# Argonaut Core Documentation

This directory contains documentation for `argonaut-core`. If you are interested in contributing new documentation, please read the [contributor guidelines](../CONTRIBUTING.md) and [What Nobody Tells You About Documentation](https://documentation.divio.com) for help getting started.

## Tutorial

Some of Argonaut's functions might seem a bit arcane at first, so it can help to understand the underlying design decisions which make it the way it is.

One approach for modelling JSON values would be to define an algebraic data type, like this:

```purs
data Json
  = JNull
  | JString String
  | JNumber Number
  | JBoolean Boolean
  | JArray (Array Json)
  | JObject (Object Json)
```

And indeed, some might even say this is the obvious approach.

Because Argonaut is written with the compilation target of JavaScript in mind, it takes a slightly different approach, which is to reuse the existing data types which JavaScript already provides. This way, the result of JavaScript's `JSON.parse` function is already a `Json` value, and no extra processing is needed before you can start operating on it. This ought to help your program both in terms of speed and memory churn.

Much of the design of Argonaut follows naturally from this design decision.

### Introducing Json values

(Or, where do `Json` values come from?)

If your program is receiving JSON data as a string, you probably want the `jsonParser` function in `Data.Argonaut.Parser`, which is a very simple wrapper around JavaScript's `JSON.parse`.

Otherwise, `Json` values can be introduced into your program via the FFI or via the construction functions in `Data.Argonaut.Core`. Here are some examples:

```js
// In an FFI module.
exports.someNumber = 23.6;
exports.someBoolean = false;
exports.someObject = {
  people: [{ name: "john" }, { name: "jane" }],
  common_interests: [],
};
```

```purs
foreign import someNumber :: Json
foreign import someBoolean :: Json
foreign import someObject :: Json
```

Generally, if a JavaScript value could be returned from a call to `JSON.parse`, it's fine to import it from the FFI as `Json`. So, for example, objects, booleans, numbers, strings, and arrays are all fine, but functions are not.

The construction functions (that is, `fromX`, or `jsonX`) can be used as follows:

```purs
import Data.Tuple (Tuple(..))
import Foreign.Object as Object
import Data.Argonaut.Core as A

someNumber = A.fromNumber 23.6

someBoolean = A.fromBoolean false

someObject =
  A.fromObject
    ( Object.fromFoldable
        [ Tuple "people"
            ( A.fromArray
                [ A.jsonSingletonObject "name" (A.fromString "john")
                , A.jsonSingletonObject "name" (A.fromString "jane")
                ]
            )
        , Tuple "common_interests" A.jsonEmptyArray
        ]
    )
```

### Eliminating/matching on `Json` values

We can perform case analysis for `Json` values using the `caseJson` function. This function is necessary because `Json` is not an algebraic data type. If `Json` were an algebraic data type, we would not have as much need for this function, because we could perform pattern matching with a `case ... of` expression instead.

The type of `caseJson` is:

```purs
caseJson
  :: forall a
   . (Unit -> a)
  -> (Boolean -> a)
  -> (Number -> a)
  -> (String -> a)
  -> (Array Json -> a)
  -> (Object Json -> a)
  -> Json
  -> a
```

That is, `caseJson` takes six functions, which all must return values of some particular type `a`, together with one `Json` value. `caseJson` itself also returns a value of the same type `a`.

A use of `caseJson` is very similar to a `case ... of` expression, as it allows you to handle each of the six possibilities for the `Json` value you passed in. Thinking of it this way, each of the six function arguments is like one of the case alternatives.

The function that takes `Unit` as an argument is for matching `null` values. As there is only one possible `null` value, we use the PureScript `Unit` type, as correspondingly there is only one possible `Unit` value.

Just like in a `case ... of` expression, the final value that the whole expression evaluates to comes from evaluating exactly one of the 'alternatives' (functions) that you pass in. In fact, you can tell that this is the case just by looking at the type signature of `caseJson`, because of a property called _parametricity_ (although a deeper explanation of parametricity is outside the scope of this tutorial).

For example, imagine we had the following values defined in JavaScript and imported via the FFI:

```js
exports.anotherNumber = 0.0;
exports.anotherArray = [0.0, { foo: "bar" }, false];
exports.anotherObject = { foo: 1, bar: [2, 2] };
```

Then we can match on them in PureScript using `caseJson`:

```purs
foreign import anotherNumber :: Json
foreign import anotherArray :: Json
foreign import anotherObject :: Json

basicInfo :: Json -> String
basicInfo = caseJson
  (const "It was null")
  (\b -> "Got a boolean: " <> if b then "it was true!" else "It was false.")
  (\x -> "Got a number: " <> show x)
  (\s -> "Got a string, which was " <> Data.String.length s <> " characters long.")
  (\xs -> "Got an array, which had " <> Data.Array.length xs <> " items.")
  (\obj -> "Got an object, which had " <> Foreign.Object.size obj <> " items.")
```

```purs
basicInfo anotherNumber -- => "Got a number: 0.0"
basicInfo anotherArray  -- => "Got an array, which had 3 items."
basicInfo anotherObject -- => "Got an object, which had 2 items."
```

`caseJson` is the fundamental function for pattern matching on `Json` values; any kind of pattern matching you might want to do can be done with `caseJson`.

However, `caseJson` is not always comfortable to use, so Argonaut provides a few other simpler versions for convenience. For example, the `caseJsonX` functions can be used to match on a specific type. The first argument acts as a default value, to be used if the `Json` value turned out not to be that type. For example, we can write a function which tests whether a JSON value is the string "lol" like this:

```purs
caseJsonString :: forall a. a -> (String -> a) -> Json -> a

isJsonLol = caseJsonString false (_ == "lol")
```

If the `Json` value is not a string, the default `false` is used. Otherwise, we test whether the string is equal to "lol".

The `toX` functions also occupy a similar role: they attempt to convert `Json` values into a specific type. If the json value you provide is of the right type, you'll get a `Just` value. Otherwise, you'll get `Nothing`. For example, we could have written `isJsonLol` like this, too:

```purs
toString :: Json -> Maybe String

isJsonLol json =
  case toString json of
    Just str -> str == "lol"
    Nothing  -> false
```