Bounded Models
[!WARNING] This project is in early development. The API may change significantly.
A framework to check if Pydantic models are "bounded" and enable uniform sampling from constrained spaces.
Installation
pip install bounded-models
# or
uv add bounded-models
Quick Start
from typing import Literal
from bounded_models import FieldHandlerRegistry
from pydantic import BaseModel, Field
class Config(BaseModel):
mode: Literal["fast", "slow"]
threshold: float = Field(ge=0.0, le=1.0)
count: int = Field(ge=1, le=10)
registry = FieldHandlerRegistry.default()
registry.check_model_boundedness(Config) # True
registry.model_dimensions(Config) # 3
# Sample from unit hypercube [0, 1]^dim
registry.sample_model([0.5, 0.5, 0.5], Config)
# Config(mode='slow', threshold=0.5, count=5)
Supported Field Types
| Type | Example |
|---|---|
Numeric (int, float) |
Field(ge=0, le=10) |
Literal |
Literal["a", "b", "c"] |
Enum |
class Color(Enum): ... |
Nested BaseModel |
BoundedModel subclasses |
Documentation
For detailed usage, see the documentation.
License
MIT
1 maintainer
Metadata
1 maintainer
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