릭합니다.

    출력은 다음과 같습니다. 응답에는 장기 실행 작업(LRO)의 식별자가 포함됩니다. 장기 실행 작업은 메서드 호출을 완료하는 데 추가 시간이 걸릴 수 있는 경우에 반환됩니다. OPERATION_ID의 값을 확인합니다. 다음 단계에서 이 값이 필요합니다.

  2. projects.locations.datasets.operations.get 메서드를 사용하여 장기 실행 작업의 상태를 가져옵니다.

    요청 데이터를 사용하기 전에 다음을 바꿉니다.

    • PROJECT_ID: Google Cloud 프로젝트의 ID
    • LOCATION: 데이터 세트 위치
    • DATASET_ID: 생성 중인 데이터 세트의 ID
    • OPERATION_ID: 장기 실행 작업의 ID

    요청을 보내려면 다음 옵션 중 하나를 선택합니다.

    curl

    다음 명령어를 실행합니다.

    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"

    PowerShell

    다음 명령어를 실행합니다.

    $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

    API 탐색기

    메서드 참조 페이지를 엽니다. 페이지 오른쪽에 API 탐색기 패널이 열립니다. 이 도구를 사용하여 요청을 보낼 수 있습니다. 모든 필수 필드를 입력하고 실행을 클릭합니다.

    출력은 다음과 같습니다. 응답에는 데이터 세트가 성공적으로 생성되었음을 나타내는 "done": true가 포함됩니다.

Go

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
}

Java

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();
  }
}

Node.js

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();

Python

# 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

데이터 세트 수정

다음 샘플에서는 데이터 세트를 수정하는 방법을 보여줍니다.

콘솔

Google Cloud 콘솔에서 데이터 세트를 수정할 수 없습니다. 대신 Google Cloud CLI 또는 REST API를 사용합니다.

gcloud

gcloud healthcare datasets update 명령어를 실행합니다.

아래의 명령어 데이터를 사용하기 전에 다음을 바꿉니다.

  • LOCATION: 데이터 세트 위치
  • DATASET_ID: 데이터 세트 ID
  • TIME_ZONE: 지원되는 시간대(예: UTC)

다음 명령어를 실행합니다.

Linux, macOS 또는 Cloud Shell

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

Windows(PowerShell)

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

Windows(cmd.exe)

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

다음과 비슷한 응답이 표시됩니다.

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

REST

projects.locations.datasets.patch 메서드를 사용합니다.

요청 데이터를 사용하기 전에 다음을 바꿉니다.

  • PROJECT_ID: Google Cloud 프로젝트의 ID
  • LOCATION: 데이터 세트 위치
  • DATASET_ID: 데이터 세트 ID
  • TIME_ZONE: 지원되는 시간대(예: UTC)

JSON 요청 본문:

{
  "timeZone": "TIME_ZONE"
}

요청을 보내려면 다음 옵션 중 하나를 선택합니다.

curl

요청 본문을 request.json 파일에 저장하고 다음 명령어를 실행합니다.

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"

PowerShell

요청 본문을 request.json 파일에 저장하고 다음 명령어를 실행합니다.

$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

API 탐색기

요청 본문을 복사하고 메서드 참조 페이지를 엽니다. 페이지 오른쪽에 API 탐색기 패널이 열립니다. 이 도구를 사용하여 요청을 보낼 수 있습니다. 요청 본문을 이 도구에 붙여넣고 다른 필수 필드를 입력한 후 실행을 클릭합니다.

다음과 비슷한 JSON 응답이 표시됩니다.

Go

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
}

Java

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();
  }
}

Node.js

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();

Python

# 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

데이터 세트 세부정보 가져오기

다음 샘플에서는 데이터 세트에 대한 세부정보를 가져오는 방법을 보여줍니다.

콘솔

  1. Google Cloud 콘솔에서 브라우저 페이지로 이동합니다.

    브라우저로 이동

  2. 데이터 세트를 선택합니다. 데이터 세트 페이지와 데이터 세트의 데이터 저장소가 표시됩니다.

gcloud

gcloud healthcare datasets describe 명령어를 실행합니다.

아래의 명령어 데이터를 사용하기 전에 다음을 바꿉니다.

  • LOCATION: 데이터 세트 위치
  • DATASET_ID: 데이터 세트 ID

다음 명령어를 실행합니다.

Linux, macOS 또는 Cloud Shell

gcloud healthcare datasets describe DATASET_ID \
  --location=LOCATION

Windows(PowerShell)

gcloud healthcare datasets describe DATASET_ID `
  --location=LOCATION

Windows(cmd.exe)

gcloud healthcare datasets describe DATASET_ID ^
  --location=LOCATION

다음과 비슷한 응답이 표시됩니다.

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

REST

projects.locations.datasets.get 메서드를 사용합니다.

요청 데이터를 사용하기 전에 다음을 바꿉니다.

  • PROJECT_ID: Google Cloud 프로젝트의 ID
  • LOCATION: 데이터 세트 위치
  • DATASET_ID: 데이터 세트 ID

요청을 보내려면 다음 옵션 중 하나를 선택합니다.

curl

다음 명령어를 실행합니다.

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

PowerShell

다음 명령어를 실행합니다.

$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

API 탐색기

메서드 참조 페이지를 엽니다. 페이지 오른쪽에 API 탐색기 패널이 열립니다. 이 도구를 사용하여 요청을 보낼 수 있습니다. 모든 필수 필드를 입력하고 실행을 클릭합니다.

다음과 비슷한 JSON 응답이 표시됩니다.

Go

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
}

Java

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();
  }
}

Node.js

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();

Python

# 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

데이터 세트 나열

다음 예시는 프로젝트의 데이터 세트를 나열하는 방법을 보여줍니다.

콘솔

Google Cloud 콘솔에서 브라우저 페이지로 이동합니다.

브라우저로 이동

gcloud

gcloud healthcare datasets list 명령어를 실행합니다.

아래의 명령어 데이터를 사용하기 전에 다음을 바꿉니다.

  • LOCATION: 데이터 세트 위치

다음 명령어를 실행합니다.

Linux, macOS 또는 Cloud Shell

gcloud healthcare datasets list --location=LOCATION

Windows(PowerShell)

gcloud healthcare datasets list --location=LOCATION

Windows(cmd.exe)

gcloud healthcare datasets list --location=LOCATION

다음과 비슷한 응답이 표시됩니다.

ID           LOCATION     TIMEZONE
DATASET_ID   LOCATION       TIME_ZONE

REST

projects.locations.datasets.list 메서드를 사용합니다.

요청 데이터를 사용하기 전에 다음을 바꿉니다.

  • PROJECT_ID: Google Cloud 프로젝트의 ID
  • LOCATION: 데이터 세트 위치

요청을 보내려면 다음 옵션 중 하나를 선택합니다.

curl

다음 명령어를 실행합니다.

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

PowerShell

다음 명령어를 실행합니다.

$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

API 탐색기

메서드 참조 페이지를 엽니다. 페이지 오른쪽에 API 탐색기 패널이 열립니다. 이 도구를 사용하여 요청을 보낼 수 있습니다. 모든 필수 필드를 입력하고 실행을 클릭합니다.

다음과 비슷한 JSON 응답이 표시됩니다.

Go

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
}

Java

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();
  }
}

Node.js

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();

Python

# 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

데이터 세트 삭제

다음 샘플에서는 데이터 세트를 삭제하는 방법을 보여줍니다.

콘솔

  1. Google Cloud 콘솔에서 브라우저 페이지로 이동합니다.

    브라우저로 이동

  2. 데이터 세트와 동일한 행에서 작업 옵션을 클릭한 후 삭제를 선택합니다.

  3. 확인 대화상자에서 데이터 세트 ID를 입력한 후 삭제를 클릭합니다.

gcloud

gcloud healthcare datasets delete 명령어를 실행합니다.

아래의 명령어 데이터를 사용하기 전에 다음을 바꿉니다.

  • LOCATION: 데이터 세트 위치
  • DATASET_ID: 데이터 세트 ID

다음 명령어를 실행합니다.

Linux, macOS 또는 Cloud Shell

gcloud healthcare datasets delete DATASET_ID \
  --location=LOCATION

Windows(PowerShell)

gcloud healthcare datasets delete DATASET_ID `
  --location=LOCATION

Windows(cmd.exe)

gcloud healthcare datasets delete DATASET_ID ^
  --location=LOCATION

확인하려면 Y를 입력합니다.

출력은 다음과 같습니다.

Deleted dataset [DATASET_ID]

REST

projects.locations.datasets.delete 메서드를 사용합니다.

요청 데이터를 사용하기 전에 다음을 바꿉니다.

  • PROJECT_ID: Google Cloud 프로젝트의 ID
  • LOCATION: 데이터 세트 위치
  • DATASET_ID: 데이터 세트 ID

요청을 보내려면 다음 옵션 중 하나를 선택합니다.

curl

다음 명령어를 실행합니다.

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

PowerShell

다음 명령어를 실행합니다.

$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

API 탐색기

메서드 참조 페이지를 엽니다. 페이지 오른쪽에 API 탐색기 패널이 열립니다. 이 도구를 사용하여 요청을 보낼 수 있습니다. 모든 필수 필드를 입력하고 실행을 클릭합니다.

성공 상태 코드(2xx)와 빈 응답을 받게 됩니다.

Go

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
}

Java

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();
  }
}

Node.js

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();

Python

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

다음 단계