Berliant
Berliant is a Python library for discovering stochastic failure-inducing capability interactions.
Status
Berliant is currently an early-stage research-oriented Python library.
Current version: 0.1.0
Requirements
- Python 3.10 or newer
uvis recommended for development
Quickstart
Berliant exposes its primary API directly from the package root.
from berliant import KeyedSimulator, load_scenario, validated_scif
scenario = load_scenario(
"benchmarks/bsib_01/mixed/BSIB-MIXED-001.yaml"
)
simulator = KeyedSimulator(
scenario=scenario,
seed=42,
)
discovery = validated_scif(
invoke=simulator.invoke,
capabilities=scenario.capabilities,
)
report = discovery.discover()
print(report.executions)
print([
candidate.capabilities
for candidate in report.pairwise_report.candidates
])
if report.higher_order is not None:
print(report.higher_order.candidate)
Run the included example:
uv run python examples/quickstart.py
Public API
Primary imports:
from berliant import (
SCIF,
KeyedSimulator,
Scenario,
load_scenario,
validated_scif,
)
validated_scif(...)uses the configuration evaluated in Berliant's benchmark experiments.SCIF(...)provides full parameter control.KeyedSimulatorprovides deterministic configuration-keyed stochastic simulation.Scenarioandload_scenario(...)define and load benchmark scenarios.
Discovery Report
discover() returns an SCIFV4Report containing:
pairwise_reportresidualhigher_orderexecutions
Development
uv run ruff check .
uv run mypy src
uv run pytest -q
License
Licensed under the Apache License 2.0.
1 maintainer
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