Functional Programming

Functional C#: Debugging Method Chains

One of the most common questions I get in regard to the Map and Tee extension methods I presented in my recent Pluralsight course is “That’s great…but how do I debug these chains?” I get it – debugging a lengthy method chain can seem like a monumental task upon first glance but I assure you, it really isn’t all that difficult or even much different from what you’re accustomed to with more traditional, imperative C# code.

I’ve found that when debugging method chains I typically already have a good idea where the problem is. Spoiler: It’s in the code I wrote. That means that I can almost always automatically rule out any chained in framework or other third-party library methods as the source of the problem. It also means that setting a breakpoint within a chained lambda expression or method is often an adequate first step in isolating the problem. This is especially useful when working with pure, deterministic methods because you can then write a test case around the method in question and already have the breakpoint right where you need it.

In some situations though, you want to follow computation through the chain but constantly stepping through the extension methods can be both tedious and distracting, especially when the chained method is outside of your control and won’t be stepped into anyway. Fortunately this is easily resolved with a single attribute.

The System.Diagnostics.DebuggerNonUserCodeAttribute class is intended specifically for this purpose. As MSDN states, this attribute instructs the debugger to step through rather than into the decorated type or member. You can either apply this attribute to individual methods or to the extension class to prevent the methods from disrupting your debugging experience. For my projects I opted to simply suppress all of the extension methods by decorating the class like this:

[DebuggerNonUserCodeAttribute]
public static class FunctionalExtensions
{
    public static TResult Map<TSource, TResult>(
        this TSource @this,
        Func<TSource, TResult> map) => map(@this);

    // -- Snipped --
}

With the attribute applied, you can simply set a breakpoint on the chain and step into it as you normally would. Then, instead of having to walk through each of the extension methods you’ll simply be taken right into the chained methods or lambda expressions.

Enjoy!

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Functional C#: Chaining Async Methods

The response to my new Functional Programming with C# course on Pluralsight has been far better than I ever imagined it would be while I was writing it. Thanks, everyone for your support!

One viewer, John Hoerr, asked an interesting question about how to include async methods within a chain. I have to be honest that I never really thought about it but I can definitely see how it would be useful.

In his hypothetical example John provided the following three async methods:

public async Task<int> F(int x) => await Task.FromResult(x + 1);
public async Task<int> G(int x) => await Task.FromResult(x * 2);
public async Task<int> H(int x) => await Task.FromResult(x + 3);

He wanted to chain these three methods together such that the asynchronous result from one task would be passed as input to the next method. Essentially he wanted the asynchronous version of this:

1
    .Map(H)
    .Map(G)
    .Map(F);

These methods can’t be chained together using the Map method I defined in the course because each of them want an int value rather than Task<int>. One thing John considered was using the ContinueWith method.

1
    .Map(H)
    .ContinueWith(t => G(t.Result))
    .ContinueWith(t => F(t.Result.Result));

This approach does play well with method chaining because each method returns a task that exposes the ContinueWith method but it requires working with the tasks directly to get the result and hand it off to the next method. Also, as we chain more tasks together we have to drill through the results to get to the value we really care about. Instead what we’re looking for is a more generalized approach that can be used across methods and at an arbitrary level within the chain.

After some more discussion we arrived at the following solution:

public static async Task<TResult> MapAsync<TSource, TResult>(
    this Task<TSource> @this,
    Func<TSource, Task<TResult>> fn) => await fn(await @this);

Rather than working with TSource and TResult directly like the Map method does, MapAsync operates against Task<TResult>. This approach allows us to define the method as async, accept the task returned from one async method, and await the call to the delegate. The method name also gives anyone reading the code a good visual indication that it is intended to be used with asynchronous methods.

With MapAsync now defined we can easily include async methods in a chain like this:

await 1
    .Map(H)
    .MapAsync(G)
    .MapAsync(F);

Here we begin with the synchronous Map call because at this point we have an integer rather than a task. The call to H returns a Task so from there we chain in G and F respectively using the new MapAsync method. Because we’re awaiting the whole chain, it’s all wrapped up in a nice continuation automatically for us.

This version of the MapAsync method definitely covers the original question but there are two other permutations that could also be useful.

public static async Task<TResult> MapAsync<TSource, TResult>(
    this TSource @this,
    Func<TSource, Task<TResult>> fn) => await fn(@this);

public static async Task<TResult> MapAsync<TSource, TResult>(
    this Task<TSource> @this,
    Func<TSource, TResult> fn) => fn(await @this);

Both of these overloads awaits results at different points depending on the input or output but they each operate against a Task at some point.

So there you have it, a relatively painless way to include arbitrary async methods within a method chain.

Thanks, John, for your question and your contributions to this post!

Have fun!

Functional C#: Fluent Interfaces and Functional Method Chaining

This is adapted from a talk I’ve been refining a bit. I’m pretty happy with it overall but please let me know what you think in the comments.

Update: I went to correct a minor issue in a code sample and WordPress messed up the code formatting. Even after reverting to the previous version I still found issues with escaped quotes and casing changes on some generic type definitions. I’ve tried to fix the problems but I may have missed a few spots. I apologize for any odd formatting issues.

I’ve been developing software professionally for 15 years or so. Like many of today’s enterprise developers much of my career has been spent with object-oriented languages but when I discovered functional programming a few years ago it changed the way I think about code at the most fundamental levels. As such I no longer think about problems in terms of object hierarchies, encapsulation, or and associated behavior. Instead I think in terms of independent functions and the data upon which they operate in order to produce the desired result. (more…)

Extending F# Pipelines with a Tee Function

In functional programming we strive to minimize side-effects but not only are some side-effects desirable, in the largely object-oriented world in which many of us still operate such side-effects are often unavoidable. There are plenty of APIs that rely on side-effects particularly when it comes to initializing types or properties. One example that immediately comes to mind is building up an HttpResponseMessage in Web API 2. Consider the following snippet which creates a response containing the contents of a stream and sets some relevant header values:

member __.GetFile() =
  // ... SNIP ...
  let response = new HttpResponseMessage(HttpStatusCode.OK, Content = new StreamContent(stream))
  response.Content.Headers.ContentType <- MediaTypeHeaderValue("application/octet-stream")
  response.Content.Headers.ContentLength <- Nullable.op_Implicit stream.Length
  response.Content.Headers.ContentDisposition <- new ContentDispositionHeaderValue("attachment", FileName = "test.pdf")
  response

This code is straight-forward but it’s highly imperative. Like side-effects, imperative code isn’t necessarily a bad thing but it would be nice to tame it a bit by initializing the header values as part of a pipeline while still returning the response message. Doing so isn’t hard: just create the HttpResponseMessage instance via the constructor and pipe it to a function that does the initialization before returning, right?

member __.GetFile() =
  // ... SNIP ...
  new HttpResponseMessage(HttpStatusCode.OK, Content = new StreamContent(stream))
  |> (fun response -> response.Content.Headers.ContentType <- MediaTypeHeaderValue("application/octet-stream")
                      response.Content.Headers.ContentLength <- Nullable.op_Implicit stream.Length
                      response.Content.Headers.ContentDisposition <- new ContentDispositionHeaderValue("attachment", FileName = "test.pdf")
                      response)

This is a perfectly acceptable approach and is something I’ve definitely done plenty of times but all it has achieved is moving the explicit return into the function. After doing this a few times, you might start to think there has to be a way to standardize this pattern and you’d be right.

Over the holidays I finally found some time to relax and although I spent a great deal of time glued to Assassin’s Creed: Unity on my Xbox One I managed to read a few more articles than usual. Something that struck me as interesting was that I noticed a theme across several of the code samples: they were using a tee function within a pipeline. The tee function isn’t part of the core F# libraries and I couldn’t recall having encountered it before so I started doing some background investigation.

One of the first sites I found that mentioned the function in the context of F# was Scott Wlaschin’s excellent Railway Oriented Programming article which I’d read previously but clearly not thoroughly enough. In the article Scott says he named the function after a Unix command of the same name. The Unix command, which is named after plumbing tee fittings, splits a pipeline such that input flows to both standard output and a file. This is certainly useful for logging in shell scripts but its possibilities are much more interesting in an F# pipeline.

The tee function is a simple function which essentially says “given a value, apply a function to it, ignore the result, then return the original value.” It’s basic definition is as follows:

let inline tee fn x = x |> fn |> ignore; x

By introducing the tee function into the pipelined version of the GetFile method we can remove the explicit return:

member __.GetFile() =
  // ... SNIP ...
  new HttpResponseMessage(HttpStatusCode.OK, Content = new StreamContent(stream))
  |> tee (fun response -> response.Content.Headers.ContentType <- MediaTypeHeaderValue("application/octet-stream")
                          response.Content.Headers.ContentLength <- Nullable.op_Implicit stream.Length
                          response.Content.Headers.ContentDisposition <- new ContentDispositionHeaderValue("attachment", FileName = "test.pdf"))

Now the pipeline looks more like what we might expect since we’re no longer explicitly returning the response from the lambda expression.

Depending on your style preferences, injecting the tee function explicitly into the pipeline as you would a Seq.filter or other such function might bother you. To me, the tee function is a perfect candidate for a custom operator so let’s define one.

let inline ( |>! ) x fn = tee fn x

Here we’ve defined |>! as the tee operator (this is the same symbol that WebSharper uses). Notice how the parameter order is reversed from the tee function. This is due to the fact that when using our new operator, we’re not relying on partial application to invoke the tee function. Now we can eliminate the explicit reference to the function, making the operation look like a natural part of the F# language.

member __.GetFile() =
  // ... SNIP ...
  new HttpResponseMessage(HttpStatusCode.OK, Content = new StreamContent(stream))
  |>! (fun response -> response.Content.Headers.ContentType <- MediaTypeHeaderValue("application/octet-stream")
                       response.Content.Headers.ContentLength <- Nullable.op_Implicit stream.Length
                       response.Content.Headers.ContentDisposition <- new ContentDispositionHeaderValue("attachment", FileName = "test.pdf"))

Since the tee function/operator is intended to allow side-effects within a pipeline it is ideal for adding logging or other diagnostics into a pipeline (as was the intent in the original Unix command). For instance, to write out a message as each header value is set, we can simply split the tee’d function above into separate functions, inserting a tee’d logging function in between:

member __.GetFile() =
  // ... SNIP ...
  new HttpResponseMessage(HttpStatusCode.OK, Content = new StreamContent(stream))
  |>! (fun _ -> Debug.WriteLine "Created response")
  |>! (fun r -> r.Content.Headers.ContentType <- MediaTypeHeaderValue("application/octet-stream"))
  |>! (fun r -> Debug.WriteLine("Set content type: {0}",
                                [| box r.Content.Headers.ContentType.MediaType |]))
  |>! (fun r -> r.Content.Headers.ContentLength <- Nullable.op_Implicit stream.Length)
  |>! (fun r -> Debug.WriteLine("Set content length: {0}",
                                [| box r.Content.Headers.ContentLength.Value |]))
  |>! (fun r -> r.Content.Headers.ContentDisposition <- new ContentDispositionHeaderValue("attachment", FileName = "test.txt"))
  |>! (fun r -> Debug.WriteLine("Set content disposition: {0}",
                                [| box r.Content.Headers.ContentDisposition.DispositionType |]))

By introducing the tee function and operator you give yourself another tool for taming the imperative code and side-effects that tend to pop up in software projects of any complexity.