New post, deriving quickcheck
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rauhala.info/posts/2021-01-26-Tests-with-Deriving.md
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rauhala.info/posts/2021-01-26-Tests-with-Deriving.md
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---
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title: Tests with Deriving Via
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tags: haskell, testing, pbt
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---
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I have been using both `hedgehog` and `QuickCheck` based property-based testing
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frameworks, I'm fairly comfortable in writing tests and generators in both.
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Theoretical aspects aside, for a user, I feel like `hedgehog` is more
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ergonomic as it does automatic shrinking *and* does away with typeclasses. The
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former is important as writing good shrinkers is hard, remembering to write
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shrinkers is even harder. The latter is important when you need to modify your
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generation for some tests.
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In this post, I'll show that using `DerivingVia` extension and generic
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coercions can help you write almost as ergonomic `Arbitrary` definitions for
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`QuickCheck`. The initial idea is taken from the
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[Deriving Via](https://www.kosmikus.org/DerivingVia/deriving-via-paper.pdf) paper,
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but taken a little bit further. This post assumes some level of understanding
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of type level programming.
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For the examples, we're using a `Person` as shown in the examples below. The
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test we'll implement will be the `tripping` property. For the *expected*
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values, the `name` is something name-like and `age` is a range between 1-99.
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I'll use `hedgehog` to write the ideal case. The generator is light-weight, but
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has been customized for the business case. I'm using the `hedgehog-corpus`
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package for the name-like generation.
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``` haskell
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import GHC.Generics (Generic)
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import Data.Text (Text)
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import qualified Data.Aeson as A
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import Hedgehog
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import qualified Hedgehog.Gen as Gen
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import qualified Hedgehog.Range as Range
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import qualified Hedgehog.Corpus as Corpus
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data Person
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= Person { name :: Text
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, age :: Int
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}
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deriving stock (Show, Eq, Generic)
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deriving anyclass (A.ToJSON, A.FromJSON)
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genValidPerson :: Gen Person
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genValidPerson =
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Person <$> Gen.element Corpus.simpsons
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<*> Gen.integral (Range.linear 0 99)
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prop_encoding :: Property
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prop_encoding = property $ do
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p <- forAll genValidPerson
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pure p === A.eitherDecode (A.encode p)
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```
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For comparison, this is what I would write with QuickCheck without any helpers.
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There's quite a bit of added complexity, especially in the shrinker, and only
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with two fields.
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``` haskell
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import GHC.Generics (Generic)
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import Data.Text (Text)
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import qualified Data.Aeson as A
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import Test.QuickCheck
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data Person
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= Person { name :: Text
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, age :: Int
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}
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deriving stock (Show, Eq, Generic)
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deriving anyclass (A.ToJSON, A.FromJSON)
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instance Arbitrary Person where
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arbitrary = Person <$> elements simpsons <*> choose (1,99)
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where
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simpsons = ["bart", "marge", "homer", "lisa", "ned"]
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shrink Person{name,age} =
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[Person name' age'
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| name' <- [name]
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, age' <- shrinkIntegral age
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, age' >= 1
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, age' <= 99
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]
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prop_encoding :: Person -> Property
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prop_encoding p = pure p === A.eitherDecode (A.encode p)
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```
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Good, now that the base is done, let's see what we can do about making
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`QuickCheck` more ergonomic. The solution I'm outlining here relies on these
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features.
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- `DerivingVia` extension which can automatically generate instances for you if two types are `Coercible`
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- Isomorphism between the `Generic` representation of two types. For example `(a,b)` has a `Generic` representation that is the same as `data Foo = Foo a b`
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- `QuickCheck` modifiers, for example `PrintableString` which modify the arbitrary generation
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The paper defines this piece of code for deriving `Arbitrary` instances for
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anything that is generically isomorphic to something that is already an
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instance.
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``` haskell
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newtype SameRepAs a b = SameRepAs a
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instance
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( Generic a
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, Generic b
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, Arbitrary b
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, Coercible (Rep a ()) (Rep b ())
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)
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=> Arbitrary (a `SameRepAs` b) where
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arbitrary = SameRepAs . coerceViaRep <$> arbitrary
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where
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coerceViaRep :: b -> a
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coerceViaRep =
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to . (coerce :: Rep b () -> Rep a ()) . from
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```
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For my implementation, I'll be cleaning the code from the paper. I'm swapping
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the type parameters of the newtype and extract the coercion function to
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top-level so that I can define the `shrink` as well.
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``` haskell
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newtype Isomorphic a b = Isomorphic b
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type GenericCoercible a b =
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( Generic a
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, Generic b
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, Coercible (Rep a ()) (Rep b ())
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)
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genericCoerce :: forall a b. GenericCoercible a b => a -> b
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genericCoerce =
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to . (coerce @(Rep a ()) @(Rep b ())) . from
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instance
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( Arbitrary a
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, GenericCoercible a b
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)
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=> Arbitrary (a `Isomorphic` b) where
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arbitrary = Isomorphic . genericCoerce @a @b <$> arbitrary
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shrink (Isomorphic b) =
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Isomorphic . genericCoerce @a @b
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<$> shrink (genericCoerce @b @a b)
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```
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With this, we can now write `Arbitrary` instances using the tuple
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representation as an intermediary. At least as long as the child types have
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their instances properly set.
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``` haskell
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data Person
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= Person { name :: Text
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, age :: Int
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}
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deriving stock (Show, Eq, Generic)
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deriving anyclass (A.ToJSON, A.FromJSON)
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deriving (Arbitrary) via ((Text, Int) `Isomorphic` Person)
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```
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This is already a marked improvement to the original `Arbitrary` instance we
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wrote, but this does not yet satisfy our original requirement of generating
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only 'valid' persons. I would like to modify the instance generation on a more
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ad-hoc fashion. For this to happen, I would need some *modifiers* that control
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the arbitrary generation. I would like to write something like the instance
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below.
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``` haskell
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type Simpsons = '["marge", "bart", "homer", "lisa", "ned"]
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data Person
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= Person { name :: Text
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, age :: Int
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}
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deriving stock (Show, Eq, Generic)
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deriving anyclass (A.ToJSON, A.FromJSON)
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deriving (Arbitrary)
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via ((Corpus Simpsons Text, Range 1 99 Int) `Isomorphic` Person)
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```
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Let's start by defining the `Range` as it's more straightforward. This is just
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a `newtype` with a couple of phantom type variables, which is used in choosing
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the range of the generator. Shrinking is already quite complex (and probably
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not optimal!), I wouldn't want to write this multiple times.
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``` haskell
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newtype Range (from :: Nat) (to :: Nat) a = Range a
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instance
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( KnownNat from
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, KnownNat to
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, Num a
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, Ord a
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, Integral a
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) => Arbitrary (Range from to a) where
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arbitrary = Range . fromInteger <$> choose (natVal $ Proxy @from, natVal $ Proxy @to)
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shrink (Range x) = Range <$> shrunk
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where
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shrunk =
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[ x'
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| x' <- shrinkIntegral x
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, x >= fromInteger (natVal $ Proxy @from)
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, x <= fromInteger (natVal $ Proxy @to)
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]
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```
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Then the corpus. Just like the `Range` it's a `newtype` with a phantom
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variable, providing the input for the random generation. There's an extra
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typeclass involved to act as a typelevel function.
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``` haskell
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newtype Corpus (corpus :: [Symbol]) a = Corpus a
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class FromCorpus (corpus :: [Symbol]) where
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fromCorpus :: [String]
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instance FromCorpus '[] where
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fromCorpus = []
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instance (KnownSymbol x, FromCorpus xs) => FromCorpus (x ': xs) where
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fromCorpus = symbolVal (Proxy @x) : fromCorpus @xs
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instance (FromCorpus corpus, IsString x) => Arbitrary (Corpus corpus x) where
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arbitrary = Corpus . fromString <$> elements (fromCorpus @corpus)
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```
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With these instances out of the way, we can redo our original test with
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automatic instances.
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``` haskell
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import GHC.Generics (Generic)
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import Data.Text (Text)
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import qualified Data.Aeson as A
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import Test.QuickCheck
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import Isomorphic
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data Person
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= Person { name :: Text
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, age :: Int
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}
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deriving stock (Show, Eq, Generic)
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deriving anyclass (A.ToJSON, A.FromJSON)
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deriving Arbitrary via ((Corpus Simpsons Text, Range 1 99 Int) `Isomorphic` Person)
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prop_encoding :: Person -> Property
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prop_encoding p = pure p === A.eitherDecode (A.encode p)
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```
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</header>
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<main role="main">
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<div>
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<h1>$title$</h1>
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$body$
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</main>
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$body$
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Posted on $date$
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