Bye Bye Javascript Promises!

Feb 11, 2014   #Promise  #Asynchronous  #CSP  #Sweet.js 

In my previous post, I explored how programming with promises can be made close to programming with values. After some more work on it, and some learning from bluebird, I came to conclude that my brain doesn’t think well with promises. So I wrote a macro for Javascript that expands “tasks” into async state machines that communicate using channels (i.e. CSP). I want to talk about the specific options for error management implemented in the task macro.


My problem: I have async JS code on the server side and the client written using callbacks, getting quite out of hand and I want to strap on some gear to be able to run faster without getting blisters.

  1. I want my async code to be resilient to exceptions that may be thrown from other libraries I may use … without me having to think about them all the time.

  2. I want the flow of async logic to be clear in the code. I do not want syntax like ‘.then’ distracting me and meddling with context (i.e. this). I want to be able to see the process.

  3. I want to control the flow of data in my code instead of having the flow of data control when some code gets run.

  4. I want to be able to think about error management up front and not leave it to, literally, the end of functions I write.

  5. I want good performance with all this.

The bluebird promises library is the best in the category and it solves problems (1) and (5). Regarding (2), I find promises can’t seem to make up their minds about whether they want to stand for values or the processes that produce them. While then and catch seem to indicate they are about processes, promises pretend to be values that have been promised in the future. If you think of them as values, you can’t do that everywhere (ex: in the ?: operator, for loops, etc.)


When I asked myself “what would I do if JS was really a scheme?“. The answer was clear - I’d just write a macro to produce a state machine given async code and get on with life. After all, ClojureScript supports core.async, which is pretty much does this.

I present to you cspjs, a compiler that transforms async “tasks” to state machines that can be run in ES5 as well - i.e. in any browser.

That was easy! .. thanks to Mozilla’s sweet.js.

sweet.js is a neat implementation of hygeinic macros for Javascript. So all I did was to treat ; as a sequencing operator and write a macro (called task) that (in effect) reprogrammed the semicolon to produce an async state machine instead of sync code.

Thank you sweet folks!


cspjs takes the “Communicating Sequential Processes” view to organizing concurrent activities. For better or worse, my brain thinks well with this model and not so well with promises.

The core interface is a task macro that expands to an asynchronous state machine that can work with and call NodeJS style callbacks of the form function (err, result) { ... }. A supporting class called Channel provides communication between these state machines.

The body of the task macro is more or less normal Javascript, except for some special constructs that clarify steps that call out to other party async APIs, and to work with channels.

All that is straightforward. What I want to talk about in this post is a change to the error management mechanism that task introduces. Before that, below is the example madeup-parallel ported from the bluebird benchmark suite, just to show what task code looks like.

task upload(stream, idOrPath, tag) {
    var queries = new Array(global.parallelQueries),
        tx = db.begin();

    catch (e) {

    var ch = new Channel();

    for (var i = 0, len = queries.length; i < len; ++i) {
        FileVersion.insert({index: i}).execWithin(tx, ch.receive(i));

    await ch.takeN(queries.length);


The traditional try-catch-finally model

I’ve never been a fan of the traditional try {} catch (e) {} finally {} construct in various languages for a variety of reasons.

  1. I don’t understand why there should be any code at all that should be outside of a try block. If it is outside, it means you’re being sloppy/optimistic about some error conditions.

  2. The catch occurs at the end of the try block, which means I tend to postpone thinking about error conditions until I reach the start of the catch block. It doesn’t fit my code flow.

  3. The code executed within finally blocks look like they have different scope than the code in the try block. The relationship between a finally block and the do-ing that it undoes is not usually clear, so it is not obvious what all operations need cleanup. C++ takes the sane route here by using destructor unwinding for cleanup instead of finally blocks.

  4. With try-catch, I often find code like this -

try {
    ...some error prone code ...
} catch (e) {
    // Do nothing.

This is not “handling” an error condition. It is just sweeping it under the carpet. “Handling” should mean “returning with a valid value”. Otherwise the error must propagate up. If you don’t know how to handle an error at some point in the code, don’t. Just let it bubble up.

The error model in the task macro

The task macro supports catch and finally clauses, but no try, due to reason (1) in the previous section. The clauses are block scoped so you can reason about error behaviour at the block level.


Raising an error condition is done using throw expr; as usual. However, within the context of a task, this translates to an error callback, as does an error actually thrown by other library code.

There is one difference between the way throw is interpreted by the task macro and how it is usually interpreted in JS. In JS, anything can be thrown, including null. However, the NodeJS style callback scheme uses err === null tests to determine whether an error occurred, so throwing a null is semantically nonsensical. So task’s interpretation of throw is that error propagation will begin only when the expression to be thrown is not null.


A catch (e) { ... } clause traps any error that occurs in the code that follows .. upto the end of the task’s scope. One enhancement is that the catch clause can take the form catch (ErrorClass e) { ... } in which case only errors that match the class will be handled by the block, with everything else bubbling up.

If you don’t have a return in the body of a catch clause in a task, the it will effectively rethrow the same error to the catch clause further up the chain.


A finally { ... } block can be placed anywhere and is expected to specify the code that is to be executed when control unwinds up the stack. The undo-ing is expected to be about whatever happened “above” the finally block and never about what happened “below” it. Therefore there can be multiple finally blocks and they will be run in the revers order in which they were encountered.

A finally someFunc(args...); statement is also supported. This form is a bit different from the finally block. The value of someFunc and the args are all computed when encountering this block during normal operation, but the function call is scheduled to take place upon unwinding. Note that someFunc can also be someObj.method and the context is kept correctly. This is a useful property in situations like this -

f <- fs.openFile('blah1');
finally f.close();
await doSomethingWith(f);
f <- fs.openFile('blah2');
finally f.close();
await doSomethingWith(f);

While unwinding, the second finally statement will close the “blah2” file and the first one will close the “blah1” file.

Note that finally actions can occur even within loops and will be unwound correctly with the correct state. The values of state variables that the finally blocks will see will be the values they had at the time the finally block was encountered, before an error happened that triggered the unwinding. This is because these actions cannot possibly know what to do with the values of the state variables at the time of the error condition.

WARNING: While technically you can return from within a finally block, you really shouldn’t. Also cleanup actions must not themselves throw errors.

Channels and errors

cspjs’s channels are implemented such that they themselves will not raise any error conditions, and will pass only non-error values to any callbacks passed to them. Since channels are the glue between tasks, it is better to pass the error to these tasks as values and let the logic in the tasks decide what to do with them instead of assuming that if some error was passed on a channel, the receiving task must bomb.

In particular, a channel’s .receive(id) method gives a NodeJS style callback that can be passed to a third party function that requires such a callback. The result will then be placed into the channel and can be read within a task. If any error occurred, the error will be passed as the .err property of the object put into the channel. If the operation succeeded, the .val property will give the result value. So a task is expected to look at the received value and decide how to handle errors.

The behaviour of throw described in the previous section helps ease the task of manual propagation of errors passed through channels. You can simply throw result.err; and place the non-error code below. This is because throw will only begin error propagation if an actual error value has been given.

var ch = new Channel();
someTask(args ... , ch.receive(42));
r <- chan ch;
console.assert( === 42);
throw r.err; // Will throw only if there is an error.


For async code, the task macro in cspjs provides a more robust error handling mechanism than ES5 javascript without garbling the syntax very much. It does this in addition to providing a clean syntax for describing processes and the channel based coordination between them. The result is code that can used on the server side or on the browser side.

Resuming and retrying operations when a failure occurs is not directly supported at the moment (as of 11 Feb 2014). This would require a different compilation approach compared to the current switch-case state machine implementation. However, since client code does not rely directly on the state_machine API and sees only Channel and the task macro itself, if this feature is desired, it would be possible at some point to change the implementation to support it while maintaining backward compatibility of code.

In all, sweet.js is a pretty sweet deal indeed and permits a programmer to bend the language while keeping compatibility with runtimes everywhere.

For my own JS code, for the foreseeable future, it will be cspjs and I will stop debating which async management library to use, all thanks to sweet.js.

To others out there selling promises … well, good luck to you!



  1. Improved semantics for control structures. All the block control structures now present their own exception handling scope. This means that a finally clause used inside an if block will get to run before exiting the if block. This prevents many kinds of resource leaks possible with the previous semantics - especially the way finally blocks behaved within loops.

  2. New statement retry;. So far, the only way in which an exception can be “handled” within a catch block has been to return a value from it. In some situations, a catch block can change some state and retry the following steps if there is reason to believe that the retry may succeed. For example, you may want to retry uploading a file to AWS S3 a little later if it failed on first try. The retry; statement offers a simple way to express such code. For example

function delay(secs, callback) {
    setTimeout(function () {
        callback(null, true);
    }, secs * 1000);

task crazyTask(x,y,z) {
    var attempt = 0;
    catch (e) {
        if (++attempt < 5) {
            await delay(30*60); // Wait for 30 minutes and try again.
        // else propagate the failure.

    // Do something that may fail for no reason occasionally,
    // like network stuff.