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test.dhall |
purescript-yoga-json
yoga-json
is a light-weight and simple json library for purescript.
Note: This library was initially forked from the amazing simple-json (MIT Licence). See migrate from simple-json
for migration instructions.
Table of Contents
Features
- 😌 simple and easy to use json codecs
- 🪶 light-weight
- 🤖 built-in support for many common types (
Sum
types, Tuples, BigInts, Maps, JSDate, DateTime, Eithers, NonEmptyStrings ) - 🖍 human-friendly error reporting
Installation
spago install yoga-json
Usage
purescript-yoga-json
basically provides two functions writeJSON
and readJSON
.
Use writeJSON
to serialise a type to a JSON string:
import Yoga.JSON as JSON
serialised :: String
serialised =
JSON.writeJSON { first_name: "Lola", last_name: "Flores" }
-- {"last_name":"Flores","first_name":"Lola"}
Use readJSON
to deserialise a JSON string:
import Yoga.JSON as JSON
deserialised :: Either MultipleErrors { first_name :: String, last_name :: String }
deserialised = JSON.readJSON """{ "first_name": "Lola", "last_name": "Flores" }"""
-- Right { first_name: "Lola", last_name: "Flores" }
As the parsing can fail, readJSON
returns an Either
, potentially containing a Left
data constructor with MultipleErrors
. If you don't care about the specific errors, you can use readJSON_
, which returns a Maybe
:
deserialised :: Maybe { first_name :: String, last_name :: String }
deserialised = JSON.readJSON_ """{ "first_name": "Lola", "last_name": "Flores" }"""
-- Just { first_name: "Lola", last_name: "Flores" }
Sum types
purescript-yoga-json
provides utility functions to easily generate serialisers and deserialisers for your sum types.
Let's start with a simple example of a sum type where our data constructors do not contain any further values:
import Data.Either (Either)
import Data.Generic.Rep (class Generic)
import Yoga.JSON as JSON
import Yoga.JSON.Generics (genericReadForeignEnum, genericWriteForeignEnum)
import Yoga.JSON.Generics.EnumSumRep as Enum
data MyEnum = Enum1 | Enum2 | Enum3
Now, we need to derive a Generic
instance for it:
derive instance Generic MyEnum _
-- and optionally a Show instance
instance Show MyEnum where
show = genericShow
Next, we define a WriteForeign
instance and implement the writeImpl
function using genericWriteForeignEnum Enum.defaultOptions
.
instance WriteForeign MyEnum
where
writeImpl = genericWriteForeignEnum Enum.defaultOptions
Similarly, we implement the ReadForeign
instance using genericReadForeignEnum Enum.defaultOptions
instance ReadForeign MyEnum
where
readImpl = genericReadForeignEnum Enum.defaultOptions
That's all, we can now serialise our data type:
serialised = writeJSON { "myEnum": Enum3 }
-- {"myEnum":"Enum3"}
and deserialise it:
deserialised :: E { "myEnum" :: MyEnum }
deserialised = readJSON serialised
-- Right { myEnum: Enum3 }
Writing custom codecs
In order to write your own, custom codecs you will need to provide instances for WriteForeign
and ReadForeign
.
Let's see an example. We define a simple data type TrafficLight
that has three data constructors Red
, Yellow
and Green
:
data TrafficLight = Red | Yellow | Green
We would like to serialise these constructors as lower case strings "red"
, "yellow"
and "green"
.
First we need to provide an implementation for the WriteForeign
type class, that tells yoga-json
how to serialise the type. We pattern match on the three different data constructors and write them as the three String
s red, yellow and green, using the same writeImpl
function:
instance WriteForeign TrafficLight where
writeImpl Red = writeImpl "red"
writeImpl Yellow = writeImpl "yellow"
writeImpl Green = writeImpl "green"
This works, because yoga-json
already nows how to serialise a String
.
Similarly, we need to provide an implementation for the ReadForeign
type class, that tells yoga-json
how to deserialise the type. We start by deserialising into a primitive type, typically a String or an Object, and then convert it to our desired Purescript type.
Since we don't know the input String
, it might contain invalid data and therefore deserialisation might fail. yoga-json
uses the ExceptT
monad to reflect this. We can return valid values using pure
and fail
on invalid values:
instance ReadForeign TrafficLight where
readImpl json = do
-- deserialise into a string
str :: String <- readImpl json
-- now we pattern match on our valid types
case str of
"red" -> pure Red
"yellow" -> pure Yellow
"green" -> pure Green
-- and fail if we get an invalid type
other -> fail $ ForeignError $ "Failed to parse " <> other <> " as TrafficLight"
Now we can serialise our data type:
serialised = writeJSON { "trafficLight": Red }
-- {"trafficLight":"red"}
and deserialise it:
deserialised :: E { "trafficLight" :: TrafficLight }
deserialised = readJSON """{ "trafficLight": "green" }"""
-- Right { trafficLight: Green }
deserialisedUnknown :: E { "trafficLight" :: TrafficLight }
deserialisedUnknown = readJSON """{ "trafficLight": "purple" }"""
-- Left (NonEmptyList (NonEmpty (ErrorAtProperty "trafficLight" (ForeignError "Failed to parse purple as TrafficLight")) Nil))