Pipes and Filters Design Pattern: A Practical Approach

When it comes to data processing, one of the common challenges developers face is how to write maintainable and reusable code. The pipes and filters design pattern is a powerful tool that can help you solve this problem by breaking down a complex data processing task into a series of simple, reusable filters that can be combined in different ways to achieve different results.

In this blog post, we will take a look at how to use the pipes and filters pattern to validate incoming data using C#, We will start by defining the basic building blocks of the pattern, then we will implement a simple example that demonstrates how the pattern works in practice.

Building Blocks

The pipes and filters pattern consists of three main components: filters, pipes, and the pipeline.

• A filter is simple piece of code that performs a specific task on the input data and returns the result. In our example, we will have two filters: a validation filter that checks if the input data is valid and a transformation filter that converts the input data to uppercase.
• A pipe is a data structure that connects the output of one filter to the input of another. In our example, we will not use pipes explicitly, but the pipeline will be responsible for connecting the filters together.
• The pipeline is the main component of the pattern that holds all the filters and connects them together. It is responsible for applying the filters to the input data in the correct order and returning the final result.

Implementing the Pipes and Filters Pattern in C#

Now that we have a basic understanding of the components of the pipes and filters pattern, let’s take a look at how we can implement in C#.

First, we will define and interface for filters called IPipeFilter<T> that has a single method called Process that takes in a input of type T and returns output of type T.

interface IPipeFilter<T>
{
    T Process(T input);
}

Next we will create two filters that implement this interface. The first one is DataValidationFilter that checks if the input data is valid and throws an exception if it is not.

class DataValidationFilter : IPipeFilter<string>
{
    public string Process(string input)
    {
        if (string.IsNullOrWhiteSpace(input))
            throw new Exception("Invalid input data");

        return input;
    }
}

The second filter is DataTransformationFilter that converts the input data to uppercase.

class DataTransformationFilter : IPipeFilter<string>
{
    public string Process(string input)
    {
        return input.ToUpper();
    }
}

Finally, we will create a class called DataProcessingPipeline that takes a list of IPipeFilter<T> as a constructor argument, and it applies each filter in the list to the input data in the order they are provided.

class DataProcessingPipeline<T>: IPipeLine<T> {
  private readonly List <IPipeFilter<T>> _filters;

  public DataProcessingPipeline(List <IPipeFilter<T>> filters) {
    _filters = filters;
  }

  public T Process(T input) {
    foreach(var filter in _filters) {
      input = filter.Process(input);
    }
    return input;
  }
}

with the above classes we are ready to implement the pipeline and use it to validate and transform incoming data.

class Program
{
    static void Main(string[] args)
    {
        var pipeline = new DataProcessingPipeline<string>(new List<IPipeFilter<string>>
        {
            new DataValidationFilter(),
            new DataTransformationFilter()
        });

        try
        {
            var processedData = pipeline.Process("valid input data");
            Console.WriteLine(processedData);
        }
        catch (Exception ex)
        {
            Console.WriteLine(ex.Message);
        }
    }
}

In this example, we first create an instance of DataProcessingPipeline<string> with a list of filters that contains DataValidationFilter and DataTransformationFilter, Then we apply the pipeline to the input data “valid input data”, the output of this pipeline will be “VALID INPUT DATA”.

Conclusion

The pipes and filters pattern is a powerful tool for breaking down complex data processing tasks into simple, reusable components. It can help you write maintainable and reusable code that is easy to understand and modify. In this blog post, we have seen how to use the pipes and filters pattern to validate incoming data using C#, but this pattern can be used in many other scenarios as well. I hope this example will give you a good starting point for using this pattern in your own projects.