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JavaScript patterns - Pyramid of doom

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In this post, I will introduce you to the concept of the pyramid of doom. Although the pattern is not typical anymore, it is good to know how you might solve this anti-pattern, as there are several ways to approach it. The pyramid of doom could be characterized as the JavaScript version of div soup familiar from HTML, where you have plenty of nesting obscuring meaning.

I wrote my first book about JavaScript a decade ago, and it was called “Survive JavaScript - a Web Developer’s Guide”. The content is still available at GitHub. While the book is severely outdated, there are still some good bits I thought might be nice to revisit and expand.

Definition - Pyramid of doom
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In the example below, I have illustrated what the pyramid of doom looks like using the original Node.js API callback style, where the first parameter captures a potential error. In contrast, the second parameter captures a possible value:

import db from "./db";

db.set("key1", "value1", (err) => {
  if(err) {
    throw err;
  }

  db.set("key2", "value2", (err) => {
    if(err) {
      throw err;
    }

    db.set("key3", "value3", (err) => {
      if(err) {
        throw err;
      }

      db.get("key1", (err, value) => {
        if(err) {
          throw err;
        }

        console.log(value + 'bar');
      });
    });
  });
});

The name pyramid of doom derives directly from the shape of the code that resembles a pyramid in terms of nesting. Nesting is not good for code readability, making it more difficult to follow the logic.

If you came to the ecosystem late enough, you likely have never seen this convention. The convention vanished for a good reason, as we now have better ways to solve the problem of asynchronous chaining.

First solution - Promises
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The pyramid of doom was initially solved by the introduction of Promises that allows wrapping asynchronous functionality behind a clean interface that resolves in a value eventually. The solution also provides error handling through its catch method. The example below uses promises to rewrite the example above in a more concise form:

import db from "./db";

db.set("key1", "value1")
  .then(() => db.set("key2", "value2"))
  .then(() => db.set("key3", "value3"))
  .then(() => db.get("key1"))
  .then(value => console.log(value + 'bar'));

As you can see, it has far less code than the original example and shows the power of promises well.

Second solution - async / await
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To improve on promises further, a feature called asynchronous functions was standardized. You could argue the new syntax has its faults due to partly magical behavior (as in, it’s not always obvious what is happening under the hood), but still it allows us to simplify the example further:

import db from "./db";

async function main() {
  await db.set("key1", "value1");
  await db.set("key2", "value2");
  await db.set("key3", "value3");

  return (await db.get("key1")) + 'bar';
}

main();

We have slightly more code here than in the promise case, but the flow is clear to read, at least. Essentially, it is still the same code but with syntax sugar on top. The important thing to keep in mind is that using that async keyword promisifies the result of your function.

In this case, I wrapped the functionality within a function as not all popular environments support top-level async/await yet. This wrapping can be avoided in some runtimes, such as Deno.

Third solution - Promise.all
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The problem with the earlier solutions is that they are blocking execution while setting data. It may be potentially faster to run the operations simultaneously and Promise.all method allows that as below:

import db from "./db";

async function main() {
  await Promise.all([
    db.set("key1", "value1"),
    db.set("key2", "value2"),
    db.set("key3", "value3")]
  );

  return (await db.get("key1")) + 'bar';
}

main();

Technically speaking, the solution is not exactly the same, given that Promise.all can throw an exception if any of the operations fail, meaning that depending on the order of execution, some operations might go through or not. In the earlier solutions, the order is guaranteed, and depending on the use case, this may be an acceptable tradeoff.

An excellent way to solve this problem might be to wrap the operations within a transaction that allows the operations to be undone should any fail. The exact implementation method depends on the underlying API, and in this case, we could assume the database driver supports transactions directly.

!
As pointed out by Joe Shelby, Promise.allSettled may often be a preferable solution over Promise.all as it allows you to deal with possible Promise rejections individually. In case any of the promises passed to Promise.all fails, execution completes on the first rejection. The problem with this is that in user interface facing code your logic might get easily out of sync with the backend due to the abstract nature of Promise.all rejection. In other words, use Promise.allSettled for more control over errors.

Error handling
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The main drawback of all the examples is that they need more error handling. It is easy to write await/async style code while forgetting to handle exceptions. It is good to remember that await works with Promises internally, meaning you can use the standard catch method with it (i.e., await db.get("key1").catch(...)). The same applies to Promise.all. You can also use the standard try/catch structure with these primitives and construct the type of error handling you prefer. The question is, what kind of errors do you want to handle and how.

Conclusion
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Our solutions went quite far from the pyramid of doom and ended up with somewhat flat solutions that are easy to interpret. Adding error handling would complicate them, but it is important to consider which error handling approach to take in production-level code to avoid leaking errors to the user. For a rough developer tool, leaking errors might be acceptable and even expected, but for anything client-facing, a good strategy should be decided.

The list of solutions here is not exhaustive, as you could try using a different programming model entirely. Reactive programming using a library, such as RxJS, would be an interesting direction. It provides an event bus, and you can decouple your events from their handling without having to introduce a library to your codebase.

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