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Sequentially Resolve Promises Works, Giải quyết tuần tự các lời hứa hoạt động (ok)

https://css-tricks.com/why-using-reduce-to-sequentially-resolve-promises-works/

D:\Tiah\working\MARUNO-21\test.html

<!DOCTYPE html>
<html lang="en">
<head>
  <meta charset="UTF-8">
  <meta name="viewport" content="width=device-width, initial-scale=1.0">
  <title>Document</title>
  <script src="https://cdnjs.cloudflare.com/ajax/libs/dayjs/1.11.7/dayjs.min.js"></script>
</head>
<body>
  <script>
  function methodThatReturnsAPromise(nextID) {
    return new Promise((resolve, reject) => {
      setTimeout(() => {
        console.log(`Resolve! ${dayjs().format('hh:mm:ss')}`);
        resolve();
      }, 1000);
    });
  }
  [1, 2, 3].reduce((accumulatorPromise, nextID) => {
    console.log(`Loop! ${dayjs().format('hh:mm:ss')}`);
    return accumulatorPromise.then(() => {
      return methodThatReturnsAPromise(nextID);
    });
  }, Promise.resolve());
  </script>
</body>
</html>

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Why Using reduce() to Sequentially Resolve Promises Works

Avatar of Alex MacArthurAlex MacArthur arrow-up-righton Oct 17, 2018

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Writing asynchronous JavaScript without using the Promise object is a lot like baking a cake with your eyes closed. It can be done, but it’s gonna be messy and you’ll probably end up burning yourself.

I won’t say it’s necessary, but you get the idea. It’s real nice. Sometimes, though, it needs a little help to solve some unique challenges, like when you’re trying to sequentially resolve a bunch of promises in order, one after the other. A trick like this is handy, for example, when you’re doing some sort of batch processing via AJAX. You want the server to process a bunch of things, but not all at once, so you space the processing out over time.

Ruling out packages that help make this task easier (like Caolan McMahon’s asyncarrow-up-right library), the most commonly suggested solution for sequentially resolving promises is to use Array.prototype.reduce(). You might’ve heard of this onearrow-up-right. Take a collection of things, and reduce them to a single value, like this:

But, when using reduce() for our purposes, the setup looks more like this:

Or, in a more modern format:

This is neat! But for the longest time, I just swallowed this solution and copied that chunk of code into my application because it “worked.” This post is me taking a stab at understanding two things:

  1. Why does this approach even work?

  2. Why can’t we use other Array methods to do the same thing?

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Why does this even work?

Remember, the main purpose of reduce() is to “reduce” a bunch of things into one thing, and it does that by storing up the result in the accumulator as the loop runs. But that accumulator doesn’t have to be numeric. The loop can return whatever it wants (like a promise), and recycle that value through the callback every iteration. Notably, no matter what the accumulator value is, the loop itself never changes its behavior — including its pace of execution. It just keeps rolling through the collection as fast as the thread allows.

This is huge to understand because it probably goes against what you think is happening during this loop (at least, it did for me). When we use it to sequentially resolve promises, the reduce() loop isn’t actually slowing down at all. It’s completely synchronous, doing its normal thing as fast as it can, just like always.

Look at the following snippet and notice how the progress of the loop isn’t hindered at all by the promises returned in the callback.

In our console:

The promises resolve in order as we expect, but the loop itself is quick, steady, and synchronous. After looking at the MDN polyfillarrow-up-right for reduce(), this makes sense. There’s nothing asynchronous about a while() loop triggering the callback() over and over again, which is what’s happening under the hood:

With all that in mind, the real magic occurs in this piece right here:

Each time our callback fires, we return a promise that resolves to another promise. And while reduce() doesn’t wait for any resolution to take place, the advantage it does provide is the ability to pass something back into the same callback after each run, a feature unique to reduce(). As a result, we’re able build a chain of promises that resolve into more promises, making everything nice and sequential:

All of this should also reveal why we can’t just return a single, new promise each iteration. Because the loop runs synchronously, each promise will be fired immediately, instead of waiting for those created before it.

In our console:

Is it possible to wait until all processing is finished before doing something else? Yes. The synchronous nature of reduce() doesn’t mean you can’t throw a party after every item has been completely processed. Look:

Since all we’re returning in our callback is a chained promise, that’s all we get when the loop is finished: a promise. After that, we can handle it however we want, even long after reduce() has run its course.

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Why won’t any other Array methods work?

Remember, under the hood of reduce(), we’re not waiting for our callback to complete before moving onto the next item. It’s completely synchronous. The same goes for all of these other methods:

But reduce() is special.

We found that the reason reduce() works for us is because we’re able to return something right back to our same callback (namely, a promise), which we can then build upon by having it resolve into another promise. With all of these other methods, however, we just can’t pass an argument to our callback that was returned from our callback. Instead, each of those callback arguments are predetermined, making it impossible for us to leverage them for something like sequential promise resolution.

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I hope this helps!

At the very least, I hope this helps shed some light on why reduce() is uniquely qualified to handle promises in this way, and maybe give you a better understanding of how common Array methods operate under the hood. Did I miss something? Get something wrong? Let me know!

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