使用 Cloud 客户端库执行工作流

本快速入门介绍如何使用 Cloud 客户端库执行工作流并查看执行结果。

如需详细了解如何安装 Cloud 客户端库和设置开发环境，请参阅 Workflows 客户端库概览。

您可以在终端或 Cloud Shell 中使用 Google Cloud CLI 完成以下步骤。

准备工作

您的组织定义的安全限制条件可能会导致您无法完成以下步骤。如需了解相关问题排查信息，请参阅在受限的 Google Cloud 环境中开发应用。

登录您的 Google Cloud 账号。如果您是 Google Cloud新手，请创建一个账号来评估我们的产品在实际场景中的表现。新客户还可获享 $300 赠金，用于运行、测试和部署工作负载。

安装 Google Cloud CLI。

如果您使用的是外部身份提供方 (IdP)，则必须先使用联合身份登录 gcloud CLI。

如需初始化 gcloud CLI，请运行以下命令：

gcloud init

创建或选择 Google Cloud 项目。

选择或创建项目所需的角色

选择项目：选择项目不需要特定的 IAM 角色，您可以选择已获授角色的任何项目。
创建项目：如需创建项目，您需要拥有 Project Creator 角色 (roles/resourcemanager.projectCreator)，该角色包含 resourcemanager.projects.create 权限。了解如何授予角色。

创建 Google Cloud 项目：
```
gcloud projects create PROJECT_ID
```
将 PROJECT_ID 替换为您要创建的 Google Cloud 项目的名称。
选择您创建的 Google Cloud 项目：
```
gcloud config set project PROJECT_ID
```
将 PROJECT_ID 替换为您的 Google Cloud 项目名称。

如果您要使用现有项目来完成本指南，请验证您是否拥有完成本指南所需的权限。如果您创建了新项目，则您已拥有所需的权限。

验证是否已为您的 Google Cloud 项目启用结算功能。

启用 Workflows API：

启用 API 所需的角色

如需启用 API，您需要拥有 Service Usage Admin IAM 角色 (roles/serviceusage.serviceUsageAdmin)，该角色包含 serviceusage.services.enable 权限。了解如何授予角色。

gcloud services enable workflows.googleapis.com

安装 Google Cloud CLI。

如果您使用的是外部身份提供方 (IdP)，则必须先使用联合身份登录 gcloud CLI。

如需初始化 gcloud CLI，请运行以下命令：

gcloud init

创建或选择 Google Cloud 项目。

选择或创建项目所需的角色

选择项目：选择项目不需要特定的 IAM 角色，您可以选择已获授角色的任何项目。
创建项目：如需创建项目，您需要拥有 Project Creator 角色 (roles/resourcemanager.projectCreator)，该角色包含 resourcemanager.projects.create 权限。了解如何授予角色。

创建 Google Cloud 项目：
```
gcloud projects create PROJECT_ID
```
将 PROJECT_ID 替换为您要创建的 Google Cloud 项目的名称。
选择您创建的 Google Cloud 项目：
```
gcloud config set project PROJECT_ID
```
将 PROJECT_ID 替换为您的 Google Cloud 项目名称。

如果您要使用现有项目来完成本指南，请验证您是否拥有完成本指南所需的权限。如果您创建了新项目，则您已拥有所需的权限。

验证是否已为您的 Google Cloud 项目启用结算功能。

启用 Workflows API：

启用 API 所需的角色

如需启用 API，您需要拥有 Service Usage Admin IAM 角色 (roles/serviceusage.serviceUsageAdmin)，该角色包含 serviceusage.services.enable 权限。了解如何授予角色。

gcloud services enable workflows.googleapis.com

设置身份验证：
1. 确保您拥有 Create Service Accounts IAM 角色 (roles/iam.serviceAccountCreator) 和 Project IAM Admin 角色 (roles/resourcemanager.projectIamAdmin)。了解如何授予角色。
2. 创建服务账号：
```
gcloud iam service-accounts create SERVICE_ACCOUNT_NAME
```
  将 SERVICE_ACCOUNT_NAME 替换为服务账号的名称。
3. 向服务账号授予 roles/logging.logWriter IAM 角色：
```
gcloud projects add-iam-policy-binding PROJECT_ID --member="serviceAccount:SERVICE_ACCOUNT_NAME@PROJECT_ID.iam.gserviceaccount.com" --role=roles/logging.logWriter
```
  请替换以下内容：
  - SERVICE_ACCOUNT_NAME：服务账号的名称
  - PROJECT_ID：您在其中创建服务账号的项目的 ID
  注意：--role 标志会影响服务账号可以访问项目中的哪些资源。您可以撤消这些角色或稍后授予其他角色。

如需详细了解服务账号角色和权限，请参阅授予工作流访问Google Cloud 资源的权限。

如果需要，请下载并安装 Git 源代码管理工具。

所需的角色

如需获得完成本快速入门所需的权限，请让您的管理员为您授予项目的以下 IAM 角色：

Service Account User (roles/iam.serviceAccountUser)
Workflows Admin (roles/workflows.admin)

如需详细了解如何授予角色，请参阅管理对项目、文件夹和组织的访问权限。

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。

部署示例工作流

定义工作流后，可以进行部署，使其可以执行。部署步骤还会验证源文件是否可以执行。

以下工作流会向公共 API 发送请求，然后返回该 API 的响应。

创建一个文件名为 myFirstWorkflow.yaml 且包含以下内容的文本文件：

# 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]}'

创建工作流后，您可以对其进行部署，但不要执行工作流：

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

将 CLOUD_REGION 替换为工作流的受支持位置。代码示例中使用的默认区域为 us-central1。

获取示例代码

您可以从 GitHub 克隆示例代码。

将示例应用代码库克隆到本地机器：
C#
```
git clone https://github.com/GoogleCloudPlatform/dotnet-docs-samples.git
```
或者，您也可以下载该示例的 zip 文件并将其解压缩。
Go
```
git clone https://github.com/GoogleCloudPlatform/golang-samples.git
```
或者，您也可以下载该示例的 zip 文件并将其解压缩。
Java
```
git clone https://github.com/GoogleCloudPlatform/java-docs-samples.git
```
或者，您也可以下载该示例的 zip 文件并将其解压缩。
Node.js
```
git clone https://github.com/GoogleCloudPlatform/nodejs-docs-samples.git
```
或者，您也可以下载该示例的 zip 文件并将其解压缩。
Python
```
git clone https://github.com/GoogleCloudPlatform/python-docs-samples.git
```
或者，您也可以下载该示例的 zip 文件并将其解压缩。

切换到包含工作流示例代码的目录：

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/

查看示例代码。每个示例应用都会执行以下操作：

为工作流设置 Cloud 客户端库。
执行工作流。
轮询工作流的执行（使用指数退避算法），直到执行终止为止。
打印执行结果。

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}")

运行示例代码

您可以运行示例代码并执行工作流。执行某个工作流会运行与该工作流关联的已部署工作流定义。

要运行示例，请先安装依赖项：

C#

dotnet restore

Go

go mod download

Java

mvn compile

Node.js

npm install -D tsx

Python

pip3 install -r requirements.txt

运行脚本：

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

替换以下内容：

PROJECT_ID：您的 Google Cloud 项目名称
CLOUD_REGION：工作流的位置（默认值：us-central1）
WORKFLOW_NAME：工作流名称（默认值：myFirstWorkflow）

输出类似于以下内容：

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)"]

在执行请求中传递数据

根据客户端库语言，您还可以在执行请求中传递运行时实参。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}")

如需详细了解如何传递运行时实参，请参阅在执行请求中传递运行时实参。

清理

为避免因本页面中使用的资源导致您的 Google Cloud 账号产生费用，请删除包含这些资源的 Google Cloud 项目。

删除您创建的工作流：

gcloud workflows delete myFirstWorkflow

当系统询问您是否要继续时，请输入 y。

工作流已删除。

使用 Cloud 客户端库执行工作流

准备工作

所需的角色

部署示例工作流

获取示例代码

C#

Go

Java

Node.js

Python

C#

Go

Java

Node.js

Python

C#

Go

Java

Node.js

Python

运行示例代码

C#

Go

Java

Node.js

Python

C#

Go

Java

Node.js

Python

在执行请求中传递数据

C#

Go

Java

Node.js

Python

清理

后续步骤