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Automatically convert JSON data into Haskell data/newtype definitions. Generate Aeson-ready code instantly to boost your development efficiency.
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Automatically convert JSON data into C# class definitions, ideal for .NET developers building data models.
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When processing JSON data returned by APIs, manually writing the corresponding Haskell data type definitions is both tedious and error-prone. This tool directly parses your input JSON string, recursively analyzes its key-value structure, and automatically generates complete Haskell data type code. This includes data or newtype declarations, field definitions, and necessary deriving clauses, enabling you to immediately use the Aeson library for serialization and deserialization in your projects.
Q: How does the generated code handle camelCase field names in JSON?
A: The tool attempts to convert common JSON naming conventions (like camelCase and snake_case) into identifiers that conform to Haskell naming idioms. Typically, it capitalizes the first letter of the field name to use as a record selector.
Q: What type are numbers converted to by default when converting JSON to Haskell?
A: They are inferred as Int by default. This is the most commonly used type for handling integers in Haskell, but you may need to manually adjust it to Integer or Scientific depending on your numerical range.
Please ensure that the input JSON format is completely valid; any syntax errors will cause the parsing to fail. The code generated by the tool includes a module declaration (e.g., module MyTypes where), and you may need to modify the module name according to your project structure. For optional fields (keys that might be null or missing in the JSON), the generated Haskell record fields will be non-Maybe types. You will need to manually change them to Maybe types based on your business logic to ensure safety.
For scenarios requiring high-precision numbers or large integers, it is recommended to manually replace the automatically inferred Int or Double types with Scientific (from the scientific package) or Integer to prevent precision loss or overflow. A typical input/output example: Inputting the JSON {"name": "Alice", "age": 30, "active": true} will generate code similar to data Person = Person { personName :: String, personAge :: Int, personActive :: Bool } deriving (Show, Generic, FromJSON, ToJSON). After integration, we recommend writing custom FromJSON/ToJSON instances for critical data types to handle more complex parsing logic or validation rules.
