使用 Cloud 用戶端程式庫執行工作流程

本快速入門導覽課程說明如何使用 Cloud 用戶端程式庫執行工作流程,以及查看執行結果。

如要進一步瞭解如何安裝 Cloud 用戶端程式庫及設定開發環境,請參閱 Workflows 用戶端程式庫總覽

您可以在終端機或 Cloud Shell 中使用 Google Cloud CLI 完成下列步驟。

事前準備

貴機構定義的安全性限制,可能會導致您無法完成下列步驟。如需疑難排解資訊,請參閱「在受限的 Google Cloud 環境中開發應用程式」。

  1. Sign in to your Google Cloud account. If you're new to Google Cloud, create an account to evaluate how our products perform in real-world scenarios. New customers also get $300 in free credits to run, test, and deploy workloads.
  2. Install the Google Cloud CLI.

  3. If you're using an external identity provider (IdP), you must first sign in to the gcloud CLI with your federated identity.

  4. To initialize the gcloud CLI, run the following command:

    gcloud init
  5. Create or select a Google Cloud project.

    • Create a Google Cloud project:

      gcloud projects create PROJECT_ID

      Replace PROJECT_ID with a name for the Google Cloud project you are creating.

    • Select the Google Cloud project that you created:

      gcloud config set project PROJECT_ID

      Replace PROJECT_ID with your Google Cloud project name.

  6. Make sure that billing is enabled for your Google Cloud project.

  7. Enable the Workflows API:

    gcloud services enable workflows.googleapis.com
  8. Set up authentication:

    1. Create the service account:

      gcloud iam service-accounts create SERVICE_ACCOUNT_NAME

      Replace SERVICE_ACCOUNT_NAME with a name for the service account.

    2. Grant the roles/owner IAM role to the service account:

      gcloud projects add-iam-policy-binding PROJECT_ID --member="serviceAccount:SERVICE_ACCOUNT_NAME@PROJECT_ID.iam.gserviceaccount.com" --role=roles/owner

      Replace the following:

      • SERVICE_ACCOUNT_NAME: the name of the service account
      • PROJECT_ID: the project ID where you created the service account
  9. Install the Google Cloud CLI.

  10. If you're using an external identity provider (IdP), you must first sign in to the gcloud CLI with your federated identity.

  11. To initialize the gcloud CLI, run the following command:

    gcloud init
  12. Create or select a Google Cloud project.

    • Create a Google Cloud project:

      gcloud projects create PROJECT_ID

      Replace PROJECT_ID with a name for the Google Cloud project you are creating.

    • Select the Google Cloud project that you created:

      gcloud config set project PROJECT_ID

      Replace PROJECT_ID with your Google Cloud project name.

  13. Make sure that billing is enabled for your Google Cloud project.

  14. Enable the Workflows API:

    gcloud services enable workflows.googleapis.com
  15. Set up authentication:

    1. Create the service account:

      gcloud iam service-accounts create SERVICE_ACCOUNT_NAME

      Replace SERVICE_ACCOUNT_NAME with a name for the service account.

    2. Grant the roles/owner IAM role to the service account:

      gcloud projects add-iam-policy-binding PROJECT_ID --member="serviceAccount:SERVICE_ACCOUNT_NAME@PROJECT_ID.iam.gserviceaccount.com" --role=roles/owner

      Replace the following:

      • SERVICE_ACCOUNT_NAME: the name of the service account
      • PROJECT_ID: the project ID where you created the service account
  16. (選用) 如要將記錄傳送至 Cloud Logging,請將 roles/logging.logWriter 角色授予服務帳戶。

    gcloud projects add-iam-policy-binding PROJECT_ID \
        --member "serviceAccount:SERVICE_ACCOUNT_NAME@PROJECT_ID.iam.gserviceaccount.com" \
        --role "roles/logging.logWriter"

    如要進一步瞭解服務帳戶角色和權限,請參閱「授予工作流程存取Google Cloud 資源的權限」。

  17. 視需要下載並安裝 Git 原始碼管理工具。

部署工作流程範例

定義工作流程後,您就可以部署工作流程,讓系統執行。部署步驟也會驗證來源檔案是否可執行。

以下工作流程會傳送要求至公用 API,然後傳回 API 的回應。

  1. 建立檔案名稱為 myFirstWorkflow.yaml 的文字檔案,並在其中加入下列內容:

    # This workflow accepts an optional "searchTerm" argument for the Wikipedia API.
    # If no input arguments are provided or "searchTerm" is absent,
    # it will fetch the day of the week in Amsterdam and use it as the search term.
    
    main:
        params: [input]
        steps:
        - validateSearchTermAndRedirectToReadWikipedia:
            switch:
                - condition: '${map.get(input, "searchTerm") != null}'
                  assign:
                    - searchTerm: '${input.searchTerm}'
                  next: readWikipedia
        - getCurrentTime:
            call: http.get
            args:
                url: https://timeapi.io/api/Time/current/zone?timeZone=Europe/Amsterdam
            result: currentTime
        - setFromCallResult:
            assign:
                - searchTerm: '${currentTime.body.dayOfWeek}'
        - readWikipedia:
            call: http.get
            args:
                url: 'https://en.wikipedia.org/w/api.php'
                query:
                    action: opensearch
                    search: '${searchTerm}'
            result: wikiResult
        - returnOutput:
                return: '${wikiResult.body[1]}'
  2. 建立工作流程後,您可以部署工作流程,但請勿執行工作流程:

    gcloud workflows deploy myFirstWorkflow \
        --source=myFirstWorkflow.yaml \
        --service-account=SERVICE_ACCOUNT_NAME@PROJECT_ID.iam.gserviceaccount.com \
        --location=CLOUD_REGION

    CLOUD_REGION 替換為工作流程支援的位置。程式碼範例中使用的預設區域為 us-central1

取得程式碼範例

您可以從 GitHub 複製程式碼範例。

  1. 將應用程式存放區範例複製到本機電腦中:

    C#

    git clone https://github.com/GoogleCloudPlatform/dotnet-docs-samples.git

    您也可以 下載 zip 格式的範例,然後解壓縮該檔案。

    Go

    git clone https://github.com/GoogleCloudPlatform/golang-samples.git

    您也可以 下載 zip 格式的範例,然後解壓縮該檔案。

    Java

    git clone https://github.com/GoogleCloudPlatform/java-docs-samples.git

    您也可以 下載 zip 格式的範例,然後解壓縮該檔案。

    Node.js

    git clone https://github.com/GoogleCloudPlatform/nodejs-docs-samples.git

    您也可以 下載 zip 格式的範例,然後解壓縮該檔案。

    Python

    git clone https://github.com/GoogleCloudPlatform/python-docs-samples.git

    您也可以 下載 zip 格式的範例,然後解壓縮該檔案。

  2. 變更為包含 Workflow 範例程式碼的目錄:

    C#

    cd dotnet-docs-samples/workflows/api/Workflow.Samples/

    Go

    cd golang-samples/workflows/executions/

    Java

    cd java-docs-samples/workflows/cloud-client/

    Node.js

    cd nodejs-docs-samples/workflows/quickstart/

    Python

    cd python-docs-samples/workflows/cloud-client/

  3. 請查看程式碼範例。每個範例應用程式都會執行下列作業:

    1. 設定工作流程的 Cloud 用戶端程式庫。
    2. 執行工作流程。
    3. 輪詢工作流程的執行作業 (使用指數輪詢),直到執行作業結束為止。
    4. 列印執行結果。

    C#

    
    using Google.Cloud.Workflows.Common.V1;
    using Google.Cloud.Workflows.Executions.V1;
    using System;
    using System.Threading;
    using System.Threading.Tasks;
    
    public class ExecuteWorkflowSample
    {
        /// <summary>
        /// Execute a workflow and return the execution operation.
        /// </summary>
        /// <param name="projectID">Your Google Cloud Project ID.</param>
        /// <param name="locationID">The region where your workflow is located.</param>
        /// <param name="workflowID">Your Workflow ID.</param>
        /// <returns>
        /// An Execute object representing the completed workflow execution.
        /// </returns>
        public async Task<Execution> ExecuteWorkflow(
            string projectId = "YOUR-PROJECT-ID",
            string locationID = "YOUR-LOCATION-ID",
            string workflowID = "YOUR-WORKFLOW-ID")
        {
            // Initialize the client.
            ExecutionsClient client = await ExecutionsClient.CreateAsync();
    
            // Build the parent location path.
            WorkflowName parent = new WorkflowName(projectId, locationID, workflowID);
    
            // Create an execution request.
            CreateExecutionRequest createExecutionRequest = new CreateExecutionRequest
            {
                ParentAsWorkflowName = parent,
            };
    
            // Execute the operation.
            Execution execution = await client.CreateExecutionAsync(createExecutionRequest);
            Console.WriteLine("- Execution started...");
    
            TimeSpan backoffDelay = TimeSpan.FromSeconds(1);
            TimeSpan maxBackoffDelay = TimeSpan.FromSeconds(16);
    
            // Keep polling the state until the execution finishes, using exponential backoff.
            while (execution.State == Execution.Types.State.Active)
            {
                await Task.Delay(backoffDelay);
    
                // Implement exponential backoff by doubling the delay, but limiting it to a practical duration.
                backoffDelay = (backoffDelay < maxBackoffDelay) ? backoffDelay * 2 : maxBackoffDelay;
    
                execution = await client.GetExecutionAsync(execution.Name);
            }
    
            // Print results.
            Console.WriteLine($"Execution finished with state: {execution.State}");
            Console.WriteLine($"Execution results: {execution.Result}");
    
            // Return the fetched execution.
            return execution;
        }
    }

    Go

    import (
    	"context"
    	"fmt"
    	"io"
    	"time"
    
    	workflowexecutions "google.golang.org/api/workflowexecutions/v1"
    )
    
    // Execute a workflow and print the execution results.
    //
    // For more information about Workflows see:
    // https://cloud.google.com/workflows/docs/overview
    func executeWorkflow(w io.Writer, projectID, workflowID, locationID string) error {
    	// TODO(developer): Uncomment and update the following lines:
    	// projectID := "YOUR_PROJECT_ID"
    	// workflowID := "YOUR_WORKFLOW_ID"
    	// locationID := "YOUR_LOCATION_ID"
    
    	ctx := context.Background()
    
    	// Construct the location path.
    	parent := fmt.Sprintf("projects/%s/locations/%s/workflows/%s", projectID, locationID, workflowID)
    
    	// Create execution client.
    	client, err := workflowexecutions.NewService(ctx)
    	if err != nil {
    		return fmt.Errorf("workflowexecutions.NewService error: %w", err)
    	}
    
    	// Get execution service.
    	service := client.Projects.Locations.Workflows.Executions
    
    	// Build and run the new workflow execution.
    	res, err := service.Create(parent, &workflowexecutions.Execution{}).Do()
    	if err != nil {
    		return fmt.Errorf("service.Create.Do error: %w", err)
    	}
    	fmt.Fprintln(w, "- Execution started...")
    
    	// Set initial value for backoff delay in one second.
    	backoffDelay := time.Second
    
    	for res.State == "ACTIVE" {
    		time.Sleep(backoffDelay)
    
    		// Request the updated state for the execution.
    		getReq := service.Get(res.Name)
    		res, err = getReq.Do()
    		if err != nil {
    			return fmt.Errorf("getReq error: %w", err)
    		}
    
    		// Double the delay to provide exponential backoff (capped at 16 seconds).
    		if backoffDelay < time.Second*16 {
    			backoffDelay *= 2
    		}
    	}
    
    	fmt.Fprintf(w, "Execution finished with state: %s\n", res.State)
    	fmt.Fprintf(w, "Execution results: %s\n", res.Result)
    
    	return nil
    }
    

    Java

    // Imports the Google Cloud client library
    
    import com.google.cloud.workflows.executions.v1.CreateExecutionRequest;
    import com.google.cloud.workflows.executions.v1.Execution;
    import com.google.cloud.workflows.executions.v1.ExecutionsClient;
    import com.google.cloud.workflows.executions.v1.WorkflowName;
    import java.io.IOException;
    import java.util.concurrent.ExecutionException;
    
    public class WorkflowsQuickstart {
    
      private static final String PROJECT = System.getenv("GOOGLE_CLOUD_PROJECT");
      private static final String LOCATION = System.getenv().getOrDefault("LOCATION", "us-central1");
      private static final String WORKFLOW =
          System.getenv().getOrDefault("WORKFLOW", "myFirstWorkflow");
    
      public static void main(String... args)
          throws IOException, InterruptedException, ExecutionException {
        if (PROJECT == null) {
          throw new IllegalArgumentException(
              "Environment variable 'GOOGLE_CLOUD_PROJECT' is required to run this quickstart.");
        }
        workflowsQuickstart(PROJECT, LOCATION, WORKFLOW);
      }
    
      private static volatile boolean finished;
    
      public static void workflowsQuickstart(String projectId, String location, String workflow)
          throws IOException, InterruptedException, ExecutionException {
        // Initialize client that will be used to send requests. This client only needs
        // to be created once, and can be reused for multiple requests. After completing all of your
        // requests, call the "close" method on the client to safely clean up any remaining background
        // resources.
        try (ExecutionsClient executionsClient = ExecutionsClient.create()) {
          // Construct the fully qualified location path.
          WorkflowName parent = WorkflowName.of(projectId, location, workflow);
    
          // Creates the execution object.
          CreateExecutionRequest request =
              CreateExecutionRequest.newBuilder()
                  .setParent(parent.toString())
                  .setExecution(Execution.newBuilder().build())
                  .build();
          Execution response = executionsClient.createExecution(request);
    
          String executionName = response.getName();
          System.out.printf("Created execution: %s%n", executionName);
    
          long backoffTime = 0;
          long backoffDelay = 1_000; // Start wait with delay of 1,000 ms
          final long backoffTimeout = 10 * 60 * 1_000; // Time out at 10 minutes
          System.out.println("Poll for results...");
    
          // Wait for execution to finish, then print results.
          while (!finished && backoffTime < backoffTimeout) {
            Execution execution = executionsClient.getExecution(executionName);
            finished = execution.getState() != Execution.State.ACTIVE;
    
            // If we haven't seen the results yet, wait.
            if (!finished) {
              System.out.println("- Waiting for results");
              Thread.sleep(backoffDelay);
              backoffTime += backoffDelay;
              backoffDelay *= 2; // Double the delay to provide exponential backoff.
            } else {
              System.out.println("Execution finished with state: " + execution.getState().name());
              System.out.println("Execution results: " + execution.getResult());
            }
          }
        }
      }
    }

    Node.js

    const {ExecutionsClient} = require('@google-cloud/workflows');
    const client = new ExecutionsClient();
    /**
     * TODO(developer): Uncomment these variables before running the sample.
     */
    // const projectId = 'my-project';
    // const location = 'us-central1';
    // const workflow = 'myFirstWorkflow';
    // const searchTerm = '';
    
    /**
     * Executes a Workflow and waits for the results with exponential backoff.
     * @param {string} projectId The Google Cloud Project containing the workflow
     * @param {string} location The workflow location
     * @param {string} workflow The workflow name
     * @param {string} searchTerm Optional search term to pass to the Workflow as a runtime argument
     */
    async function executeWorkflow(projectId, location, workflow, searchTerm) {
      /**
       * Sleeps the process N number of milliseconds.
       * @param {Number} ms The number of milliseconds to sleep.
       */
      function sleep(ms) {
        return new Promise(resolve => {
          setTimeout(resolve, ms);
        });
      }
      const runtimeArgs = searchTerm ? {searchTerm: searchTerm} : {};
      // Execute workflow
      try {
        const createExecutionRes = await client.createExecution({
          parent: client.workflowPath(projectId, location, workflow),
          execution: {
            // Runtime arguments can be passed as a JSON string
            argument: JSON.stringify(runtimeArgs),
          },
        });
        const executionName = createExecutionRes[0].name;
        console.log(`Created execution: ${executionName}`);
    
        // Wait for execution to finish, then print results.
        let executionFinished = false;
        let backoffDelay = 1000; // Start wait with delay of 1,000 ms
        console.log('Poll every second for result...');
        while (!executionFinished) {
          const [execution] = await client.getExecution({
            name: executionName,
          });
          executionFinished = execution.state !== 'ACTIVE';
    
          // If we haven't seen the result yet, wait a second.
          if (!executionFinished) {
            console.log('- Waiting for results...');
            await sleep(backoffDelay);
            backoffDelay *= 2; // Double the delay to provide exponential backoff.
          } else {
            console.log(`Execution finished with state: ${execution.state}`);
            console.log(execution.result);
            return execution.result;
          }
        }
      } catch (e) {
        console.error(`Error executing workflow: ${e}`);
      }
    }
    
    executeWorkflow(projectId, location, workflowName, searchTerm).catch(err => {
      console.error(err.message);
      process.exitCode = 1;
    });
    

    Python

    import time
    
    from google.cloud import workflows_v1
    from google.cloud.workflows import executions_v1
    
    from google.cloud.workflows.executions_v1.types import executions
    
    # TODO(developer): Update and uncomment the following lines.
    # project_id = "YOUR_PROJECT_ID"
    # location = "YOUR_LOCATION"  # For example: us-central1
    # workflow_id = "YOUR_WORKFLOW_ID"  # For example: myFirstWorkflow
    
    # Initialize API clients.
    execution_client = executions_v1.ExecutionsClient()
    workflows_client = workflows_v1.WorkflowsClient()
    
    # Construct the fully qualified location path.
    parent = workflows_client.workflow_path(project_id, location, workflow_id)
    
    # Execute the workflow.
    response = execution_client.create_execution(request={"parent": parent})
    print(f"Created execution: {response.name}")
    
    # Wait for execution to finish, then print results.
    execution_finished = False
    backoff_delay = 1  # Start wait with delay of 1 second.
    print("Poll for result...")
    
    # Keep polling the state until the execution finishes,
    # using exponential backoff.
    while not execution_finished:
        execution = execution_client.get_execution(
            request={"name": response.name}
        )
        execution_finished = execution.state != executions.Execution.State.ACTIVE
    
        # If we haven't seen the result yet, keep waiting.
        if not execution_finished:
            print("- Waiting for results...")
            time.sleep(backoff_delay)
            # Double the delay to provide exponential backoff.
            backoff_delay *= 2
        else:
            print(f"Execution finished with state: {execution.state.name}")
            print(f"Execution results: {execution.result}")

執行程式碼範例

您可以執行範例程式碼,並執行工作流程。執行工作流程會執行與工作流程相關聯的已部署工作流程定義。

  1. 如要執行範例,請先安裝依附元件:

    C#

    dotnet restore

    Go

    go mod download

    Java

    mvn compile

    Node.js

    npm install -D tsx

    Python

    pip3 install -r requirements.txt

  2. 執行指令碼:

    C#

    GOOGLE_CLOUD_PROJECT=PROJECT_ID LOCATION=CLOUD_REGION WORKFLOW=WORKFLOW_NAME dotnet run

    Go

    GOOGLE_CLOUD_PROJECT=PROJECT_ID LOCATION=CLOUD_REGION WORKFLOW=WORKFLOW_NAME go run .

    Java

    GOOGLE_CLOUD_PROJECT=PROJECT_ID LOCATION=CLOUD_REGION WORKFLOW=WORKFLOW_NAME mvn compile exec:java -Dexec.mainClass=com.example.workflows.WorkflowsQuickstart

    Node.js

    npx tsx index.js

    Python

    GOOGLE_CLOUD_PROJECT=PROJECT_ID LOCATION=CLOUD_REGION WORKFLOW=WORKFLOW_NAME python3 main.py

    更改下列內容:

    • PROJECT_ID:您的 Google Cloud 專案名稱
    • CLOUD_REGION:工作流程的位置 (預設值:us-central1)
    • WORKFLOW_NAME:工作流程名稱 (預設:myFirstWorkflow)

    輸出結果會與下列內容相似:

    Execution finished with state: SUCCEEDED
    Execution results: ["Thursday","Thursday Night Football","Thursday (band)","Thursday Island","Thursday (album)","Thursday Next","Thursday at the Square","Thursday's Child (David Bowie song)","Thursday Afternoon","Thursday (film)"]
    

在執行要求中傳遞資料

視用戶端程式庫語言而定,您也可以在執行要求中傳遞執行階段引數。例如:

C#


public class ExecuteWorkflowWithArgumentsSample
{
    /// <summary>
    /// Execute a workflow with arguments and return the execution operation.
    /// </summary>
    /// <param name="projectID">Your Google Cloud Project ID.</param>
    /// <param name="locationID">The region where your workflow is located.</param>
    /// <param name="workflowID">Your Workflow ID.</param>
    /// <returns>
    /// An Execute object representing the completed workflow execution.
    /// </returns>
    public async Task<Execution> ExecuteWorkflowWithArguments(
        string projectId = "YOUR-PROJECT-ID",
        string locationID = "YOUR-LOCATION-ID",
        string workflowID = "YOUR-WORKFLOW-ID")
    {
        // Initialize the client.
        ExecutionsClient client = await ExecutionsClient.CreateAsync();

        // Build the parent location path.
        WorkflowName parent = new WorkflowName(projectId, locationID, workflowID);

        // Serialize the argument.
        string argument = JsonSerializer.Serialize(new
        {
            searchTerm = "Cloud"
        });

        // Create an execution request.
        CreateExecutionRequest createExecutionRequest = new CreateExecutionRequest
        {
            ParentAsWorkflowName = parent,
            Execution = new Execution
            {
                Argument = argument,
            }
        };

        // Execute the operation and recieve the execution.
        Execution execution = await client.CreateExecutionAsync(createExecutionRequest);
        Console.WriteLine("- Execution started...");

        TimeSpan backoffDelay = TimeSpan.FromSeconds(1);
        TimeSpan maxBackoffDelay = TimeSpan.FromSeconds(16);

        // Keep polling the state until the execution finishes, using exponential backoff.
        while (execution.State == Execution.Types.State.Active)
        {
            await Task.Delay(backoffDelay);

            // Implement exponential backoff by doubling the delay, but limiting it to a practical duration.
            backoffDelay = (backoffDelay < maxBackoffDelay) ? backoffDelay * 2 : maxBackoffDelay;

            execution = await client.GetExecutionAsync(execution.Name);
        }

        // Print results.
        Console.WriteLine($"Execution finished with state: {execution.State}");
        Console.WriteLine($"Execution results: {execution.Result}");

        // Return the fetched execution.
        return execution;
    }
}

Go

import (
	"context"
	"encoding/json"
	"fmt"
	"io"
	"time"

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

// Execute a workflow with arguments and print the execution results.
//
// For more information about Workflows see:
// https://cloud.google.com/workflows/docs/overview
func executeWorkflowWithArguments(w io.Writer, projectID, workflowID, locationID string) error {
	// TODO(developer): Uncomment and update the following lines:
	// projectID := "YOUR_PROJECT_ID"
	// workflowID := "YOUR_WORKFLOW_ID"
	// locationID := "YOUR_LOCATION_ID"

	ctx := context.Background()

	// Construct the location path.
	parent := fmt.Sprintf("projects/%s/locations/%s/workflows/%s", projectID, locationID, workflowID)

	// Create execution client.
	client, err := workflowexecutions.NewService(ctx)
	if err != nil {
		return fmt.Errorf("workflowexecutions.NewService error: %w", err)
	}

	// Get execution service.
	service := client.Projects.Locations.Workflows.Executions

	// Create argument.
	argument := struct {
		SearchTerm string `json:"searchTerm"`
	}{
		SearchTerm: "Cloud",
	}

	// Encode argument to JSON.
	argumentEncoded, err := json.Marshal(argument)
	if err != nil {
		return fmt.Errorf("json.Marshal error: %w", err)
	}

	// Build and run the new workflow execution adding the argument.
	res, err := service.Create(parent, &workflowexecutions.Execution{
		Argument: string(argumentEncoded),
	}).Do()
	if err != nil {
		return fmt.Errorf("service.Create.Do error: %w", err)
	}
	fmt.Fprintln(w, "- Execution started...")

	// Set initial value for backoff delay in one second.
	backoffDelay := time.Second

	for res.State == "ACTIVE" {
		time.Sleep(backoffDelay)

		// Request the updated state for the execution.
		getReq := service.Get(res.Name)
		res, err = getReq.Do()
		if err != nil {
			return fmt.Errorf("getReq error: %w", err)
		}

		// Double the delay to provide exponential backoff (capped at 16 seconds).
		if backoffDelay < time.Second*16 {
			backoffDelay *= 2
		}
	}

	fmt.Fprintf(w, "Execution finished with state: %s\n", res.State)
	fmt.Fprintf(w, "Execution arguments: %s", res.Argument)
	fmt.Fprintf(w, "Execution results: %s\n", res.Result)

	return nil
}

Java

// Creates the execution object
CreateExecutionRequest request =
    CreateExecutionRequest.newBuilder()
        .setParent(parent.toString())
        .setExecution(Execution.newBuilder().setArgument("{\"searchTerm\":\"Friday\"}").build())
        .build();

Node.js

// Execute workflow
try {
  const createExecutionRes = await client.createExecution({
    parent: client.workflowPath(projectId, location, workflow),
    execution: {
      argument: JSON.stringify({"searchTerm": "Friday"})
    }
});
const executionName = createExecutionRes[0].name;

Python

import time

from google.cloud import workflows_v1
from google.cloud.workflows import executions_v1

from google.cloud.workflows.executions_v1.types import executions

# TODO(developer): Update and uncomment the following lines.
# project_id = "YOUR_PROJECT_ID"
# location = "YOUR_LOCATION"  # For example: us-central1
# workflow_id = "YOUR_WORKFLOW_ID"  # For example: myFirstWorkflow

# Initialize API clients.
execution_client = executions_v1.ExecutionsClient()
workflows_client = workflows_v1.WorkflowsClient()

# Construct the fully qualified location path.
parent = workflows_client.workflow_path(project_id, location, workflow_id)

# Execute the workflow adding an dictionary of arguments.
# Find more information about the Execution object here:
# https://cloud.google.com/python/docs/reference/workflows/latest/google.cloud.workflows.executions_v1.types.Execution
execution = executions_v1.Execution(
    name=parent,
    argument='{"searchTerm": "Cloud"}',
)

response = execution_client.create_execution(
    parent=parent,
    execution=execution,
)
print(f"Created execution: {response.name}")

# Wait for execution to finish, then print results.
execution_finished = False
backoff_delay = 1  # Start wait with delay of 1 second.
print("Poll for result...")

# Keep polling the state until the execution finishes,
# using exponential backoff.
while not execution_finished:
    execution = execution_client.get_execution(
        request={"name": response.name}
    )
    execution_finished = execution.state != executions.Execution.State.ACTIVE

    # If we haven't seen the result yet, keep waiting.
    if not execution_finished:
        print("- Waiting for results...")
        time.sleep(backoff_delay)
        # Double the delay to provide exponential backoff.
        backoff_delay *= 2
    else:
        print(f"Execution finished with state: {execution.state.name}")
        print(f"Execution results: {execution.result}")

如要進一步瞭解如何傳遞執行階段引數,請參閱「在執行要求中傳遞執行階段引數」。

清除所用資源

如要避免系統向您的 Google Cloud 帳戶收取您在本頁面使用資源的費用,請刪除含有這些資源的 Google Cloud 專案。

  1. 刪除您建立的工作流程:

    gcloud workflows delete myFirstWorkflow
    
  2. 系統詢問您是否要繼續時,請輸入 y

工作流程已刪除。

後續步驟