-- | Generic implementations of -- [QuickCheck](https://hackage.haskell.org/package/QuickCheck)'s -- @arbitrary@. -- -- = Example -- -- Define your type. -- -- @ -- data Tree a = Leaf a | Node (Tree a) (Tree a) -- deriving 'GHC.Generics.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)./ -- -- The weights actually have type @'W' \"ConstructorName\"@ (just a newtype -- around 'Int'), so that you can annotate a weight with its corresponding -- constructor, and it will be checked that you got the order right. -- -- 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 -- 'Test.QuickCheck.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 -- close to 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 -- eleement. 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 -- -- 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 'GHC.Generics.Generic' -- @ -- -- - @'Test.QuickCheck.Arbitrary' String@ may generate any unicode character, -- alphanumeric or not; -- - @'Test.QuickCheck.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 when generating certain fields (remember to end lists with @()@). -- -- @ -- 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 -- @ -- -- The custom generator modifiers that can occur in the list are: -- -- - 'Test.QuickCheck.Gen': a generator for a specific type; -- - 'FieldGen': a generator for a field name and type; -- - '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! -- module Generic.Random.Tutorial () where import Generic.Random