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JSON to Haskell

Generate Haskell classes/structs automatically from a JSON object.

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

This free online tool turns a sample JSON payload into a ready-to-use data type (record) for Haskell, so you can use this json to haskell data type generator tool to go straight from raw JSON to a typed data type / record without writing the boilerplate yourself. It is built around Haskell's actual idiom — a Haskell record — rather than a generic one-size-fits-all class, and pairs naturally with Aeson for real-world (de)serialization. Use it for json to haskell record online or any time you need aeson json to haskell type, whether you're scaffolding a new Haskell 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 Haskell type for each value — mapping basic JSON types to `Text`/`String`, `Int`/`Double`, and `Bool` as appropriate. For nested data, it defines a separate record data type with its own `FromJSON` instance for every nested JSON object, and types arrays as `[T]` using Haskell's native list syntax. On the naming side, it converts snake_case or camelCase JSON keys into Haskell's camelCase record-field convention (often prefixed to avoid field-name clashes between records), and generates the matching `FromJSON`/`ToJSON` instances via Aeson's `Options` so the original key is preserved on the wire. For optional data, fields observed as `null`, or missing from some sample objects, are typed as `Maybe T`, and the generated `FromJSON` instance uses `.:?` instead of `.:` so Aeson parses a missing key as `Nothing` rather than failing.

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 Haskell record. 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 Haskell (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 data type / record will be).
  2. Paste it into the input panel of the JSON to Haskell 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 Haskell record to use a specific class or type name instead of the default.
  4. Click "Generate" to produce the Haskell data type / record, 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 `.hs` file.
  6. Paste the result into your Haskell 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 Haskell?
A: The tool defines a separate record data type with its own `FromJSON` instance for every nested JSON object, and types arrays as `[T]` using Haskell's native list syntax That keeps the generated code organized the way a Haskell developer would structure it by hand, instead of flattening everything into one giant data type / record.
Q: What happens to fields that are nullable or missing from some records?
A: For optional data, fields observed as `null`, or missing from some sample objects, are typed as `Maybe T`, and the generated `FromJSON` instance uses `.:?` instead of `.:` so Aeson parses a missing key as `Nothing` rather than failing. 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 data type / record by hand?
A: For anything beyond a trivial, flat payload, yes — hand-writing Aeson `FromJSON` instances for a nested record is verbose and strict about types, so a single mismatched field will fail to compile, which a generator catches for you upfront by inferring it correctly from the sample. 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 Haskell record. 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 haskell type?
A: Yes — the tool is commonly used as a convert json to haskell type, 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 Haskell naming conventions?
A: Yes. It converts snake_case or camelCase JSON keys into Haskell's camelCase record-field convention (often prefixed to avoid field-name clashes between records), and generates the matching `FromJSON`/`ToJSON` instances via Aeson's `Options` so the original key is preserved on the wire, so the generated code reads naturally in Haskell while still deserializing the original JSON correctly.
Q: What Haskell library does the generated code work with?
A: The output is written to pair cleanly with Aeson, the most common choice for Haskell 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 data type / record 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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