Execute um fluxo de trabalho através das bibliotecas cliente da Google Cloud

Este início rápido mostra como executar um fluxo de trabalho e ver os resultados da execução através das bibliotecas de cliente da nuvem.

Para mais informações sobre a instalação das bibliotecas de cliente da nuvem e a configuração do seu ambiente de desenvolvimento, consulte a vista geral das bibliotecas de cliente do Workflows.

Pode concluir os seguintes passos através da CLI Google Cloud no seu terminal ou no Cloud Shell.

Antes de começar

As restrições de segurança definidas pela sua organização podem impedir a conclusão dos seguintes passos. Para informações de resolução de problemas, consulte o artigo Desenvolva aplicações num ambiente Google Cloud restrito.

  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. Se estiver a usar um fornecedor de identidade (IdP) externo, primeiro, tem de iniciar sessão na CLI gcloud com a sua identidade federada.

  4. Para inicializar a CLI gcloud, execute o seguinte comando:

    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. Verify 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. Se estiver a usar um fornecedor de identidade (IdP) externo, primeiro, tem de iniciar sessão na CLI gcloud com a sua identidade federada.

  11. Para inicializar a CLI gcloud, execute o seguinte comando:

    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. Verify 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. (Opcional) Para enviar registos para o Cloud Logging, conceda a função roles/logging.logWriter à conta de serviço.

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

    Para saber mais sobre as funções e as autorizações da conta de serviço, consulte o artigo Conceda uma autorização de fluxo de trabalho para aceder a Google Cloud recursos.

  17. Se necessário, transfira e instale a ferramenta de gestão de código-fonte Git.
  18. Implemente um fluxo de trabalho de amostra

    Depois de definir um fluxo de trabalho, implementa-o para o disponibilizar para execução. O passo de implementação também valida se o ficheiro de origem pode ser executado.

    O fluxo de trabalho seguinte envia um pedido a uma API pública e, em seguida, devolve a resposta da API.

    1. Crie um ficheiro de texto com o nome de ficheiro myFirstWorkflow.yaml com o seguinte conteúdo:

      # 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. Depois de criar o fluxo de trabalho, pode implementá-lo, mas não execute o fluxo de trabalho:

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

      Substitua CLOUD_REGION por um local suportado para o fluxo de trabalho. A região predefinida usada nos exemplos de código é us-central1.

    Obtenha o exemplo de código

    Pode clonar o código de exemplo do GitHub.

    1. Clone o repositório da app de exemplo para a sua máquina local:

      C#

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

      Em alternativa, pode transferir o exemplo como um ficheiro ZIP e extraí-lo.

      Ir

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

      Em alternativa, pode transferir o exemplo como um ficheiro ZIP e extraí-lo.

      Java

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

      Em alternativa, pode transferir o exemplo como um ficheiro ZIP e extraí-lo.

      Node.js

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

      Em alternativa, pode transferir o exemplo como um ficheiro ZIP e extraí-lo.

      Python

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

      Em alternativa, pode transferir o exemplo como um ficheiro ZIP e extraí-lo.

    2. Altere para o diretório que contém o código de exemplo do Workflows:

      C#

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

      Ir

      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. Veja o exemplo de código. Cada app de exemplo faz o seguinte:

      1. Configura as bibliotecas de cliente da Google Cloud para workflows.
      2. Executa um fluxo de trabalho.
      3. Sonda a execução do fluxo de trabalho (usando a retirada exponencial) até que a execução termine.
      4. Imprime os resultados da execução.

      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;
          }
      }

      Ir

      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}")

    Execute o exemplo de código

    Pode executar o exemplo de código e executar o seu fluxo de trabalho. A execução de um fluxo de trabalho executa a definição do fluxo de trabalho implementada associada ao fluxo de trabalho.

    1. Para executar o exemplo, instale primeiro as dependências:

      C#

      dotnet restore

      Ir

      go mod download

      Java

      mvn compile

      Node.js

      npm install -D tsx

      Python

      pip3 install -r requirements.txt

    2. Execute o script:

      C#

      GOOGLE_CLOUD_PROJECT=PROJECT_ID LOCATION=CLOUD_REGION WORKFLOW=WORKFLOW_NAME dotnet run

      Ir

      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

      Substitua o seguinte:

      • PROJECT_ID: o nome do seu Google Cloud projeto
      • CLOUD_REGION: a localização do seu fluxo de trabalho (predefinição: us-central1)
      • WORKFLOW_NAME: o nome do fluxo de trabalho (predefinição: myFirstWorkflow)

      O resultado é semelhante ao seguinte:

      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)"]
      

    Transmita dados num pedido de execução

    Consoante a linguagem da biblioteca cliente, também pode transmitir um argumento de tempo de execução num pedido de execução. Por exemplo:

    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;
        }
    }

    Ir

    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}")

    Para mais informações sobre a transmissão de argumentos de tempo de execução, consulte o artigo Transmita argumentos de tempo de execução num pedido de execução.

    Limpar

    Para evitar incorrer em custos na sua Google Cloud conta pelos recursos usados nesta página, elimine o Google Cloud projeto com os recursos.

    1. Elimine o fluxo de trabalho que criou:

      gcloud workflows delete myFirstWorkflow
      
    2. Quando lhe for perguntado se quer continuar, introduza y.

    O fluxo de trabalho é eliminado.

    O que se segue?