pydantic-function-models 0.1.11

Migrating v1 Pydantic ValidatedFunction to v2.

Pydantic Function Models

A library to model Python function signatures using Pydantic, inspired by the now-deprecated ValidatedFunction from Pydantic v1. This package helps validate function arguments according to type hints, bridging the gap between Pydantic v1 and v2.

Installation

pip install pydantic-function-models

Features

• Signature modelling: Wrap any Python function to model its signature (positional, keyword, etc.) using Pydantic. Note that if you are after just validation (whether the arguments are valid) then you want validate call
• Painless migration from Pydantic v1: Provides a ValidatedFunction class ported to v2, for those who relied on ValidatedFunction in v1.
• Clear error messages: Raises Pydantic ValidationError with helpful details if input arguments do not match the declared types.
• Reserved name checks: Prevents usage of special parameter names (e.g., v__args, v__kwargs) that could conflict with internal validation logic.

Usage

Below is a general overview of how to use pydantic-function-models in your own code. There is no built-in command-line interface; usage is purely through Python imports.

Command-Line Interface

This library does not provide a CLI. All functionality is accessed by importing and using its classes in Python code. The remaining “Examples” section demonstrates typical usage patterns.

Example: Basic Validated Function

from pydantic_function_models import ValidatedFunction

def add(a: int, b: int) -> int:
    return a + b

vf = ValidatedFunction(add)

# Build arguments for validation
args_to_validate = (1,)
kwargs_to_validate = {"b": 2}

validated = vf.model.model_validate({
    "a": args_to_validate[0],
    "b": kwargs_to_validate["b"]
})
result = add(**validated.model_dump(exclude_unset=True))

print(result)  # 3

Here, ValidatedFunction creates an internal Pydantic model that enforces integer values for a and b. If you passed a string for a or b, it would raise a ValidationError.

Library Usage

Internally, each ValidatedFunction builds a Pydantic model representing the function’s signature. When you call .model.model_validate(...) or .build_values(...), it validates the provided arguments (whether positional or keyword-based) against the signature.

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Project Structure

Take a look at the internals here:

• validated_function.py: Core logic for ValidatedFunction, which encapsulates argument validation and Pydantic model generation.
• parameters.py: Model definitions for function parameters/signatures, with checks for reserved argument names.

Contributing

Maintained by lmmx. Contributions are welcome!

1. Issues & Discussions: Please open a GitHub issue or discussion for bugs, feature requests, or questions.
2. Pull Requests: PRs are welcome!
   • Install the dev extra (e.g. with uv: uv pip install -e .[dev])
   • Run tests (e.g. pytest) and include updates to docs or examples if relevant.
   • If reporting a bug, please include the version and error message/traceback if available.

License

This project is licensed under the MIT License.