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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