JSON to Pydantic Model Generator

Code Generators

Generate Python Pydantic v2 BaseModel classes from JSON. Nested models, Optional fields, list[...] and dict[...] hints, aliases via Field — copy-paste ready Python code.

100% Client-Side — Your data never leaves your browser.
Model name
Options
Nullable keys become Optional[...] = None; nested objects become separate models.
JSON Input
Pydantic v2 Output

Paste a JSON payload (or click "Load Sample") to generate Pydantic v2 BaseModel classes.

JSON to C# Class Generator

Generate strongly-typed C# classes from JSON instantly. Nested objects, List<T>, DateTime, nullable types, JsonPropertyName attributes and PascalCase options — copy ready-to-use code.

Code Generators

JSON to YAML Converter

Convert JSON to clean, readable YAML instantly. Choose 2 or 4 space indentation, validate JSON in real time, then copy or download — nothing ever leaves your browser.

Data Converters

JSON to CSV Converter

Convert JSON arrays or objects to CSV instantly. Nested objects are flattened into dot notation, arrays kept as clean JSON cells, with live preview and one-click .csv download.

Data Converters

JSON to Excel Converter

Turn JSON arrays into real .xlsx spreadsheets in seconds. Auto-sized columns, a live spreadsheet preview, plus one-click Excel and PDF table export — 100% local and free.

Data Converters

How to Use

Three steps from raw data to finished output — no account required.

  1. 1

    Paste the JSON payload (API response, form data or database row) into the input pane.

  2. 2

    Set your model name — nested objects become separate BaseModel classes automatically.

  3. 3

    Copy the Pydantic v2 code, including Optional fields and Field aliases, into your Python project.

Frequently Asked Questions

Everything you need to know about the json to pydantic model generator.

Yes. It emits modern Pydantic v2 code with lowercase generics such as list[str] and dict[str, Any], Optional[X] = None for nullable keys, Field(default_factory=...) for mutable defaults and Field(alias=...) for non-identifier keys.

A key that is null anywhere in the payload — or missing from some records in an array — becomes Optional[T] = None, so the model validates the sample data without rejecting absent or null fields at runtime.

Yes. Every nested object becomes its own BaseModel class, referenced by type, and duplicate structures reuse a single class. Primitive arrays become list[int], list[str] and similar annotations, while mixed arrays fall back to list[Any].

Yes. Keys such as user-id are sanitized to valid identifiers like user_id and a Field(alias="user-id") is added automatically, so model_validate() still accepts the original JSON keys unchanged.