Creating truly asynchronus functions has never been easier!
The workers-pool
package allows you to easily create a pool of workers, pass them
some heavy tasks in the form of functions, and use the generated async function as
asynchronous Promise-based functions.
Important note 1: This is not yet fully tested, so be careful while using it!
Important note 2: Currently there is supports for only node environment!
npm i workers-pool
functions.js
const { Pool } = require('workers-pool');
const {isMainThread} = require('worker_threads');
// Some function to be made asynchronous
function add (a, b) {
return a + b;
}
function sub (a, b) {
return a - b;
}
// Step 1: export the functions
module.exports.add = add;
module.exports.sub = sub;
if (isMainThread){
// Step 2: create a pool (can create a
// separate pool for separate functions)
const myPool = new Pool({
taskRunners: [
{name: 'add', job: add, threadCount: 4, lockToThreads: true},
{name: 'sub', job: sub, threadCount: 4, lockToThreads: true},
],
totalThreadCount: 8,
});
// Step 3: generate the async version of the functions
let addAsync = myPool.getAsyncFunc('add');
let subAsync = myPool.getAsyncFunc('sub');
// Step 4: export the new async functions
module.exports.addAsync = addAsync;
module.exports.subAsync = subAsync;
module.exports.myPool = myPool;
}
index.js
const {addAsync, subAsync, myPool} = require('./functions.js')
async function test() {
try {
let result = await addAsync(2, 5);
console.log(result); // output: 7
} catch (error) {
console.log(error);
}
try {
let result = await subAsync(100, 10);
console.log(result) // output: 90
} catch (error) {
console.log(error);
}
}
test().then(() => {
myPool.terminate();
});
Note isMainThread
is essential to defferentiate whether a file is being run in the main
thread or a worker thread, so it can be used to prevent certain parts of the code, especially
pool and async functions creation, from being recursively run as shown in the example.
To allow dynamical addition of functions to workers, you only to enable the option of allowDynamicTaskRunnerAddition
.
You can still have static ones, but make sure that the totalThreadCount
is more than the sume of threadCount
of each static taskRunner
since they can cause a starvation for the dynamic ones.
index.js
const { Pool } = require('workers-pool');
const {isMainThread} = require('worker_threads');
// Some function to be made asynchronous
function mul (a, b) {
return a * b;
}
function add (a, b) {
return a + b;
}
function sub (a, b) {
return a - b;
}
// Export the functions
module.exports.add = add;
module.exports.sub = sub;
module.exports.mul = mul;
if (isMainThread) {
// Create the pool with some static TaskRunners (if wanted)
const myPool = new Pool({
taskRunners: [
{name: 'add', job: add, threadCount: 2, lockToThreads: true}, // Static
{name: 'sub', job: sub, threadCount: 2, lockToThreads: true}, // Static
],
totalThreadCount: 5,
allowDynamicTaskRunnerAddition: true,
});
// Then finally, to add a dynamic TaskRunner call addTaskRunner(TaskRunner[])
myPool.addTaskRunner({name: 'multiply', job: mul}); // Dynamic
let mulAsync = myPool.getAsyncFunc('multiply');
// Use the async function
mulAsync(2, 5).then((answer) => {
console.log(answer);
});
}
The dynamic TaskRunnres
are not bound to a worker thread; therefore, at every call to the generated
async function corresponding to them, they are required by a different thread and executed there.
The static TaskRunners
on the other hand, they are required by the worker thread at its instantiation and
they are bound to it.
As a result, we can have more of the dynamic TaskRunners
with a smaller number of threads; however, static TaskRunners
execute faster since there is no overhead of requiring the function everytime we try to execute the generated async function
corresponfing to it.
You can also get the statistics of the pools:
const Pool = require('workers-pool');
Pool.stats(); // brief info about the pools
Pool.stats(true); // Verbose info about the pools
You can terminate all the threads in the pool at once by calling:
myPool.terminate(true);