Do. Or do not. There is no try. Well actually, there is.

One of the great things about being a programmer is that you never stop learning. Even after having programmed for almost 35 years, I still improve on the way I write code. About a year ago, the way I write code changed once again when I started to apply monads and especially the Try class.


Do. Or do not. There is no try.

A port from Scala

During a recent Java project, one of the guys on my team created a small library that ports the behavior of the Scala Try classes (including Success and Failure). The Try class basically allows you to invoke a function that is passed as a parameter, and wrap either the result in an instance of the Success class, or in the case and exception occurs, wrap this exception in an instance of the Failure class. These can then be used to invoke a next function on the result of the previous invocation. Thus, Try allows for chaining methods without any exception being thrown, resulting in highly compact and robust code.

Although at first this new monad didn’t appeal to me, I soon really started to appreciate this style of programming, where we concatenate series of Map() and FlatMap() methods, using the power of the Try monad, and thus avoiding abundant try-catch blocks, many if-statements and null checks. Hence, I decided to port this library to C#.

Try and succeed

When programming using the Try classes, you can actually avoid most try-catch blocks in code, because the monad Try will wrap possible exceptions, and just return whether the actions and functions you’ve called fail or succeed.

In the (simple) code example below an instance of the class Employee is created, the name of the employee is fetched in the Map() statement where e is really the instance of Employee that was created above, and we check whether it ends with the character s. This will return a Try<bool>, and we use the property Value to get the actual value from the Try.

    var result = Try<Employee>.Invoke(() => repo.Create("Kees"))
        .Map(e => e.Name)
        .Map(s => s.EndsWith("s"))
        .Value;

    Assert.IsTrue(result);

Every time either an Invoke(), Map() or Flatmap() method is executed, the function that is passed as a lambda expression is invoked within a try-catch block. If no exceptions are thrown, these methods return a new instance of the Success class, with the result from the invocation inside it. If an exception is thrown, it will be wrapped in a new instance of the Failure class. As both of these inherit from the Try class, we can concatenate another round of Map() or Flatmap() methods again and again.

Getting the Value property in the end will only return a valid value IF all of the statements above have executed successfully – that is, if we have an instance of the Success class in the end. If not, we have an instance of Failure on our hands and getting the value will throw an exception.

Try and fail

In the next example, some more of the power of Try is exposed. Here one of the statements fails (deliberately).

    var result = Try<Employee>.Invoke(() => repo.Create("Kees"))
        .Map(e => e.WillThrowException());

    Assert.IsTrue(result.IsFailure);

Now, the first Invoke() call returns an employee, but the second statement Map() throws an exception. But instead of crashing your code, the result will be an instance of the Failure class, holding the exception that was thrown. If one of the statements in your code returns an instance of Failure all following statements are being ignored.

Although this example seems trivial, once you get used to programming with Try you will soon realize that it is actually quite powerful in building more robust code, that also becomes much easier to test too.

Recovering from failure

The next thing you might want to do is to recover from failure and continue. To this aim there are the Recover() methods.

    var result = Try<Employee>.Invoke(() => repo.Create("Kees"))
        .FlatMap(e => e.WillThrowException())
        .Recover(ex => repo.Create("Jaap"));

    Assert.IsTrue(result.IsSuccess);
    Assert.AreEqual(result.Value.Name, "Jaap");

In this code example the second statement throws and will return an instance of Failure. What the Recover() method in the next statement will do is help you get back on track. It will create a new employee (with the name Jaap) and allow you to continue.

Quite often, recover statements appear at the end of a block of statements, for instance to recover from REST calls that do not return anything useful.

In case your code can throw several different exceptions and you want to recover in different ways, the Try class offers some additional features as shown in the example below.

    var result = Try<Employee>.Invoke(() => repo.Create("Kees"))
        .FlatMap(e => e.WillThrowTryException())
        .Recover<TryException>(e => repo.Create("Jaap"))
        .Recover(ex => repo.Create("Jan"));

    Assert.IsTrue(result.IsSuccess);
    Assert.AreEqual(result.Get().Name, "Jaap");

Here, the generic Recover<T> method only fires when this specific type of exception is thrown in one of the invoked methods.

What if?

Next to avoiding try-catch blocks in your code, and making the code robust, the Try monad also allows you to avoid many if-statements (the next big thing to avoid after goto-blocks). It allows you to define filters on the results of previous calls to Invoke(), Map() or Flatmap() methods, as in the example below.

    var result = Try<Employee>.Invoke(() => repo.Create("Kees"))
        .Filter(e => e.IsNameKees().Value);

    Assert.IsTrue(result.IsSuccess);

Starting with return

All in all, after having used the Try monad in many different situations, and in different programming languages, my preferred style of coding has totally changed. These days almost all of the methods I write immediately start with a return statements, followed by a concatenations of Map() and Flatmap() calls – along with a number of other useful features on the Try classes. As a result the code I write is smaller and much more compact, much better in adhering to the Single Responsibility Principle. And my code much more robust – as it also catches any exception you might have overlooked when writing more traditional code.

In the meantime, I have contaminated many programmers with this style. At one of my clients the developers actually make it a sport to always start every method with e return statement. Don’t hesitate to join in.

You can find my Try repository in my GitHub account at github.com/aahoogendoorn/Monads.