Registry / serialization / jsonschema-pydantic-converter

jsonschema-pydantic-converter

library0.4.0pypypi✓ verified 83d ago

This library dynamically converts JSON Schema definitions into Pydantic models at runtime. It currently supports both Pydantic v1 and v2. The latest version is 0.4.0, with development actively progressing through minor releases.

serialization

pip install jsonschema-pydantic-converter

github ↗package ↗

INSTALL

IMPORT

SIG · JSONSCHEMA-PYDANTI

jsonschema-pydantic-converter

serializationpythonv0.4.0

Install

3.0s avg

Import

—

Disk

26MB

Pass rate

8/ 10

Env Coverage8 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v0.4.0 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

glibc

py 3.10

✓ —

✓ 3.83s

py 3.11

✓ —

✓ 3s

py 3.12

✓ —

✓ 2.55s

py 3.13

✓ —

✓ 2.65s

py 3.9

✕ build_error

26MB installed

● package 26MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

create_type_adapter

✓ from jsonschema_pydantic_converter import create_type_adapter

✗ from jsonschema_pydantic.builder import build_pydantic_model

transform

✓ from jsonschema_pydantic_converter import transform

transform_with_modules

✓ from jsonschema_pydantic_converter import transform_with_modules

This quickstart demonstrates how to define a simple JSON Schema, use `build_pydantic_model` to generate a Pydantic model dynamically, and then instantiate and validate data against the newly created model. It also shows an example of a validation failure.

from jsonschema_pydantic.builder import build_pydantic_model # Define a JSON Schema schema = { "title": "User", "type": "object", "properties": { "name": {"type": "string", "minLength": 1}, "age": {"type": "integer", "minimum": 0, "maximum": 150}, "email": {"type": "string", "format": "email"} }, "required": ["name", "age"] } # Build the Pydantic model from the schema UserModel = build_pydantic_model(schema_data=schema) # Instantiate and use the generated model try: user_data = UserModel(name="Alice", age=30, email="alice@example.com") print("Valid user data:") print(user_data.model_dump_json(indent=2)) except Exception as e: print(f"Error creating valid user: {e}") # Demonstrate validation failure try: invalid_user_data = UserModel(name="", age=-5) print("Invalid user data (should not reach here):", invalid_user_data) except Exception as e: print("\nValidation error for invalid user data:") print(e)

Debug

Known issues

gotchaWhile the library supports both Pydantic v1 and v2, the behavior of the *generated* models (e.g., method names like `.dict()` vs `.model_dump()`, specific validator implementations) can differ. Ensure your application's Pydantic version aligns with the expected model behavior.

fix

Always test generated models with your target Pydantic version. For Pydantic v1, use `.dict()` and `.json()`. For Pydantic v2, use `.model_dump()` and `.model_dump_json()`.

affects: All versions

gotchaThe library relies on well-formed and compliant JSON Schema definitions. Malformed schemas, unsupported keywords, or custom extensions not handled by the library can lead to conversion errors or unexpected Pydantic model structures.

fix

Validate your JSON Schema externally (e.g., using `jsonschema.validate`) before passing it to `build_pydantic_model`. Refer to the official JSON Schema specification for valid syntax and keywords.

affects: All versions

gotchaSchemas with deeply nested or complex `$ref` references, especially those involving circular dependencies or external files, might encounter resolution issues or performance degradation.

fix

Simplify complex `$ref` structures where possible. Ensure all referenced schemas are accessible and well-defined. For external `$ref`s, ensure the converter's environment can resolve them (though current versions focus on in-schema refs).

affects: All versions

Upgrade

Version history

0.4.0latest on PyPI · released Mar 25, 2026

Audit

Dependencies

pydanticrequiredCore dependency for generating and validating models.

jsonschemarequiredCore dependency for parsing and validating JSON schemas.

Agent activity

2 hits · last 30 days

node

Resources

githubhttps://github.com/akshaylive/jsonschema-pydantic-converter ↗

packagehttps://pypi.org/project/jsonschema-pydantic-converter/ ↗