haive.core.graph.common.references

Reference classes for serializing callables and types.

Classes

CallableReference	Serializable reference to a callable.
TypeReference	Reference to a type that can be serialized.

Module Contents

class haive.core.graph.common.references.CallableReference(/, **data)

Bases: pydantic.BaseModel

Serializable reference to a callable.

This class can store and resolve references to: - Module-level functions - Lambda functions - Methods - Partial functions - Directly passed callables

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Parameters:

data (Any)

classmethod from_callable(callable_obj)

Create reference from a callable.

Parameters:

callable_obj (collections.abc.Callable)

Return type:

Optional[CallableReference]

resolve()

Resolve reference to a callable.

Priority: 1. Direct function reference if available 2. Module/name resolution for regular functions 3. Source code evaluation for lambdas 4. Partial function reconstruction

Return type:

collections.abc.Callable | None

model_config

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class haive.core.graph.common.references.TypeReference(/, **data)

Bases: pydantic.BaseModel

Reference to a type that can be serialized.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Parameters:

data (Any)

classmethod from_type(type_obj)

Create a TypeReference from a type object.

Parameters:

type_obj (type | None)

Return type:

Optional[TypeReference]

resolve()

Resolve the reference back to a type.

Return type:

type | None

model_config

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].