4 ms·

Found the theoretical informatician... Nope, not in real world software engineering. Especially not in JIT runtimes like V8. Try it! I tried it, code: https://

• throwitaway1123 2y ago
  It's a little bit faster (on my machine at least) if you combine the filter and map into a flatMap (it's still not as performant as the imperative solution though). function process3(input) { return input .flatMap((n) => (n % 2 === 0 ? n * 2 : [])) .reduce((a, b) => a + b, 0) }
  • 6510 2y ago
    If it needs to be fast use oldskool for() loops. function processfor(input){ let sum = 0 for (let i = 0; i < input.length; i++){ if (input[i] % 2 !== 0){ continue } sum += input[i] * 2 } return sum } https://jsfiddle.net/gaby_de_wilde/y7a39r15/5/ https://jsfiddle.net/gaby_de_wilde/y7a39r15/5/
    • throwitaway1123 2y ago
      Yeah the comment I was originally responding to included a for loop (in the Pastebin link). My point is that if you're set on going down the functional route you don't need separate map and filter steps, you can just use flatMap which is effectively a filter and map combined (returning an empty array filters out the current value, since an empty array gets flattened into nothing). Of course, if you want the most performant solution an imperative for loop is faster (which is what I said in my last comment).
      • 6510 2y ago
        input.reduce((a, b) => b % 2 !== 0 ? a : a + (b * 2), 0) or if you want it really silly. input.reduce((a, b) => a + (b % 2 && b * 2), 0) dont ask me why but for(a of b) is slower than for(i=0;i<b.length;i++)
        • throwitaway1123 2y ago
          Array.prototype.reduce can basically do almost anything a for loop can do, since it gives you access to state from one iteration to the next. The only reason I didn't remove the flatMap in my original example and convert it all to reduce, is because there's no longer any method chaining which was the point of the original comparison between the Go and JS examples. > dont ask me why but for(a of b) is slower than for(i=0;i<b.length;i++) Probably because for of loops use the iterator protocol. So I'm assuming under the hood the JS engine is actually invoking the Symbol.iterator method (which is slower). #! /usr/bin/env node --experimental-strip-types function processIterator(input: number[]) { let sum = 0 for (let i = input[Symbol.iterator](), r; (r = i.next()); ) { if (r.done) return sum if (r.value % 2 === 0) sum += r.value * 2 } } function processfor(input: number[]) { let sum = 0 for (let i = 0; i < input.length; i++) { const value = input[i] if (value % 2 === 0) sum += value * 2 } return sum } const input = Array.from({ length: 1_000_000 }, (_, i) => i) console.time('normal for loop') console.log(processfor(input)) console.timeEnd('normal for loop') console.time('iterator for loop') console.log(processIterator(input)) console.timeEnd('iterator for loop')
• nine_k 2y ago
  But this is apples and oranges. Process 1 creates and calls lambdas, etc. A proper comparison could be: # Case 1. for n in range(len(data)): data[n] = transform1(data[n]) data[n] = transform2(data[n]) # Case 2. for n in range(len(data)): data[n] = transform1(data[n]) for n in range(len(data)): data[n] = transform2(data[n])
  • thrww120956 2y ago
    It illustrates how this kind of code is used in the wild - array functions vs a for loop. What you did is not even a fruit, if I go along with your metaphor.
• bschwindHN 2y ago
  Funny enough, the iterator version is much faster in rust because the compiler can more easily optimize iterator chains than custom for loops: https://play.rust-lang.org/?version=stable&mode=release&edition=2021&gist=e4b11bda65cd43ba77678284c28e7f76 https://play.rust-lang.org/?version=stable&mode=release&edit... (I'd recommend running it on your own machine as the rust playground limits memory and will likely kill this program) Output from my machine: $ cargo run --release Finished `release` profile [optimized] target(s) in 0.05s Running `target/release/iterator` Process 1 returned 18270843109002848788 and took 64.58175ms Process 2 returned 18270843109002848788 and took 308.969083ms