generic-random-1.3.0.0: Generic random generators

Generic.Random.Tutorial

Description

Generic implementations of QuickCheck's arbitrary.

# Example

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 % ())


arbitrary :: Gen (Tree a) picks a Leaf with probability 9/17, or a Node with probability 8/17, and recursively fills their fields with arbitrary.

For Tree, genericArbitrary produces code 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 proportional to its weight; 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. The uniform distribution can be obtained with uniform.

## Uniform distribution

You can specify the uniform distribution (all weights equal) 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

GHC 8.0.1 and above only (base ≥ 4.9). For compatibility, the annotations are still allowed on older GHC versions, but ignored.

The weights actually have type W "ConstructorName" (just a newtype around 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 the Tree type.

( 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, 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. withBaseCase defG baseG is equal to defG 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 genericArbitraryRec with 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: • Arbitrary String may generate any unicode character, alphanumeric or not; • Arbitrary Int may generate negative values; • using newtype wrappers 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 :+ Gen String 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 String fields will use the provided generator of alphanumeric strings;
• the field "userId" of type Int will 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.