| Safe Haskell | None |
|---|---|
| Language | Haskell2010 |
Generic.Random.Tutorial
Description
Generic implementations of
QuickCheck's
arbitrary.
Example
Define your type.
data Tree a = Leaf a | Node (Tree a) (Tree a)
deriving Generic
Pick an arbitrary implementation, specifying the required distribution of
data constructors.
instance Arbitrary a => Arbitrary (Tree a) where arbitrary =genericArbitrary(9%8%())
That random generator arbitrary :: picks a
Gen (Tree a)Leaf with probability 9/17, or a
Node with probability 8/17, and recursively fills their fields with
arbitrary.
For Tree, the generic implementation genericArbitrary is equivalent to
the following:
genericArbitrary:: Arbitrary a =>Weights(Tree a) -> Gen (Tree a)genericArbitrary(x%y%()) = frequency [ (x, Leaf<$>arbitrary) , (y, Node<$>arbitrary<*>arbitrary) ]
Distribution of constructors
The distribution of constructors can be specified as
a special list of weights in the same order as the data type definition.
This assigns to each constructor a probability p_C proportional to its weight weight_C;
in other words, p_C = weight_C / sumOfWeights.
The list of weights is built up with the ( operator as a cons, and using
the unit %)() as the empty list, in the order corresponding to the data type
definition.
Uniform distribution
You can specify the uniform distribution (all weights equal to 1) with uniform.
(genericArbitraryU is available as a shorthand for
.)genericArbitrary uniform
Note that for many recursive types, a uniform distribution tends to produce big or even infinite values.
Typed weights
The weights actually have type (just a newtype
around W "ConstructorName"Int), so that you can annotate a weight with its corresponding
constructor. The constructors must appear in the same order as in the
original type definition.
This will type-check:
((x ::W"Leaf")%(y ::W"Node")%()) ::Weights(Tree a) ( x%(y ::W"Node")%()) ::Weights(Tree a)
This will not:
((x ::W"Node")%y%()) ::Weights(Tree a) -- Requires an order of constructors different from the definition of theTreetype. ( x%y%z%()) ::Weights(Tree a) -- Doesn't have the right number of weights.
Ensuring termination
As mentioned earlier, one must be careful with recursive types
to avoid producing extremely large values.
The alternative generator genericArbitraryRec decreases the size
parameter at every call to keep values at reasonable sizes.
It is to be used together with withBaseCase.
For example, we may provide a base case consisting of only Leaf:
instance Arbitrary a => Arbitrary (Tree a) where arbitrary =genericArbitraryRec(1%2%())`withBaseCase`(Leaf<$>arbitrary)
That is equivalent to the following definition. Note the
resize modifier.
arbitrary :: Arbitrary a => Gen (Tree a)
arbitrary = sized $ \n ->
-- "if" condition from withBaseCase
if n == 0 then
Leaf <$> arbitrary
else
-- genericArbitraryRec
frequency
[ (1, resize (max 0 (n - 1)) (Leaf <$> arbitrary))
, (2, resize (n `div` 2) (Node <$> arbitrary <*> arbitrary))
]
The resizing strategy is as follows:
the size parameter of Gen is divided among the fields of
the chosen constructor, or decreases by one if the constructor is unary.
is equal to withBaseCase defG baseGdefG as long as the size parameter
is nonzero, and it becomes baseG once the size reaches zero.
This combination generally ensures that the number of constructors remains
bounded by the initial size parameter passed to Gen.
Automatic base case discovery
In some situations, generic-random can also construct base cases automatically. This works best with fully concrete types (no type parameters).
{-# LANGUAGE FlexibleInstances #-}
instance Arbitrary (Tree ()) where
arbitrary = genericArbitrary' (1 % 2 % ())
The above instance will infer the value Leaf () as a base case.
To discover values of type Tree a, we must inspect the type argument a,
thus we incur some extra constraints if we want polymorphism.
It is preferrable to apply the type class BaseCase to the instance head
(Tree a) as follows, as it doesn't reduce to something worth seeing.
{-# LANGUAGE FlexibleContexts, UndecidableInstances #-}
instance (Arbitrary a, BaseCase (Tree a))
=> Arbitrary (Tree a) where
arbitrary = genericArbitrary' (1 % 2 % ())
The BaseCase type class finds values of minimal depth,
where the depth of a constructor is defined as 1 + max(0, depths of fields),
e.g., Leaf () has depth 2.
Note about lists
The Arbitrary instance for lists can be problematic for this way
of implementing recursive sized generators, because they make a lot of
recursive calls to arbitrary without decreasing the size parameter.
Hence, as a default, genericArbitraryRec also detects fields which are
lists to replace arbitrary with a different generator that divides
the size parameter by the length of the list before generating each
element. This uses the customizable mechanism shown in the next section.
If you really want to use arbitrary for lists in the derived instances,
substitute with genericArbitraryRec.genericArbitraryRecG ()
arbitrary =genericArbitraryRecG()`withBaseCase`baseGen
Some combinators are available for further tweaking: listOf', listOf1',
vectorOf'.
Custom generators for some fields
Example 1 (Gen, FieldGen)
Sometimes, a few fields may need custom generators instead of arbitrary.
For example, imagine here that String is meant to represent
alphanumerical strings only, and that IDs are meant to be nonnegative,
whereas balances can have any sign.
data User = User {
userName :: String,
userId :: Int,
userBalance :: Int
} deriving Generic
A naive approach has the following problems:
may generate any unicode character, alphanumeric or not;ArbitraryStringmay generate negative values;ArbitraryInt- using
newtypewrappers or passing generators explicitly to properties may be impractical (the maintenance overhead can be high because the types are big or change often).
Using generic-random, we can declare a (heterogeneous) list of generators to
be used instead of arbitrary when generating certain fields.
customGens ::FieldGen"userId" Int:+GenString customGens =FieldGen(getNonNegative<$>arbitrary):+listOf(elements(filter isAlphaNum [minBound .. maxBound]))
Now we use the genericArbitraryG combinator and other G-suffixed
variants that accept those explicit generators.
- All
Stringfields will use the provided generator of alphanumeric strings; - the field
"userId"of typeIntwill use the generator of nonnegative integers; - everything else defaults to
arbitrary.
instance Arbitrary User where
arbitrary = genericArbitrarySingleG customGens
Example 2 (ConstrGen)
Here's the Tree type from the beginning again.
data Tree a = Leaf a | Node (Tree a) (Tree a)
deriving Generic
We will generate "right-leaning linear trees", which look like this:
Node (Leaf 1)
(Node (Leaf 2)
(Node (Leaf 3)
(Node (Leaf 4)
(Leaf 5))))To do so, we force every left child of a Node to be a Leaf:
{-# LANGUAGE ScopedTypeVariables #-}
instance Arbitrary a => Arbitrary (Tree a) where
arbitrary = genericArbitraryUG customGens
where
-- Generator for the left field (i.e., at index 0) of constructor Node,
-- which must have type (Tree a).
customGens :: ConstrGen "Node" 0 (Tree a)
customGens = ConstrGen (Leaf <$> arbitrary)
That instance is equivalent to the following:
instance Arbitrary a => Arbitrary (Tree a) where
arbitrary = oneof
[ Leaf <$> arbitrary
, Node <$> (Leaf <$> arbitrary) <*> arbitrary
-- ^ recursive call
]
Custom generators reference
The custom generator modifiers that can occur in the list are:
Gen: a generator for a specific type;FieldGen: a generator for a record field;ConstrGen: a generator for a field of a given constructor;Gen1: a generator for "containers", parameterized by a generator for individual elements;Gen1_: a generator for unary type constructors that are not containers.
Suggestions to add more modifiers or otherwise improve this tutorial are welcome! The issue tracker is this way.