To complete the missing encoders, we can follow a test-driven development (TDD) approach by writing the test cases first and then implementing the encoders to make the tests pass.
To create the appropriate encoder for the pageDecoder in Wiki.elm, you'll need to update the test code in WikiSpec.elm to include a test case for the pageEncoder.
Here are the necessary changes: (ChatGPT May 24 Version)
1. In WikiSpec.elm, import the Json.Encode module:
import Json.Encode as Encode
2. Add the following test case for the pageEncoder encoder:
[ test "Future" <| \() -> let page = Page -- TITLE "Create New Page Test" -- STORY [ Future { id = "b8a8a898990b9b70" , type_ = "future" , text = "We could not find this page." , title = "Create New Page Test" } ] -- JOURNAL [] expectedJson = rawData encoded = Encode.encode 2 (pageEncoder page) in Expect.equal encoded expectedJson ]
3. In Wiki.elm, add the following encoder for pageEncoder:
import Json.Encode as Encode -- ... pageEncoder : Page -> Encode.Value pageEncoder page = Encode.object [ ( "title", Encode.string page.title ) , ( "story", Encode.list storyEncoder page.story ) , ( "journal", Encode.list journalEncoder page.journal ) ] -- ...
The pageEncoder and related encoder functions are implemented to match the expected output of the pageDecoder.
Please note that the encoder functions are implemented based on the assumption of the corresponding types and field names used in the Wiki module. Make sure to adjust them accordingly if there are any differences.
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⇒ test(WikiSpec): RED add encoder. commit 
Note the pattern in storyEncoder:
storyEncoder : Story -> Encode.Value storyEncoder story = case story of NonEmptyStory alias -> Encode.object [ ( "type", Encode.string alias.type_ ) , ( "id", Encode.string alias.id ) , ( "text", Encode.string alias.text ) ] -- Add encoders for other story variants as needed _ -> Encode.null
In the case expression, the story value is matched against different patterns. Each pattern corresponds to a specific variant of the Story type.
The pattern NonEmptyStory alias is used to match the NonEmptyStory variant and bind the record value to the alias variable. This pattern effectively deconstructs the NonEmptyStory variant and allows access to its fields.
Inside the body of the case expression for the NonEmptyStory pattern, you can see that the alias record is used to extract the type_, id, and text fields. These fields are then encoded as key-value pairs in a JSON object using Encode.object. The type_ field is encoded as "type", and the corresponding value is encoded as Encode.string alias.type_. Similarly, the id field is encoded as "id" and alias.id, and the text field is encoded as "text" and alias.text.
By using the pattern match NonEmptyStory alias and accessing the fields of the alias record, you can easily extract and encode the values associated with the NonEmptyStory variant.
It's worth noting that this pattern matching technique is possible in Elm because variant types (like Story) are constructed using Algebraic Data Types, and pattern matching allows you to handle each variant differently based on its structure. (ChatGPT May 24 Version)
⇒ test(WikiSpec, Future): GREEN commit