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db718654b5
* feat: Add Schema Registry and Validation Framework This commit introduces a comprehensive schema registry and validation framework, providing schema-based validation of resources and policy effects. - Thread-safe, in-memory registry for schema storage and management - Global registry patterns for effects and resources - Concurrent access with proper error handling - Unicode schema names support - JSON Schema-compliant validation for all primitive types - Advanced constraint validation (patterns, ranges, length limits) - Discriminated union support with anyOf schemas - Detailed error reporting with nested validation paths - Discriminated subobject validation for polymorphic schemas - **Registry Tests**: All registry operations - **Effect Tests**: Policy effect validation - **Resource Tests**: Resource validation - **Validation Tests**: Core validation engine - Thread-safety, error handling, integration scenarios, edge cases - **Dependencies**: dashmap, once_cell, regex - **Thread Safety**: Minimal locking with Rc<Schema> sharing - **Error Types**: TypeMismatch, OutOfRange, PatternMismatch, etc. - Complete schema registry and validation subsystem - Comprehensive test coverage - Foundation for policy validation in Regorus Benchmarks: - Criterion benchmarks for basic types, effects and Azure resources - Performance range: 3.22ns (string) to 34.74µs (Azure VM resource schema validation) - String withs patterns validation: 30.2µs. Need to explore whether regex caching helps bring this down. - Azure policy effects: 188ns-1.4µs Signed-off-by: Anand Krishnamoorthi <anakrish@microsoft.com> * Address PR feedback - move error to a separate file - use meaningful var names Signed-off-by: Anand Krishnamoorthi <anakrish@microsoft.com> * Refactor - Reusable Registry struct - Split and simplify tests Signed-off-by: Anand Krishnamoorthi <anakrish@microsoft.com> --------- 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.
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)