aeson-schemas: Easily consume JSON data on-demand with type-safety

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Parse JSON data easily and safely without defining new data types. Useful for deeply nested JSON data, which is difficult to parse using the default FromJSON instances.


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Versions1.0.0, 1.0.0, 1.0.1, 1.0.2, 1.0.3
Change logCHANGELOG.md
Dependenciesaeson (>=1.1.2.0 && <1.5), base (>=4.9 && <5), bytestring (>=0.10.8.1 && <0.11), first-class-families (>=0.3.0.0 && <0.6), megaparsec (>=6.0.0 && <7.1), template-haskell (>=2.12.0.0 && <2.15), text (>=1.2.2.2 && <1.3), unordered-containers (>=0.2.8.0 && <0.3) [details]
LicenseBSD-3-Clause
AuthorBrandon Chinn <brandon@leapyear.io>
MaintainerBrandon Chinn <brandon@leapyear.io>
CategoryJSON
Home pagehttps://github.com/LeapYear/aeson-schemas#readme
Bug trackerhttps://github.com/LeapYear/aeson-schemas/issues
Source repositoryhead: git clone https://github.com/LeapYear/aeson-schemas
UploadedThu Sep 19 18:56:38 UTC 2019 by leapyear

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Readme for aeson-schemas-1.0.0

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aeson-schemas

A library that extracts information from JSON input using type-level schemas and quasiquoters, consuming JSON data in a type-safe manner. Better than aeson for decoding nested JSON data that would be cumbersome to represent as Haskell ADTs.

Quickstart

{-# LANGUAGE DataKinds #-}
{-# LANGUAGE QuasiQuotes #-}

import Data.Aeson (eitherDecodeFileStrict)
import Data.Aeson.Schema
import qualified Data.Text as T

-- First, define the schema of the JSON data
type MySchema = [schema|
  {
    users: List {
      id: Int,
      name: Text,
      age: Maybe Int,
      enabled: Bool,
      groups: Maybe List {
        id: Int,
        name: Text,
      },
    },
  }
|]

main :: IO ()
main = do
  -- Then, load data from a file
  obj <- either fail return =<<
    eitherDecodeFileStrict "examples/input.json" :: IO (Object MySchema)

  -- print all the users' ids
  print [get| obj.users[].id |]

  flip mapM_ [get| obj.users |] $ \user -> do
    -- for each user, print out some information
    putStrLn $ "Details for user #" ++ show [get| user.id |] ++ ":"
    putStrLn $ "* Name: " ++ T.unpack [get| user.name |]
    putStrLn $ "* Age: " ++ maybe "N/A" show [get| user.age |]
    case [get| user.groups |] of
      Nothing -> putStrLn "* No groups"
      Just groups -> putStrLn $ "* Groups: " ++ show groups

Features

Type safe

Since schemas are defined at the type level, parsing JSON objects is checked at compile-time:

-- using schema from above
>>> [get| obj.users[].isEnabled |]

<interactive>:1:6: error:
    • Key 'isEnabled' does not exist in the following schema:
      '[ '("id", 'Data.Aeson.Schema.SchemaInt),
         '("name", 'Data.Aeson.Schema.SchemaText),
         '("age",
           'Data.Aeson.Schema.SchemaMaybe 'Data.Aeson.Schema.SchemaInt),
         '("enabled", 'Data.Aeson.Schema.SchemaBool),
         '("groups",
           'Data.Aeson.Schema.SchemaMaybe
             ('Data.Aeson.Schema.SchemaList
                ('Data.Aeson.Schema.SchemaObject
                   '[ '("id", 'Data.Aeson.Schema.SchemaInt),
                      '("name", 'Data.Aeson.Schema.SchemaText)])))]
    • In the second argument of ‘(.)’, namely ‘getKey @"isEnabled"’
      In the first argument of ‘(<$:>)’, namely
        ‘(id . getKey @"isEnabled")’
      In the first argument of ‘(.)’, namely
        ‘((id . getKey @"isEnabled") <$:>)’

Point-free definitions

You can also use the get quasiquoter to define a pointfree function:

getNames :: Object MySchema -> [Text]
getNames = [get| .users[].name |]

You can use the unwrap quasiquoter to define intermediate schemas:

type User = [unwrap| MySchema.users[] |]

getUsers :: Object MySchema -> [User]
getUsers = [get| .users[] |]

groupNames :: User -> Maybe [Text]
groupNames = [get| .groups?[].name |]

Advantages over aeson

JSON keys that are invalid Haskell field names

aeson does a really good job of encoding and decoding JSON data into Haskell values. Most of the time, however, you don't deal with encoding/decoding data types manually, you would derive Generic and automatically derive FromJSON. In this case, you would match the constructor field names with the keys in the JSON data. The problem is that sometimes, JSON data just isn't suited for being defined as Haskell ADTs. For example, take the following JSON data:

{
    "id": 1,
    "type": "admin",
    "DOB": "5/23/90"
}

The FromJSON instance for this data is not able to be automatically generated from Generic because the keys are not valid/ideal field names in Haskell:

data Result = Result
  { id :: Int
    -- ^ `id` shadows `Prelude.id`
  , type :: String
    -- ^ `type` is a reserved keyword
  , DOB :: String
    -- ^ fields can't start with an uppercase letter
  } deriving (Generic, FromJSON)

The only option is to manually define FromJSON -- not a bad option, but less than ideal.

With this library, you don't have these limitations:

type Result = [schema|
  {
    id: Int,
    type: Text,
    DOB: Text,
  }
|]

Nested data

What about nested data? If we wanted to represent nested JSON data as Haskell data types, you would need to define a Haskell data type for each level.

{
    "permissions": [
        {
            "resource": {
                "name": "secretdata.txt",
                "owner": {
                    "username": "john@example.com"
                }
            },
            "access": "READ"
        }
    ]
}
data Result = Result
  { permissions :: [Permission]
  }
  deriving (Generic, FromJSON)

data Permission = Permission
  { resource :: Resource
  , access :: String
  } deriving (Generic, FromJSON)

data Resource = Resource
  { name :: String
  , owner :: Owner
  } deriving (Generic, FromJSON)

data Owner = Owner
  { username :: String
  }

It might be fine for a single example like this, but if you have to parse this kind of data often, it'll quickly become cumbersome defining multiple data types for each JSON schema. Additionally, the namespace becomes more polluted with each data type. For example, if you imported all four of these data types, you wouldn't be able to use name, username, resource, etc. as variable names, which can become a pain.

Compared with this library:

type Result = [schema|
  {
    permissions: List {
      resource: {
        name: Text,
        owner: {
          username: Text,
        },
      },
      access: Text,
    }
  }
|]

The only identifier added to the namespace is Result, and parsing out data is easier and more readable:

-- without aeson-schemas
map (username . owner . resource) . permissions

-- with aeson-schemas
[get| result.permissions[].resource.owner.username |]

Duplicate JSON keys

Maybe you have nested data with JSON keys reused:

{
    "_type": "user",
    "node": {
        "name": "John",
        "groups": [
            {
                "_type": "group",
                "node": {
                    "name": "Admin",
                    "writeAccess": true
                }
            }
        ]
    }
}

This might be represented as:

data UserNode = UserNode
  { _type :: String
  , node :: User
  }

data User = User
  { name :: String
  , groups :: [GroupNode]
  }

data GroupNode = GroupNode
  { _type :: String
  , node :: Group
  }

data Group = Group
  { name :: String
  , writeAccess :: Bool
  }

Here, _type, name, and node are repeated. This works with {-# LANGUAGE DuplicateRecordFields #-}, but you wouldn't be able to use the accessor function anymore:

>>> node userNode

<interactive>:1:1: error:
    Ambiguous occurrence 'node'
    It could refer to either the field 'node',
                             defined at MyModule.hs:3:5
                          or the field 'node', defined at MyModule.hs:13:5

So you'd have to pattern match out the data you want:

let UserNode{node = User{groups = userGroups}} = userNode
    groupNames = map (\GroupNode{node = Group{name = name}} -> name) userGroups

With this library, parsing is much more straightforward

let groupNames = [get| userNode.node.groups[].node.name |]