---
id: jambo
version: "0.1.7"
license: MIT
license_treatment: permissive
maintenance: aging
---

# jambo — Jambo - JSON Schema to Pydantic Converter

License: permissive · Maintenance: aging · Downloads: 488.1K/mo

## What it is and what it does

Jambo is a converter that takes JSON Schema definitions and generates Pydantic models from them automatically. It bridges the gap between schema-first design and Python type safety by eliminating manual model writing. The package supports a broad range of JSON Schema features including nested objects, references, unions (anyOf, oneOf, allOf), enums, and validation constraints like minLength, maxLength, pattern, minimum, and maximum.

It offers two APIs: a static convenience method for one-off conversions and an instance-based API with reference caching for scenarios where you need to reuse generated subtypes or manage schema namespaces. The package is designed for frameworks like LangChain and CrewAI that need to dynamically generate models at runtime, though it works for any use case requiring schema-driven validation.

Use it for:

- Generate Pydantic models from OpenAPI or JSON Schema specifications without manual model definition.
- Build dynamic validation layers in AI frameworks that accept arbitrary schema inputs from users or APIs.
- Convert third-party schema definitions into type-safe Python models for data processing pipelines.
- Reuse schema-derived subtypes across multiple converter instances using the reference cache.
- Enforce JSON Schema constraints (pattern, bounds, length limits) through Pydantic validation automatically.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Converts JSON Schema definitions into Pydantic models dynamically, handling validation constraints and complex schema features like references, unions, and enums.

Yes, with conditions. Install if you need dynamic schema-to-model conversion and can tolerate alpha-stage software. The package has no known vulnerabilities, permissive licensing, and reasonable download volume (488061 monthly). However, the 212-day gap since last release and alpha status mean you should verify stability for your use case and be prepared to maintain a fork if needed.

## Install

pip install jambo
uv add jambo
poetry add jambo

## Installing jambo

Before you install: High install friction due to three runtime dependencies (email-validator, jsonschema, pydantic). Package is in alpha status with aging maintenance signal—last release 212 days ago, though repository remains active and not archived.

License in practice: MIT license permits commercial and private use with minimal restrictions, making it suitable for most projects without licensing concerns.

Quickstart:

from jambo import SchemaConverter

schema = {
    "title": "Person",
    "type": "object",
    "properties": {"name": {"type": "string"}, "age": {"type": "integer"}},
    "required": ["name"],
}

Person = SchemaConverter.build(schema)
obj = Person(name="Alice", age=30)

Requires Python 3.10 or later; pydantic, jsonschema, and email-validator must be installed.

Verify before relying:

- Whether the package handles all JSON Schema draft versions or only specific ones
- Performance characteristics when converting large or deeply nested schemas
- Stability guarantees given alpha development status

## Package facts

- License: MIT (permissive)
- Python support: supports_current
- Install friction: high
- Maintenance: aging
- Downloads: 488.1K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

json schema to pydantic, dynamic pydantic model generation, schema validation converter, pydantic model builder, json schema validation, automatic model generation, schema-driven validation, schema-validation, pydantic-integration, dynamic-models

[View on SkillFed](https://skillfed.io/packages/jambo) · [View on PyPI](https://pypi.org/project/jambo/)