Enum proptest::test_runner::RngAlgorithm [−][src]
Identifies a particular RNG algorithm supported by proptest.
Proptest supports dynamic configuration of algorithms to allow it to
continue operating with persisted regression files and to allow the
configuration to be expressed in the Config
struct.
Variants
The XorShift algorithm. This was the default up through and including Proptest 0.9.0.
It is faster than ChaCha but produces lower quality randomness and has some pathological cases where it may fail to produce outputs that are random even to casual observation.
The seed must be exactly 16 bytes.
The ChaCha algorithm. This became the default with Proptest 0.9.1.
The seed must be exactly 32 bytes.
This is not an actual RNG algorithm, but instead returns data directly from its "seed".
This is useful when Proptest is being driven from some other entropy source, such as a fuzzer.
If the seed is depleted, the RNG will return 0s forever.
Note that in cases where a new RNG is to be derived from an existing
one, the data is split evenly between them, regardless of how much
entropy is actually needed. This means that combinators like
prop_perturb
and prop_flat_map
can require extremely large inputs.
This is equivalent to the ChaCha
RNG, with the addition that it
records the bytes used to create a value.
This is useful when Proptest is used for fuzzing, and a corpus of
initial inputs need to be created. Note that in these cases, you need
to use the TestRunner
API directly yourself instead of using the
proptest!
macro, as otherwise there is no way to obtain the bytes
this captures.
Trait Implementations
impl Clone for RngAlgorithm
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fn clone(&self) -> RngAlgorithm
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pub fn clone_from(&mut self, source: &Self)
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impl Copy for RngAlgorithm
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impl Debug for RngAlgorithm
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impl Default for RngAlgorithm
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impl Display for RngAlgorithm
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impl Eq for RngAlgorithm
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impl FromStr for RngAlgorithm
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type Err = ()
The associated error which can be returned from parsing.
fn from_str(s: &str) -> Result<Self, ()>
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impl PartialEq<RngAlgorithm> for RngAlgorithm
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fn eq(&self, other: &RngAlgorithm) -> bool
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#[must_use]pub fn ne(&self, other: &Rhs) -> bool
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impl StructuralEq for RngAlgorithm
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impl StructuralPartialEq for RngAlgorithm
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Auto Trait Implementations
Blanket Implementations
impl<T> Any for T where
T: 'static + ?Sized,
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T: 'static + ?Sized,
impl<T> Borrow<T> for T where
T: ?Sized,
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T: ?Sized,
impl<T> BorrowMut<T> for T where
T: ?Sized,
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T: ?Sized,
pub fn borrow_mut(&mut self) -> &mut T
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impl<T> From<T> for T
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impl<T, U> Into<U> for T where
U: From<T>,
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U: From<T>,
impl<T> ToOwned for T where
T: Clone,
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T: Clone,
type Owned = T
The resulting type after obtaining ownership.
pub fn to_owned(&self) -> T
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pub fn clone_into(&self, target: &mut T)
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impl<T> ToString for T where
T: Display + ?Sized,
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T: Display + ?Sized,
impl<T, U> TryFrom<U> for T where
U: Into<T>,
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U: Into<T>,
type Error = Infallible
The type returned in the event of a conversion error.
pub fn try_from(value: U) -> Result<T, <T as TryFrom<U>>::Error>
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impl<T, U> TryInto<U> for T where
U: TryFrom<T>,
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U: TryFrom<T>,
type Error = <U as TryFrom<T>>::Error
The type returned in the event of a conversion error.
pub fn try_into(self) -> Result<U, <U as TryFrom<T>>::Error>
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impl<V, T> VZip<V> for T where
V: MultiLane<T>,
V: MultiLane<T>,