[swift-evolution] [Proposal] Random Unification

Alejandro Alonso aalonso128 at outlook.com
Fri Nov 17 12:02:15 CST 2017

I agree with all your points, but that’s if we were implementing a randomness source. What we’re providing is a random number generator that takes some randomness from a source and uses that to give the user an actual number it knows about. That differs from a randomness source because a generator doesn’t create randomness, it simply uses it to generate a random number. For this reason I think that rngs should not write to a pointer.

- Alejandro

El nov. 17, 2017, a la(s) 11:29, David Waite <david at alkaline-solutions.com<mailto:david at alkaline-solutions.com>> escribió:

On Nov 16, 2017, at 8:12 PM, Alejandro Alonso via swift-evolution <swift-evolution at swift.org<mailto:swift-evolution at swift.org>> wrote:

While this could work, I don’t believe this aligns with Swift. SecRandomCopyBytes and arc4random_buf do it this way because of the languages they were built in, and for SecRandomCopyBytes, it needs to also return an error (in the form of its return value). For custom generators this doesn’t make sense to me because it seems as if each generator will have the same code to return an integer of a different size from what it’ll be producing. I really like Xiaodi’s solution to explicitly state what type of integer a custom generator will return, and as a default implementation, we provide a way to transform that.

- Alejandro

The random source does not know about integers or floats or colors. It just provides randomness. Higher level code is what determines for instance how to generate (for example) a random number between 1 and 27 with equal probability - which could theoretically require more than a 64 bits of randomness (with probability of that depending on luck and the algorithm used)

A double is not a uniform distribution, so likewise simply casting a 64 bit integer value to a double would not yield appropriate results (you’d have a significant chance of NaN values, for instance)

Thats why I would recommend having the random source just be a sequence of bytes. The higher level API choosing random elements from a Strideable or shuffling an array *should* be the interfaces that developers use, rather than directly reading from the random source

I proposed “read” below because it is compatible with the signature on InputStream, which both would allow you to easily bridge /dev/random or /dev/urandom in as well as have predefined data as a source of randomness for predictable testing.

Predictable randomness and multiple sources of randomness are important in a few scenarios, including gaming where the same “random” choices need to be made locally for each player to keep the games in sync.


On Nov 15, 2017, 11:26 AM -0600, Nate Cook <natecook at apple.com<mailto:natecook at apple.com>>, wrote:
On Nov 13, 2017, at 7:38 PM, Xiaodi Wu <xiaodi.wu at gmail.com<mailto:xiaodi.wu at gmail.com>> wrote:

On Mon, Nov 13, 2017 at 7:12 PM, Alejandro Alonso <aalonso128 at outlook.com<mailto:aalonso128 at outlook.com>> wrote:
After thinking about this for a while, I don’t agree with with an associated type on RandomNumberGenerator. I think a generic FixedWidthInteger & UnsignedInteger should be sufficient. If there were an associated type, and the default for Random was UInt32, then there might be some arguments about allowing Double to utilize the full 64 bit precision. We could make Random32 and Random64, but I think people will ask why there isn’t a Random8 or Random16 for those bit widths. The same could also be said that any experienced developer would know that his PRNG would be switched if he asked for 32 bit or 64 bit.

I don't understand. Of course, Double would require 64 bits of randomness. It would obtain this by calling `next()` as many times as necessary to obtain the requisite number of bits.

At base, any PRNG algorithm yields some fixed number of bits on each iteration. You can certainly have a function that returns an arbitrary number of random bits (in fact, I would recommend that such an algorithm be a protocol extension method on RandomNumberGenerator), but it must be built on top of a function that returns a fixed number of bits, where that number is determined on a per-algorithm basis. Moreover--and this is important--generating a random unsigned integer of arbitrary bit width in a sound way is actually subtly _different_ from generating a floating-point value of a certain bit width, and I'm not sure that one can be built on top of the other. Compare, for example:


(These are essentially Swift versions of C++ algorithms.)

Basically, what I'm saying is that RandomNumberGenerator needs a `next()` method that returns a fixed number of bits, and extension methods that build on that to return T : FixedWidthInteger & UnsignedInteger of arbitrary bit width or U : BinaryFloatingPoint of an arbitrary number of bits of precision. Each individual RNG does not need to reimplement the latter methods, just a method to return a `next()` value of a fixed number of bits. You are welcome to use my implementation.

An alternative to this is to have the random generator write a specified number of bytes to a pointer’s memory, as David Waite and others have suggested. This is same way arc4random_buf and SecRandomCopyBytes are implemented. Each random number generator could then choose the most efficient way to provide the requested number of bytes. The protocol could look something like this:

protocol RandomNumberGenerator {
    /// Writes the specified number of bytes to the given pointer’s memory.
    func read(into p: UnsafeMutableRawPointer, bytes: Int)

This is less user-friendly than having a next() method, but I think that’s a good thing—we very much want people who need a random value to use higher-level APIs and just pass the RNG as a parameter when necessary.


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