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- Introduce ExecutionTimer/ExecutionTimerConfig to allow limiting evaluating time. - To amortize time checking costs, checking interval can be configured via the notion of work units - A global fallback time limit can be set to universally limit all evaluation in addition to engine level limit setting. - Implement limnits in interpreter and RVM. In RVM, also handle suspend/resume so that time during pause is not counted. - Add engine-level APIs to set/clear per-engine timer configuration and apply global fallback defaults. - Surface execution-time limits through FFI and C# bindings - Add C# tests and example usage to validate engine overrides, global fallback behavior, and compiled policy enforcement. - Expand docs for execution-time limit - Add interpreter YAML cases and VM unit tests for time-limit behavior and deterministic time sources. Signed-off-by: Anand Krishnamoorthi <anakrish@microsoft.com>
regorus
Regorus is
- Rego-Rus(t) - A fast, light-weight Rego interpreter written in Rust.
- Rigorous - A rigorous enforcer of well-defined Rego semantics.
Regorus can be used in Python via regorus package. (It is not yet available in PyPI, but can be manually built.)
See Repository.
Automation
Run cargo xtask build-python to produce wheels via maturin, or cargo xtask test-python to reinstall the package locally and execute the sample script and pytest suite.
To build this binding, see building
Usage
import regorus
# Create engine
engine = regorus.Engine()
# Load policies
engine.add_policy_from_file('../../tests/aci/framework.rego')
engine.add_policy_from_file('../../tests/aci/api.rego')
engine.add_policy_from_file('../../tests/aci/policy.rego')
# Add policy data
data = {
"metadata": {
"devices": {
"/run/layers/p0-layer0": "1b80f120dbd88e4355d6241b519c3e25290215c469516b49dece9cf07175a766",
"/run/layers/p0-layer1": "e769d7487cc314d3ee748a4440805317c19262c7acd2fdbdb0d47d2e4613a15c",
"/run/layers/p0-layer2": "eb36921e1f82af46dfe248ef8f1b3afb6a5230a64181d960d10237a08cd73c79",
"/run/layers/p0-layer3": "41d64cdeb347bf236b4c13b7403b633ff11f1cf94dbc7cf881a44d6da88c5156",
"/run/layers/p0-layer4": "4dedae42847c704da891a28c25d32201a1ae440bce2aecccfa8e6f03b97a6a6c",
"/run/layers/p0-layer5": "fe84c9d5bfddd07a2624d00333cf13c1a9c941f3a261f13ead44fc6a93bc0e7a"
}
}
}
engine.add_data(data)
# Set input
input = {
"containerID": "container0",
"layerPaths": [
"/run/layers/p0-layer0",
"/run/layers/p0-layer1",
"/run/layers/p0-layer2",
"/run/layers/p0-layer3",
"/run/layers/p0-layer4",
"/run/layers/p0-layer5"
],
"target": "/run/gcs/c/container0/rootfs"
}
engine.set_input(input)
# Eval rule
value = engine.eval_rule('data.framework.mount_overlay')
# Print value
print(value)