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JSON to Haskell Data Type Converter
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Automatically convert JSON data into Haskell data/newtype definitions. Generate Aeson-ready code instantly to boost your development efficiency.
Overview
Understand what the tool solves, how it works, and the boundaries of its data.
Paste a JSON value and the converter infers Haskell declarations from the structure it can see: objects, nested objects, arrays, and primitive values. JSON is a text format for structured data; an object contains named values, while an array contains an ordered sequence. The generated types are therefore a model of this example, not a complete contract for every response an API might return.
For instance, a sample such as {"name":"Riley","tags":["ops"]} gives the generator evidence for an object with a text field and a list-like field. The result is editable Haskell source. Use it to get a first pass at the shape of unfamiliar payloads, then compare every field with the real interface or data specification.
Guide
Follow the workflow and verify inputs and outputs with practical examples.
Include the opening and closing braces or brackets and use JSON quoting and separators. A lone object, array, or other valid JSON value can be used as an input sample.
Set the module name to match your project. Keep the default option for type definitions plus generated conversion code, or select the types-only option if you want declarations without converter code. You can also choose list-based arrays or vector-based arrays, and ordinary records instead of newtype wrappers.
As the input or settings change, review the generated source. Copy it or download the Haskell file, then check names, imports, types, and library dependencies in your project before using it.
Use cases
See how the tool fits into real work and everyday tasks.
A developer can paste a representative response to reveal nested records and repeated array structures, then compare that draft with the API’s documented required and optional fields.
A team can turn a sanitized test fixture into editable declarations, choose list or vector arrays to suit its conventions, and review the source together before adding it to the project.
Q&A
Find concise answers to common questions and confusing cases.
It only provides the values present in that sample. If a field may be missing or null in other responses, include representative examples where possible and inspect or adjust the resulting types to match the full data contract.
No library integration should be assumed from the output label alone. Inspect the generated source for the declarations and conversion code it actually contains, confirm the imports and package versions in your project, and compile it there.
The output is inferred from the current example. Changing a value or adding a nested object can change the inferred structure, so use representative samples and review the new output after each change.
Notes
Review scope, result limitations, and important precautions before use.
A sample cannot establish every allowed value, whether a key can be absent, the meaning of a number, or whether text represents a date or identifier. Review these decisions manually and compile the result with the target project’s compiler and dependencies. Avoid pasting credentials, personal records, or other sensitive production data; use a sanitized sample.
Related
Discover related tools, collections, and available API capabilities.