Shuttle.Core.Pipelines 13.0.0

Shuttle.Core.Pipelines

PM> Install-Package Shuttle.Core.Pipelines

Observable event-based pipelines based broadly on pipes and filters.

Configuration

In order to more easily make use of pipelines an implementation of the IPipelineFactory should be used. The following will register the PipelineFactory implementation:

services.AddPipelineProcessing(builder => {
    builder.AddAssembly(assembly);
});

This will register the IPipelineFactory and, using the builder, add all IPipeline and IPipelineObserver implementations as Transient. The pipeline instances are re-used as they are kept in a pool.

Since pipelines are quite frequently extended by adding observers, the recommended pattern is to make use of an IHostedService implementation that accepts the IPipelineFactory dependency:

public class CustomHostedService : IHostedService
{
    private readonly Type _pipelineType = typeof(InterestingPipeline);

    public CustomHostedService(IPipelineFactory pipelineFactory)
    {
        Guard.AgainstNull(pipelineFactory, nameof(pipelineFactory));

        pipelineFactory.PipelineCreated += PipelineCreated;
    }

    private void PipelineCreated(object sender, PipelineEventArgs e)
    {
        if (e.Pipeline.GetType() != _pipelineType
        {
            return;
        }

        e.Pipeline.RegisterObserver(new SomeObserver());
    }

    public async Task StartAsync(CancellationToken cancellationToken)
    {
        await Task.CompletedTask;
    }

    public async Task StopAsync(CancellationToken cancellationToken)
    {
        _pipelineFactory.PipelineCreated -= OnPipelineCreated;

        await Task.CompletedTask;
    }
}

Typically you would also have a way to register the above CustomHostedService with the IServiceCollection:

public static class ServiceCollectionExtensions
{
    public static IServiceCollection AddCustomPipelineObserver(this IServiceCollection services)
    {
        services.AddHostedService<CustomHostedService>();

        return services;
    }
}

The above is a rather naive example but it should give you an idea of how to extend pipelines using the IPipelineFactory and IHostedService implementations.

Overview

A Pipeline is a variation of the pipes and filters pattern and consists of 1 or more stages that each contain one or more events. When the pipeline is executed each event in each stage is raised in the order that they were registered. One or more observers should be registered to handle the relevant event(s).

Each Pipeline always has its own state that is simply a name/value pair with some convenience methods to get and set/replace values. The State class will use the full type name of the object as a key should none be specified:

var state = new State();
var list = new List<string> {"item-1"};

state.Add(list); // key = System.Collections.Generic.List`1[[System.String...]]
state.Add("my-key", "my-key-value");

Console.WriteLine(state.Get<List<string>>()[0]);
Console.Write(state.Get<string>("my-key"));

The Pipeline class has a RegisterStage method that will return a PipelineStage instance. The PipelineStage instance has a WithEvent method that will return a PipelineStageEvent instance. This allows for a fluent interface to register events for a pipeline:

IPipelineObserver

The IPipelineObserver interface is used to define the observer that will handle the events:

public interface IPipelineObserver<in TPipelineEvent> : IPipelineObserver where TPipelineEvent : IPipelineEvent
{
    void Execute(TPipelineEvent pipelineEvent);
    Task ExecuteAsync(TPipelineEvent pipelineEvent);
}

The interface has two methods that can be implemented. The Execute method is used for synchronous processing whereas the ExecuteAsync method is used for asynchronous processing.

Example

Events should derive from PipelineEvent.

We will use the following events:

public class OnAddCharacterA : PipelineEvent
{
}

public class OnAddCharacter : PipelineEvent
{
	public char Character { get; private set; }

	public OnAddCharacter(char character)
	{
		Character = character;
	}
}

The OnAddCharacterA event represents a very explicit event whereas with the OnAddCharacter event one can specify some data. In this case the character to add.

In order for the pipeline to process the events we will have to define one or more observers to handle the events. We will define only one for this sample but we could very easily add another that will handle one or more of the same, or other, events:

    public class CharacterPipelineObserver : 
        IPipelineObserver<OnAddCharacterA>,
        IPipelineObserver<OnAddCharacter>
    {
        public void Execute(OnAddCharacterA pipelineEvent)
        {
            var state = pipelineEvent.Pipeline.State;
            var value = state.Get<string>("value");

            value = string.Format("{0}-A", value);

            state.Replace("value", value);
        }

        public async Task ExecuteAsync(OnAddCharacterA pipelineEvent)
        {
			Execute(pipelineEvent);

            await Task.CompletedTask;
        }

        public void Execute(OnAddCharacter pipelineEvent)
        {
            var state = pipelineEvent.Pipeline.State;
            var value = state.Get<string>("value");

            value = string.Format("{0}-{1}", value, pipelineEvent.Character);

            state.Replace("value", value);
        }

        public async Task ExecuteAsync(OnAddCharacter pipelineEvent)
        {
            Execute(pipelineEvent);

			await Task.CompletedTask;
        }
    }

Next we will define the pipeline itself:

var pipeline = new Pipeline();

pipeline.RegisterStage("process")
	.WithEvent<OnAddCharacterA>()
	.WithEvent(new OnAddCharacter('Z'));

pipeline.RegisterObserver(new CharacterPipelineObserver());

pipeline.State.Add("value", "start");

if (sync)
{
    pipeline.Execute();
}
else
{
	await pipeline.ExecuteAsync();
}

Console.WriteLine(pipeline.State.Get<string>("value")); // outputs start-A-Z

We can now execute this pipeline with predictable results.

Pipelines afford us the ability to better decouple functionality. This means that we could re-use the same observer in multiple pipelines enabling us to compose functionality at a more granular level.