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!

Append and Prepend

.append (Publishers.Concatenate) takes a publisher as a parameter; it is also applied to a publisher (obviously). Both publishers must have the same Output and Failure generic types. It produces all the values from the publisher it is applied to, as they arrive, followed by the values from the publisher that is its parameter, as they arrive.

To enforce the policy of making these values arrive sequentially, this operator doesn’t subscribe to the second publisher until it receives the first publisher’s .finished completion. (Conversely, if it never receives .finished completion from the first publisher, it just keeps publishing the first publisher’s values and never subscribes to the second publisher.)

If the second publisher sends a .finished completion, this operator sends a .finished completion. If either publisher emits a failure, this publisher cancels the other publisher and passes the failure on downstream.

WARNING: The documentation’s description of how .append behaves is completely wrong.

A toy example with some artificial timing will demonstrate:

[1,2,3].publisher.flatMap(maxPublishers: .max(1)) {
    Just($0).delay(for: 1, scheduler: DispatchQueue.main)

That produces this output:

[one second]
[one second]
[one second]

.append also comes in two convenience forms. The parameter, instead of being a publisher, can be a sequence of values or simply a variadic (a comma-separated list of values). So in this example it would be legal to write .append([10,20,30]) or even .append(10,20,30).

.prepend (Publishers.Concatenate) is exactly like .append — indeed, it is the very same operator under the hood — except that the meanings of the publishers are reversed. It starts out by subscribing to and publishing the values from the publisher that is its parameter; when that finishes, it subscribes to and publishes the values from the publisher to which it is applied.

This produces the same output, with the same timing, as the previous example:

Just(100).prepend (
    [1,2,3].publisher.flatMap(maxPublishers: .max(1)) {
        Just($0).delay(for: 1, scheduler: DispatchQueue.main)

You can readily see that .append (and, for that matter, .prepend) is a way to serialize asynchronicity, because the second publisher can’t even get started until the first publisher has finished. This is a lot simpler than the ways of serializing asynchronicity that I described earlier in connection with .flatMap. But, of course, there’s a price to pay for that simplicity: with .flatMap, you can flow each value produced by the first asynchronous operation into the second asynchronous operation, but with .append, all the values just flow out the bottom of the pipeline independently. What you are serializing here are not individual values, but entire streams from each publisher in turn.

Sometimes, however, that is exactly what you want; and if you have several publishers whose output streams you want to serialize, you can chain .append calls to construct the serialized publisher you’re after. It will be useful to have a utility method that lets you do that:

extension Collection where Element: Publisher {
    func serialize() -> AnyPublisher<Element.Output, Element.Failure>? {
        guard let start = self.first else { return nil }
        return self.dropFirst().reduce(start.eraseToAnyPublisher()) {

So now all you have to do is construct an array of publishers and serialize it. For example:

let arr = [
    .map {URLSession.shared.dataTaskPublisher(for:$0)

If we now call arr.serialize()!, we get a publisher that produces the output of each data task publisher in order. Note that if one of the publishers produces a failure, the entire pipeline fails immediately; again, that’s the price we pay for simplicity.

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