So, if I use `math/rand` the RNG will always output the same sequence of random numbers?
How do I make sure I'm passing a random seed to my RNG?
(I must be missing something here)
How do I make sure I'm passing a random seed to my RNG?
(I must be missing something here)
math/rand provides global functions using a global RNG, as well as the ability to instantiate your own RNG and call functions (methods) on that RNG.
Previously, the global functions all used a seed of 1, which made them generate identical sequences. Now, they use random seed, which makes them less-easily predictable (though still predictable).
There is no change to the self-instantiated RNGs.
> How do I make sure I'm passing a random seed to my RNG?
With the change, using the global functions in Go 1.20+ is the same as instantiating your own RNG with a random seed.
https://en.m.wikipedia.org/wiki/Hardware_random_number_gener...
Maybe we're in the first batch of simulations, and the tester came along and asks why they're all identical. The cosmic coder then realises that they forgot to call the function to seed the prng.
*BSD, newer macOS, and GNU libc: int getentropy(void *buffer, size_t length);
Linux 3.19+: ssize_t getrandom(void *buf, size_t buflen, unsigned int flags);
iOS and macOS 10.7+: int SecRandomCopyBytes(SecRandomRef, size_t, uint8_t *);
Fuchsia: void zx_cprng_draw(void* buffer, size_t buffer_size);
Any *nix: Read from "/dev/random" (or "/dev/urandom" under the assumption that your system has already enough entropy).
Windows: There are different functions/libraries depending on the Windows version and some of them are a complicated multi-step mess.
Some time ago I wrote a C library that abstracts that away just for fun: https://github.com/panzi/portable_get_random*