Use async await with Array.map
By using Array.map
, you dispatch the async operations concurrently. You then await completion of all calls with Promise.all
. The asyncMap
function is a sweet bit of sugar. Our example just multiplies numbers for demonstration purposes.
Understanding Promise Combinators: The Fantastic Four
When juggling with multiple promises (not recommended IRL), familiarise yourself with following Promise combinators:
Promise.all
: Waits until all its promises are kept—no exceptions.Promise.allSettled
: Puts all its promise-debts on a payment plan, no matter how those plans end.Promise.any
: Celebrates the successful resolution of a single promise. Quite optimistic!Promise.race
: Here, every promise for itself. First to resolve (or reject) wins the race.
In most scenarios, Promise.all
will be your go-to. But Promise.allSettled
can be your best pal if you need to know the fate of all operations, success or fail.
Error handling: Anticipating Promise broken (sad face)
When performing asynchronous mapping, you must contain any chaos. This is where error handling comes in:
Wrapping the await Promise.all
within a try/catch
block lets you catch errors and handle them with grace and dignity, ensuring your app doesn't go caput.
Enhancing Readability: Bullet Speed.
Arrow functions within Array.map
can make your async mappings look as clean as your room (presumably):
Pairing arrow functions & async/await can significantly reduce boilerplate and turbocharge the clarity of your code.
TypeScript: The Butcher's scale of Javascript
With TypeScript, you're assured of type safety while using Array.map
. This increases the likelihood that your code behaves as expected, avoiding sudden heating of your machine.
Testing Corners in Async Iterations
For testing async/await
mappings, simulate async operations. The randomDelay
function is great for network latency simulation or file I/O tests:
Testing with induced delays helps ensure your code's behavior under asynchronous conditions.
Bluebird Library: Promise's Cool Cousin
Bluebird offers Promise.map()
that provides concurrency control—perfect for edge cases:
This pattern helps manage system resources when bursting with concurrent operations.
Performance Juicing
When processing large datasets or heavy operations, optimisation matters:
- Cap concurrency: Keep a leash on simultaneous operations to prevent overcrowding of the event loop.
- Chunk processing: Divide the data set into smaller chunks and process them in isolation.
- Bypass unnecessary computations: Skip iterations if they won't affect the result.
Keeping Result Order: First In, First Out
When using Array.map
and await
on an array of promises, the resolution order is the same as the triggering order:
Regardless of promise resolution times, dataInOrder
maintains the order of ids
, preventing any "unexpected" occurrences.
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