7d52d612ce
* removed debug println * added newline to the end of the file * time: add .unix_time_milli() method; rand,time: add tests * rand: add more ulid tests; move tests to a separate file random_identifiers_test.v * run vfmt over vlib/rand/random_identifiers_test.v * speed up time.unix_time_milli * simplify and speedup time.unix_time/0 and time.new_time/1 * update comment about rand.ulid() * fix terminating 0 off by 1 issue in rand.ulid() * optimize time.new_time() * restore the master version of vlib/time/parse.v * make test_unix_time more robust Co-authored-by: Delyan Angelov <delian66@gmail.com> |
||
|---|---|---|
| .. | ||
| mt19937 | ||
| musl | ||
| pcg32 | ||
| splitmix64 | ||
| sys | ||
| util | ||
| wyrand | ||
| README.md | ||
| rand.v | ||
| random_identifiers_test.v | ||
| random_numbers_test.v | ||
README.md
Quickstart
The V rand module provides two main ways in which users can generate pseudorandom numbers:
- Through top-level functions in the
randmodule.import rand- Import therandmodule.rand.seed(seed_data)to seed (optional).- Use
rand.int(),rand.u32n(max), etc.
- Through a generator of choice. The PRNGs are included in their respective submodules.
import rand.pcg32- Import the module of the PRNG required.mut rng := pcg32.PCG32RNG{}- Initialize the struct. Note that themutis important.rng.seed(seed_data)- optionally seed it with an array ofu32values.- Use
rng.int(),rng.u32n(max), etc.
General Background
A PRNG is a Pseudo Random Number Generator. Computers cannot generate truly random numbers without an external source of noise or entropy. We can use algorithms to generate sequences of seemingly random numbers, but their outputs will always be deterministic. This is often useful for simulations that need the same starting seed.
If you need truly random numbers that are going to be used for cryptography, use the crypto.rand module.
Guaranteed functions
The following 21 functions are guaranteed to be supported by rand as well as the individual PRNGs.
seed(seed_data)whereseed_datais an array ofu32values. Different generators require different number of bits as the initial seed. The smallest is 32-bits, required bysys.SysRNG. Most others require 64-bits or 2u32values.u32(),u64(),int(),i64(),f32(),f64()u32n(max),u64n(max),intn(max),i64n(max),f32n(max),f64n(max)u32_in_range(min, max),u64_in_range(min, max),int_in_range(min, max),i64_in_range(min, max),f32_in_range(min, max),f64_in_range(min, max)int31(),int63()
Utility Functions
All the generators are time-seeded. The helper functions publicly available in rand.util module are:
time_seed_array()- returns a[]u32that can be directly plugged into theseed()functions.time_seed_32()andtime_seed_64()- 32-bit and 64-bit values respectively that are generated from the current time.
Caveats
Note that the sys.SysRNG struct (in the C backend) uses C.srand() which sets the seed globally. Consequently, all instances of the RNG will be affected. This problem does not arise for the other RNGs. A workaround (if you must use the libc RNG) is to:
- Seed the first instance.
- Generate all values required.
- Seed the second instance.
- Generate all values required.
- And so on...