A value that knows how to decode CSV values.

The raw CSV data structure.

A structured error describing exactly how the decoder failed. You can use this to create more elaborate visualizations of a decoder problem. For example, you could show the entire CSV record and show the part causing the failure in red.

Kind determines what type a decoder expects. Used in combination with the Not error.

Decode a CSV string into an Elm String.

decodeString string "true" == Ok [ "true" ]


decodeString string "42" == Ok [ "42" ]


decodeString string "3.14" == Ok [ "3.14" ]


decodeString string "hello" == Ok [ "hello" ]

Decode a CSV number into an Elm Int.

decodeString int "true"  == Err ...
decodeString int "42"    == Ok [ 42 ]
decodeString int "3.14"  == Err ...
decodeString int "hello" == Err ...

Decode a CSV number into an Elm Float.

decodeString float "true"  == Err ..
decodeString float "42"    == Ok [ 42 ]
decodeString float "3.14"  == Ok [ 3.14 ]
decodeString float "hello" == Err ...

Decode a CSV boolean into an Elm Bool.

decodeString bool "true"  == Ok [ True ]
decodeString bool "42"    == Err ...
decodeString bool "3.14"  == Err ...
decodeString bool "hello" == Err ...

Decode the given Csv into a list of custom value by running Decoder on it. This will fail if any of the records can not be decoded by the Decoder for some reason.

Transform a decoder. Maybe you just want to know the length of a string:

import String


stringLength : Decoder Int
stringLength =
    map String.length string

It is often helpful to use map with oneOf, like when defining maybe:

maybe : Decoder a -> Decoder (Maybe a)
maybe decoder =
    oneOf
        [ map Just decoder
        , succeed Nothing
        ]

Try two decoders and then combine the result. We can use this to decode objects with many fields:

type alias Point =
    { x : Float, y : Float }


point : Decoder Point
point =
    map2 Point
        float
        float


-- decodeString point "3,4" == Ok { x = 3, y = 4 }

It tries each individual decoder and puts the result together with the Point constructor.

Try three decoders and then combine the result. We can use this to decode objects with many fields:

type alias Person =
    { name : String, age : Int, height : Float }


person : Decoder Person
person =
    map3 Person
        string
        int
        float


-- csv = "tom,42,1.8"
-- decodeString person csv == Ok { name = "tom", age = 42, height = 1.8 }

Like map2 it tries each decoder in order and then give the results to the Person constructor. That can be any function though!

Ignore the CSV and produce a certain Elm value.

decodeString (succeed 42) "true"  == Ok [ 42 ]
decodeString (succeed 42) "1,2,3" == Ok [ 42 ]
decodeString (succeed 42) "hello" == Ok [ 42 ]

This is handy when used with oneOf.

Ignore the CSV and make the decoder fail. This is handy when used with oneOf where you want to give a custom error message in some case.

Helpful for dealing with optional fields. Here are a few slightly different examples:

decodeString (maybe int) "42" == Ok [ Just 42 ]


decodeString (maybe int) ",42" == Ok [ Nothing ]

Try a bunch of different decoders. This can be useful if the CSV may come in a couple different formats. For example, say you want to read an array of numbers, but some of them are null.

import String


badInt : Decoder Int
badInt =
    oneOf [ int, null 0 ]


-- decodeString (list badInt) "[1,2,null,4]" == Ok [1,2,0,4]

Why would someone generate CSV like this? Questions like this are not good for your health. The point is that you can use oneOf to handle situations like this!