This is Understanding Combine, written by Matt Neuburg. It is a work in progress. Corrections and suggestions are greatly appreciated (you can comment here). So are donations; please consider keeping me going by funding this work at Or buy my books: the current editions are iOS 13 Programming Fundamentals with Swift and Programming iOS 13. Thank you!


.scan (Publishers.Scan) is like .map, in that it takes a map function that receives a value from upstream and returns a value that will be sent on downstream in place of the upstream value. However, this map function, unlike the .map operator’s map function, takes two parameters: it receives the value emitted by the upstream publisher, but it also receives the value that the function itself produced previously. The first time scan is called, there is obviously no previously produced value, so you have to supply that as the first parameter.

For example, recall that a Timer publisher publishes the current date–time. Suppose that instead what we’re interested in is a count of how many times the Timer has fired. We can do that with .scan:

Timer.publish(every: 1, on: .main, in: .common)
    .scan(0) { count, date in count + 1 }

That causes 1, 2, 3 and so on to be produced at 1-second intervals.

In that example, we’re ignoring the incoming value completely. Sometimes, however, what you want is to pass along the incoming value (possibly transformed in some way) along with a secondary piece of information injected by the scan. The usual technique is to produce a tuple:

Timer.publish(every: 1, on: .main, in: .common)
    .scan((count:0, date:Date.distantPast)) {
        tuple, date in (count:tuple.count + 1, date:date)

That produces tuples pairing the count of times the Timer has fired with the Date when the Timer last fired:

(count: 1, date: 2020-03-02 15:39:50 +0000)
(count: 2, date: 2020-03-02 15:39:51 +0000)
(count: 3, date: 2020-03-02 15:39:52 +0000)

The downstream can then extract and manipulate that information as desired.

A particularly common thing to do is to make a tuple consisting of the current and previous values, allowing the downstream to draw from these whatever conclusions it likes. I gave an example earlier:

Timer.publish(every: 1, on: .main, in: .default)
    .scan((prev:Date.distantPast, now:Date())) { (prev:$, now:$1) }
    .map { $$0.prev) }

In that code, the scan operator pairs the current and previous values, and the subsequent map operator extracts the time difference between them; so what arrives at the end of that pipeline is the interval since the previous firing of the Timer.

In situations where you can’t coherently provide an initial value for the scan first parameter, you can use an Optional and provide nil. For example, in the preceding code, the first interval reported is with respect to now — Date() — at the time the pipeline starts operating, and I use a fake value, Date.distantPast, as the initial previous value. Instead of that, we might like the first value to report that there is no previous value, leaving the downstream to draw its own conclusions:

Timer.publish(every: 1, on: .main, in: .default)
    .scan((prev:Optional<Date>.none, now:Optional<Date>.none)) {
        (prev:$, now:$1)
    .map { (prev:$0.prev, now:$!)}

In that code we follow .scan with a .map that force-unwraps the .now value, which is known always to exist by the time we get here. Thus what emerges from the pipeline is a tuple consisting of prev, which is an Optional Date reporting the previous occasion when the Timer fired, but might be nil to indicate that this is the first time, along with now, which is a Date reporting when the Timer fired on this occasion. (I owe that idea to Rob Mayoff).

In addition to .scan, there is also .tryScan (Publishers.TryScan); it works similarly to .tryMap, so I won’t say more about it.

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