Convert JSON data structures into Pike language class definitions, simplifying data modeling and coding workflows.
JSON to CSV & CSV to JSON Converter
Convert seamlessly between JSON arrays and CSV tabular data. Ideal for data analysis and software development.
JSON to XML & XML to JSON Converter
A two-way conversion tool for JSON and XML data structures, designed for development, testing, and data processing.
JSON to C# Class Converter
Automatically convert JSON data into C# class definitions, ideal for .NET developers building data models.
JSON to YAML & YAML to JSON Converter
Bidirectionally convert between JSON and YAML structured data formats, with support for custom output styling.
JSON to Java POJO Generator
Automatically convert JSON strings into standard Java POJO class code for API integration, data modeling, and other development scenarios.
Manually writing Pike class definitions to map JSON data structures can be tedious and error-prone. This tool parses standard JSON input and automatically generates type-safe, well-structured Pike class code. JSON (JavaScript Object Notation) is a lightweight data-interchange format, while Pike classes define the member variables and type structures of data objects. The tool intelligently infers field types (such as string, int, array, or nested objects) based on JSON key-value pairs, outputting class definition code that can be directly embedded into your Pike projects.
Q: What JSON data type mappings does the tool support?
A: The tool maps JSON strings to string, numbers to int, booleans to bool, and arrays to array. Nested objects will generate independent classes.
Q: How are empty arrays or null values handled?
A: Empty arrays are inferred as the array type by default. Null values may not have their types accurately inferred, so it is recommended to check or manually adjust the generated code.
Please ensure the input is in a valid JSON format, otherwise parsing may fail. The generated types are based on value inference, so manual verification is required for complex scenarios. The tool does not store user data, but please avoid entering sensitive information. Extremely large JSON files may result in slower response times; we recommend processing them in chunks.
For fields with mixed types in JSON, it is recommended to preprocess the data to ensure type consistency before conversion. For example, if a number might contain decimals, the generated code needs to be manually adjusted from int to float. A typical input like {"name":"Alice","score":95} will output a class with string name; int score;.
