Struct TestRng

pub struct TestRng { /* private fields */ }

Proptest’s random number generator.

Implementations

impl TestRng

pub fn from_seed(algorithm: RngAlgorithm, seed: &[u8]) -> Self

Create a new RNG with the given algorithm and seed.

Any RNG created with the same algorithm-seed pair will produce the same sequence of values on all systems and all supporting versions of proptest.

Panics

Panics if seed is not an appropriate length for algorithm.

pub fn bytes_used(&self) -> Vec<u8>

Dumps the bytes obtained from the RNG so far (only works if the RNG is set to Recorder).

Panics

Panics if this RNG does not capture generated data.

pub fn deterministic_rng(algorithm: RngAlgorithm) -> Self

Returns a TestRng with a particular hard-coded seed.

The seed value will always be the same for a particular version of Proptest and algorithm, but may change across releases.

This is useful for testing things like strategy implementations without risking getting “unlucky” RNGs which deviate from average behaviour enough to cause spurious failures. For example, a strategy for bool which is supposed to produce true 50% of the time might have a test which checks that the distribution is “close enough” to 50%. If every test run starts with a different RNG, occasionally there will be spurious test failures when the RNG happens to produce a very skewed distribution. Using this or TestRunner::deterministic() avoids such issues.

Trait Implementations

impl Clone for TestRng

fn clone(&self) -> TestRng

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for TestRng

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl RngCore for TestRng

fn next_u32(&mut self) -> u32

Return the next random u32.

fn next_u64(&mut self) -> u64

Return the next random u64.

fn fill_bytes(&mut self, dest: &mut [u8])

Fill dest with random data.

fn try_fill_bytes(&mut self, dest: &mut [u8]) -> Result<(), Error>

Fill dest entirely with random data.