Why use the yield keyword, when I could just use an ordinary IEnumerable?

Answer 1

The benefit of iterator blocks is that they work lazily. So you can write a filtering method like this:

public static IEnumerable<T> Where<T>(this IEnumerable<T> source,
                                   Func<T, bool> predicate)
{
    foreach (var item in source)
    {
        if (predicate(item))
        {
            yield return item;
        }
    }
}

That will allow you to filter a stream as long as you like, never buffering more than a single item at a time. If you only need the first value from the returned sequence, for example, why would you want to copy everything into a new list?

As another example, you can easily create an infinite stream using iterator blocks. For example, here's a sequence of random numbers:

public static IEnumerable<int> RandomSequence(int minInclusive, int maxExclusive)
{
    Random rng = new Random();
    while (true)
    {
        yield return rng.Next(minInclusive, maxExclusive);
    }
}

How would you store an infinite sequence in a list?

My Edulinq blog series gives a sample implementation of LINQ to Objects which makes heavy use of iterator blocks. LINQ is fundamentally lazy where it can be - and putting things in a list simply doesn't work that way.

Answer 2

object jamesItem = null;
foreach(var item in FilteredList())
{
   if (item.Name == "James")
   {
       jamesItem = item;
       break;
   }
}
return jamesItem;

When the above code is used to loop through FilteredList() and assuming item.Name == "James" will be satisfied on 2nd item in the list, the method using yield will yield twice. This is a lazy behavior.

Where as the method using list will add all the n objects to the list and pass the complete list to the calling method.

This is exactly a use case where difference between IEnumerable and IList can be highlighted.

Answer 3

The best real world example I've seen for the use of yield would be to calculate a Fibonacci sequence.

Consider the following code:

class Program
{
    static void Main(string[] args)
    {
        Console.WriteLine(string.Join(", ", Fibonacci().Take(10)));
        Console.WriteLine(string.Join(", ", Fibonacci().Skip(15).Take(1)));
        Console.WriteLine(string.Join(", ", Fibonacci().Skip(10).Take(5)));
        Console.WriteLine(string.Join(", ", Fibonacci().Skip(100).Take(1)));
        Console.ReadKey();
    }

    private static IEnumerable<long> Fibonacci()
    {
        long a = 0;
        long b = 1;

        while (true)
        {
            long temp = a;
            a = b;

            yield return a;

            b = temp + b;
        }
    }
}

This will return:

1, 1, 2, 3, 5, 8, 13, 21, 34, 55
987
89, 144, 233, 377, 610
1298777728820984005

This is nice because it allows you to calculate out an infinite series quickly and easily, giving you the ability to use the Linq extensions and query only what you need.

Answer 4

You can use yield to return items that aren't in a list. Here's a little sample that could iterate infinitely through a list until canceled.

public IEnumerable<int> GetNextNumber()
{
    while (true)
    {
        for (int i = 0; i < 10; i++)
        {
            yield return i;
        }
    }
}

public bool Canceled { get; set; }

public void StartCounting()
{
    foreach (var number in GetNextNumber())
    {
        if (this.Canceled) break;
        Console.WriteLine(number);
    }
}

This writes

0
1
2
3
4
5
6
7
8
9
0
1
2
3
4

...etc. to the console until canceled.

Answer 5

With the "list" code, you have to process the full list before you can pass it on to the next step. The "yield" version passes the processed item immediately to the next step. If that "next step" contains a ".Take(10)" then the "yield" version will only process the first 10 items and forget about the rest. The "list" code would have processed everything.

This means that you see the most difference when you need to do a lot of processing and/or have long lists of items to process.

Answer 6

The yield return statement allows you to return only one item at a time. You are collecting all the items in a list and again returning that list, which is a memory overhead.