logicpearl 0.1.5

Official Python bindings for logicpearl-engine.

logicpearl

Official Python bindings for logicpearl-engine.

Use this package when:

• Python code needs to execute a pearl artifact or pipeline directly
• you want a real bridge to the Rust execution surface
• you do not want to shell out to the CLI for every request

Do not use it as a reason to bake observers into pearls. The intended split is still:

• observer/plugin: messy input interpretation
• pearl: deterministic policy artifact
• verify/response: operational interpretation

Example

from logicpearl import LogicPearlEngine

engine = LogicPearlEngine.from_artifact_path("/path/to/logicpearl-bundle")
result = engine.evaluate({
    "age": 34,
    "member": True,
    "country": "US",
})

print(result["decision_kind"])
print(result["allow"])

For pipeline execution, use LogicPearlEngine.from_pipeline_path("/path/to/pipeline.json"). The installed Python package does not bundle the repository examples under examples/.

Scope

This package exposes local execution through logicpearl-engine.

It is:

• a local evaluation library, not a service client
• not a reimplementation of runtime semantics in Python
• not a wrapper around logicpearl CLI subprocess calls

API Shape

LogicPearlEngine.from_path(path) loads an artifact or pipeline once. Reuse the engine object for request-time evaluation.

• evaluate(input) returns the runtime result payload directly. For gate and action artifacts, this matches logicpearl run --json.
• evaluate_batch(inputs) returns a list of runtime result payloads.
• run(input) returns the full engine envelope with the artifact kind included.
• run_single(input) and run_batch(inputs) expose the same envelope shape for callers that need dispatch metadata.

Inputs must be JSON-compatible Python values: dict, list, tuple, str, int, float, bool, or None. Evaluation runs in Rust without spawning the CLI.