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JSON to Elm

Generate Elm classes/structs automatically from a JSON object.

100% Client-Side Local Execution
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What is JSON to Elm?

This free online tool turns a sample JSON payload into a ready-to-use type alias with a JSON decoder for Elm, so you can use this json to elm decoder generator tool to go straight from raw JSON to a typed type alias and decoder without writing the boilerplate yourself. It is built around Elm's actual idiom — a Elm decoder — rather than a generic one-size-fits-all class, and pairs naturally with elm/json's Json.Decode module for real-world (de)serialization. Use it for json to elm type online or any time you need elm json decoder generator, whether you're scaffolding a new Elm project or mapping an existing API response.

Technical Execution

Paste or upload a sample JSON object or array and the tool walks its structure field by field, inferring a concrete Elm type for each value — mapping basic JSON types to `String`, `Int`/`Float`, and `Bool` as appropriate. For nested data, it emits a separate type alias and matching decoder function for every nested JSON object, and types arrays as `List T` decoded with `Json.Decode.list`. On the naming side, it preserves the original JSON key names inside the generated `Json.Decode.field "originalKey"` calls, while the Elm record fields themselves follow Elm's camelCase convention. For optional data, fields seen as `null`, or missing from some sample objects, are typed as `Maybe T` and decoded with `Json.Decode.maybe` (or `Json.Decode.Pipeline.optional`), matching Elm's requirement that every possible absence be represented in the type.

Zero Data Storage Guarantee

Everything runs client-side in your browser: the sample JSON you paste in — which may contain real field names, endpoint shapes, or structure from a private API or project — is parsed and converted entirely on your device and is never uploaded to any server. Nothing you enter is logged, stored, or transmitted anywhere, so you can safely paste a real payload from an internal or unreleased API to generate an accurate Elm decoder. Closing or refreshing the tab clears everything, since no copy of your data ever left your machine in the first place.

How to Use JSON to Elm (Step-by-Step Guide)

  1. Copy a representative sample of your JSON (the more fields and nested objects it includes, the more complete the generated type alias and decoder will be).
  2. Paste it into the input panel of the JSON to Elm tool, or click "Upload" to load it from a json file.
  3. Review the auto-detected root name, and rename it if you want the generated Elm decoder to use a specific class or type name instead of the default.
  4. Click "Generate" to produce the Elm type alias and decoder, which appears instantly in the output panel with syntax highlighting.
  5. Click "Copy" to copy the generated code to your clipboard, or "Download" to save it as a `.elm` file.
  6. Paste the result into your Elm project and adjust field names or types if your data has edge cases the sample didn't cover.

Frequently Asked Questions (FAQ)

Q: How does this tool handle nested objects and arrays when converting JSON to Elm?
A: The tool emits a separate type alias and matching decoder function for every nested JSON object, and types arrays as `List T` decoded with `Json.Decode.list` That keeps the generated code organized the way a Elm developer would structure it by hand, instead of flattening everything into one giant type alias and decoder.
Q: What happens to fields that are nullable or missing from some records?
A: For optional data, fields seen as `null`, or missing from some sample objects, are typed as `Maybe T` and decoded with `Json.Decode.maybe` (or `Json.Decode.Pipeline.optional`), matching Elm's requirement that every possible absence be represented in the type. If your sample only has one example object, fields that could be null in other records might not be detected as optional — paste a few varied samples (or an array of objects) for the most accurate result.
Q: Is this better than writing the type alias and decoder by hand?
A: For anything beyond a trivial, flat payload, yes — hand-writing Elm decoders for a nested JSON payload is notoriously verbose, since every field needs its own `Json.Decode.field` call chained through `andThen` or the pipeline operators, and one mismatch fails to compile until you track it down. The generator produces the same result in seconds and gives you a correct starting point to refine, rather than a blank page.
Q: Is my JSON data safe to paste into this tool, especially if it's from a private API?
A: Yes. Everything runs client-side in your browser: the sample JSON you paste in — which may contain real field names, endpoint shapes, or structure from a private API or project — is parsed and converted entirely on your device and is never uploaded to any server. Nothing you enter is logged, stored, or transmitted anywhere, so you can safely paste a real payload from an internal or unreleased API to generate an accurate Elm decoder. Closing or refreshing the tab clears everything, since no copy of your data ever left your machine in the first place.
Q: Can I use this as a convert json to elm decoder?
A: Yes — the tool is commonly used as a convert json to elm decoder, and works the same way whether you're converting a one-off response for a prototype or generating model code for a production project.
Q: Does the tool rename fields to match Elm naming conventions?
A: Yes. It preserves the original JSON key names inside the generated `Json.Decode.field "originalKey"` calls, while the Elm record fields themselves follow Elm's camelCase convention, so the generated code reads naturally in Elm while still deserializing the original JSON correctly.
Q: What Elm library does the generated code work with?
A: The output is written to pair cleanly with elm/json's Json.Decode module, the most common choice for Elm developers handling JSON, so you can drop it into an existing project without changing your serialization setup.
Q: Does this tool work for deeply nested or large JSON samples?
A: Yes. The tool recurses through every level of nesting it finds and generates a complete set of linked type alias and decoder definitions, not just the top level — though for very large samples, trimming it down to one representative record per array is usually enough to get an accurate result.
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