#rng #prng #random #rand #cli

app rng-cli

A random data generator CLI tool. Prints an infinite stream of data generated from a selected PRNG algorithm to stdout. Basically a CLI frontend for the rand crate.

2 unstable releases

0.2.0 Dec 13, 2020
0.1.0 Jul 14, 2019

#657 in Algorithms

24 downloads per month

Apache-2.0/MIT

16KB
213 lines

rng - A random number generator CLI tool.

Contains a number of (pseudo) random number generator algorithms. Given one of these it writes an infinite stream of bytes generated from that algorithm to stdout.

In unix terms it can be viewed as the equivalent of cat /dev/urandom but with a selection of different (mostly user-space) PRNG algorithms to choose from. This is usually way faster than /dev/urandom but can also provide lower entropy output, depending on which algorithm is chosen.

This tool is more or less a CLI frontend for the awesome rand crate.

How to use

rng [--seed <seed>] [--max threads] [--verbose] [<algorithm>]

If no arguments are given it uses the default algorithm and seeds it from the operating system. You might want to change the algorithm in order to fit your needs. Maybe you need a faster algorithm that is not cryptographically secure for example.

The --seed <seed> argument initializes the random number algorithm with the given <seed> instead of obtaining some entropy from the operating system. You don't want to use this for any cryptographical purposes. Giving a seed can be useful when you need determinism and must be able to produce identical data over multiple runs.

The --max-threads argument sets an upper limit on how many threads the tool can use in multithreaded mode. By default this is set to the number of hardware threads available on the system. The exception is when --seed is specified or the algorithm is "os", then the tool always runs in single-threaded mode.

Example

We try using the PCG algoritm a few times. Here we see that without a seed it produces different output each time, and with a seed it produces the same data as long as the seed is the same.

$ rng pcg | dd count=1024 | shasum
ae148d8b54ee544a50833c2a6915b0fca4cb95ed -
$ rng pcg | dd count=1024 | shasum
65a5651a2b1201adbe8bf60d9f7a2b940f6e188b -
$ rng pcg --seed 6 | dd count=1024 | shasum
fc14baccbc847339408457335dc67bc4c9785185 -
$ rng pcg --seed 6 | dd count=1024 | shasum
fc14baccbc847339408457335dc67bc4c9785185 -
$ rng pcg --seed 7 | dd count=1024 | shasum
c7a169d195c395867396d16d70c1a3c19f63b5cc -

Why?

This tool was invented because I needed to benchmark IO (both filesystem and network) on Linux. Reading from /dev/urandom was too slow, the machine spent too much time computing the actual data and too little time performing the IO I wanted to test. On the other hand, getting data from /dev/zero is fast! But any compression (common in both network protocols and filesystems) will be able to optimize this stream down to almost nothing. And again, the actual IO is not being properly benchmarked.

So what I needed was a very fast stream of incompressible data. The rand crate provides a unified interface to a number of different random number algorithms. Some of them suiting my use case.

Dependencies

~2.2–3MB
~54K SLoC