This conversation likely interests you - Secure lottery function / Random Number Generation
Random module is here - Random :: Internet Computer
thank you! It seems that I will have to write something myself then.
I gave it a go here xorshift128plus.mo · GitHub
Seems to be generating pseudo random numbers but since I’m new Motoko learner I’m pretty sure it can be written better.
My implementation takes around 15s to return… Generating blobs is expensive and also I need to learn more about how to handle state
The latest version takes ~3s but still, it is too much. It seems that since I mutate the state it needs consensus…
Just a heads up ~3 second consensus is built into the local dev environment so developers won’t be surprised when they deploy to the mainnet. But you’re spot on - All update calls require consensus. Query calls do not.
ah, I see. ty you for the clarification @Steve
What’s left now to replicate Math.random is to convert the returned integer to a Float between 0 and 1…
I’m trying to figure it out from v8/math-random.cc at dc712da548c7fb433caed56af9a021d964952728 · v8/v8 · GitHub
Hey @chchrist, here is a thought!
Since Nat8 can store the values 0…255, all you have to do is divide the random number by highest possible number:
var myRandom : Nat8 = 123; let mappedRandom : Float = Float.fromInt(myRandom) / Float.fromInt(255);
A better way might be to use the
/// Distributes outcomes in the numeric range [0 .. 2^p - 1]. /// Seed blob must contain at least ((p+7) / 8) bytes.
So you could do something like
let random = Random.rangeFrom(32, someBlob) // between 0..4294967295 let max : Float = 4294967295; let newRandom = Float.fromInt(random) / max;
ty @Hazel! As Einstein once said " The definition of genius is taking the complex and making it simple."
Now I need to find out why I’m getting this error…
The Replica returned an error: code 5, message: "Canister rrkah-fqaaa-aaaaa-aaaaq-cai trapped explicitly: losing precision"
now I didn’t expect that! I guess that makes sense though - I’ll need to think a bit on a better mapping function.
Are you using fixed-with numbers (e.g.
Int8)? “losing precision” sounds like the error message when a lossy conversion actually loses data.