`module Random: ``Random`

`val init : ``int -> unit`

Initialize the generator, using the argument as a seed. The same seed will always yield the same sequence of numbers.

`val full_init : ``int array -> unit`

Same as `Random.init`

but takes more data as seed.

`val self_init : ``unit -> unit`

Initialize the generator with a random seed chosen
in a system-dependent way. If `/dev/urandom`

is available on
the host machine, it is used to provide a highly random initial
seed. Otherwise, a less random seed is computed from system
parameters (current time, process IDs).

`val bits : ``unit -> int`

Return 30 random bits in a nonnegative integer.

**Before 3.12.0**used a different algorithm (affects all the following functions)

`val int : ``int -> int`

`Random.int bound`

returns a random integer between 0 (inclusive)
and `bound`

(exclusive). `bound`

must be greater than 0 and less
than 2^{30}.

`val full_int : ``int -> int`

`Random.full_int bound`

returns a random integer between 0 (inclusive)
and `bound`

(exclusive). `bound`

may be any positive integer.

If `bound`

is less than 2^{30}, `Random.full_int bound`

is equal to
`Random.int`

` bound`

. If `bound`

is greater than 2^{30} (on 64-bit systems
or non-standard environments, such as JavaScript), `Random.full_int`

returns a value, where `Random.int`

raises `Invalid_argument`

.

**Since**4.13.0

`val int32 : ``Int32.t -> Int32.t`

`Random.int32 bound`

returns a random integer between 0 (inclusive)
and `bound`

(exclusive). `bound`

must be greater than 0.

`val nativeint : ``Nativeint.t -> Nativeint.t`

`Random.nativeint bound`

returns a random integer between 0 (inclusive)
and `bound`

(exclusive). `bound`

must be greater than 0.

`val int64 : ``Int64.t -> Int64.t`

`Random.int64 bound`

returns a random integer between 0 (inclusive)
and `bound`

(exclusive). `bound`

must be greater than 0.

`val float : ``float -> float`

`Random.float bound`

returns a random floating-point number
between 0 and `bound`

(inclusive). If `bound`

is
negative, the result is negative or zero. If `bound`

is 0,
the result is 0.

`val bool : ``unit -> bool`

`Random.bool ()`

returns `true`

or `false`

with probability 0.5 each.

The functions from module `Random.State`

manipulate the current state
of the random generator explicitly.
This allows using one or several deterministic PRNGs,
even in a multi-threaded program, without interference from
other parts of the program.

module State:`sig`

..`end`

`val get_state : ``unit -> State.t`

Return the current state of the generator used by the basic functions.

`val set_state : ``State.t -> unit`

Set the state of the generator used by the basic functions.