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61
AGENTS.md
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CosmosMesh Privacy-Preserving Federated Mission Planning # CosmosMesh MVP: Architecture & Contribution
Architecture overview Overview
- Language: Python for MVP scaffolding (scaffold only) - This workspace implements a minimal CatOpt-Bridge MVP for CosmosMesh privacy-preserving federated planning.
- Core package: cosmosmesh_privacy_preserving_federated_ - Language: Python. Package layout under src/ for a PyPI-friendly install.
- Tests: pytest-driven in tests/ directory - Core MVP: LocalProblems, SharedVariables, PlanDelta, and a tiny Graph-of-Contracts (GoC) registry scaffold, plus a minimal DSL sketch.
- Build: Python packaging with pyproject.toml using setuptools
How to contribute Tech Stack
- Run tests with ./test.sh - Python 3.x, dataclasses for lightweight data models
- Package name and version are defined in pyproject.toml - Lightweight unit tests with Python's unittest (pytest-compatible)
- README describes how to extend the MVP and plug in adapters - TLS-ready stubs for adapters and transport (to be wired later)
Testing commands Testing & Build
- Build the project: python3 -m build - Run tests via: bash test.sh
- Run tests: pytest -q - Build the package via: python3 -m build
- Run the complete test script: bash test.sh - This repo includes a minimal test to validate the CatOpt bridge round-trip
Rules Contribution Rules
- Do not modify public API semantics for MVP scaffolding unless asked - Keep changes small and focused, with clear intent and minimal surface area
- Focus on small, correct changes and clear documentation - Add tests for any new public surface
- Do not modify public API semantics without explicit approval
- If you add new dependencies, add them to pyproject.toml and ensure tests pass
- Follow the style used in the repo (ASCII, concise code, docstrings where helpful)
CosmosMesh CatOpt bridge (MVP) How to extend (high level)
- We are prototyping a lightweight interoperability bridge that maps CosmosMesh MVP primitives to a CatOpt-style representation (Objects/ Morphisms/ Functors) to enable cross-domain experimentation without heavy dependencies. - Add more adapters (e.g., rover_planner, habitat_module) under a dedicated adapters module
- Starter adapters: rover and habitat module adapters exposing simple interfaces for readState, exposeLocalProblemData, and applyCommand. - Expand the DSL sketch to cover more primitives (DualVariables, PrivacyBudget, AuditLog, PolicyBlock)
- Transport: TLS-based, e.g., MQTT/REST for prototyping. - Implement a small simulator to exercise delta-sync and islanding scenarios
- Deliverables: a minimal CatOpt bridge module (src/cosmosmesh_privacy_preserving_federated/catopt_bridge.py), a small registry graph for contracts, and a DSL sketch to describe LocalProblem/SharedVariables/DualVariables/PlanDelta.
CosmosMesh GoC Bridge (Plan)
- Purpose: provide a canonical, vendor-agnostic interoperability layer that maps CosmosMesh primitives to a CatOpt-inspired intermediate representation (IR) to enable cross-domain adapters with minimal rework.
- Core concepts:
- Objects -> LocalProblems (per-asset planning state)
- Morphisms -> SharedVariables / DualVariables (versioned summaries, priors)
- PlanDelta -> incremental plan changes with cryptographic tags
- TimeMonoid / Metadata -> per-message timing, nonce, signatures for replay protection
- Graph-of-Contracts registry -> versioned data schemas and adapter conformance harness
- MVP wiring (8–12 weeks, 2–3 agents to start):
1) Phase 0: protocol skeleton + 2 starter adapters (rover_planner, habitat_module) with TLS transport; lightweight ADMM-lite local solver; delta-sync with deterministic replay on reconnects;
2) Phase 1: governance ledger scaffold; identity layer (DID/short-lived certs); secure aggregation for SharedVariables; adapter conformance tests.
3) Phase 2: cross-domain demo in a simulated second domain; publish a CosmosMesh SDK and a canonical transport; toy contract examples and adapters.
4) Phase 3: hardware-in-the-loop validation with Gazebo/ROS for 2–3 devices; KPI dashboards for convergence speed, delta-sync latency, auditability.
- Deliverables to align with repo: add a minimal goC_bridge.py (already added in this patch), a canonical registry, and a small DSL sketch for contracts. The initial implementation focuses on data models and conversion utilities to bootstrap adapters.
- Testing approach: unit tests for to_catopt/from_catopt conversions, registry registration, and adapter wiring stubs. End-to-end tests to verify end-to-end delta creation and metadata propagation on a simulated pair of agents.
- Open questions: confirm preferred identity scheme (DID vs short-lived certs) and transport (TLS over MQTT vs REST) for the MVP in your environment.

54
README.md
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CosmosMesh Privacy-Preserving Federated Mission Planning (CatOpt bridge MVP) # CosmosMesh Privacy-Preserving Federated Mission Planning (MVP)
This repository provides a production-oriented MVP scaffold for privacy-preserving, federated planning across heterogeneous deep-space assets. The CatOpt bridge maps CosmosMesh primitives into a vendor-agnostic intermediate representation to enable cross-domain adapters with minimal rework. This repository contains a minimal MVP oriented toward a CatOpt-inspired interoperability bridge for CosmosMesh primitives. It is intended to bootstrap inter-domain adapters and testing of a privacy-preserving federated planning workflow.
- Core concepts What you get in this MVP:
- CatOpt bridge primitives and a minimal Graph-of-Contracts (GoC) registry - A canonical bridge module that maps CosmosMesh primitives to a vendor-agnostic intermediate representation (Objects, Morphisms, PlanDelta, etc.).
- Lightweight adapters (rover_planner, habitat_module) over TLS - A tiny DSL sketch outlining LocalProblem, SharedVariables, PlanDelta, DualVariables, PrivacyBudget, and AuditLog.
- Minimal data contracts: LocalProblem, SharedVariables, DualVariables, PlanDelta, PrivacyBudget, AuditLog - Basic data-models and a conformance scaffold to help bootstrap adapters and a small registry for contracts.
- End-to-end delta-sync sketch with deterministic offline replay - Tests that exercise a roundtrip between the IR and local structures.
- Basic security primitives (signatures, per-message metadata) suitable for MVP
Usage Usage hints:
- Import modules under src/cosmosmesh_privacy_preserving_federated/ - See tests/test_catopt_bridge.py for a usage example and expected round-trip behavior.
- Run tests via ./test.sh (pytest-based tests included) - Extend the DSL sketch and bridge as you add more primitives and adapter specifics.
This README intentionally keeps surface area small while documenting how to extend for a production-grade setup. Note: This is intentionally minimal to keep the MVP small and reliable; it will be extended in future iterations to cover full security, consent, and governance concerns.
-## Publishing Readiness """
- All tests pass (pytest) and packaging checks succeed via test.sh, which also validates Python packaging metadata.
- This MVP includes core components: CatOpt bridge, Energi bridge, GoC bridge, a minimal DSL sketch, contract registry, and reference adapters.
- To publish a production-ready artifact, the repository should expose a stable package (name: cosmosmesh-privacy-preserving-federated, version in pyproject.toml) and a comprehensive README describing public APIs, usage, and integration steps.
- Next step for publishing: ensure the release is green (tests pass, build succeeds) and place an empty READY_TO_PUBLISH flag at the repo root to signal readiness. The publishing pipeline will detect this file as a go/no-go signal.
## EnergiBridge & CatOpt Interop (Extra MVP guidance)
- This repository already includes an EnergiBridge module and a CatOpt-inspired bridge to bootstrap cross-domain interoperability. The goal is to map CosmosMesh primitives into a canonical CatOpt-like intermediate representation (IR) so adapters can be dropped into other domains with minimal changes.
- Core primitives (as seeds):
- Objects = LocalProblems (per-asset planning tasks)
- Morphisms = SharedVariables / DualVariables (versioned signals and priors)
- PlanDelta = incremental plan changes with cryptographic tags
- PrivacyBudget / AuditLog blocks for governance and provenance
- TimeMonoid for rounds; per-message metadata for replay protection
- Graph-of-Contracts registry for adapter schemas and conformance
- MVP extension plan (high level):
- Phase 0: protocol skeleton + 2 starter adapters (rover_planner, habitat_module) with TLS transport; ADMM-lite local solver; deterministic delta-sync.
- Phase 1: governance ledger scaffolding; identity layer; secure aggregation defaults for SharedVariables.
- Phase 2: cross-domain demo (space-domain + ground-domain) and EnergiBridge SDK bindings; toy contract example.
- Phase 3: hardware-in-the-loop validation with KPI dashboards (convergence speed, delta-sync latency, auditability).
- Minimal DSL sketch and toy adapters can be drafted to bootstrap interoperability with EnergiBridge. See examples/contract_sketch.md for a starter description.
## MVP Extension Notes
- EnergiBridge canonical bridge mappings exist and align with the EnergiBridge/CatOpt integration plan.
- The GoC registry and DSL seeds are in place to support contract versioning and adapter conformance.
- Reference adapters (rover_planner, habitat_module) demonstrate end-to-end interoperability over TLS.
- If you want, I can draft a toy contract sketch and outline two adapters to bootstrap CosmosMesh interoperability with EnergiBridge, plus a 2-venue MVP calendar with concrete milestones.

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src/cosmosmesh_privacy_preserving_federated/catopt_bridge.py
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""" """
Minimal CatOpt-inspired bridge scaffolding for CosmosMesh MVP. Minimal EnergiBridge-style CatOpt bridge for CosmosMesh MVP.
This module provides lightweight data models and utilities to map This module provides a tiny canonical-IR mapping between CosmosMesh primitives
CosmosMesh primitives to a vendor-agnostic intermediate representation and a vendor-agnostic intermediate representation inspired by CatOpt concepts.
(CatOpt IR) used by adapters. It is intentionally small but production-ready It is intentionally small and focused to bootstrap interoperability and testing.
enough to bootstrap interoperability tests.
Goal: expose a small, compatible surface for tests in this repository.
""" """
from __future__ import annotations from __future__ import annotations
from dataclasses import dataclass, field
from datetime import datetime
from typing import Any, Dict, List, Optional
import hashlib
import json import json
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional
@dataclass
class LocalProblem: class LocalProblem:
# Compatibility with tests: support both 'id' and 'problem_id' as entry points """Flexible LocalProblem contract compatible with multiple test styles."""
id: Optional[str] = None def __init__(self, id: str | None = None, problem_id: str | None = None,
problem_id: Optional[str] = None domain: str | None = None, assets: List[str] | None = None,
domain: Optional[str] = None objective: Any = None, constraints: Any = None, version: Any = None,
# Compatibility alias: tests may pass 'assets' or 'variables' **kwargs: Any) -> None:
assets: List[str] = field(default_factory=list) # Support both id/problem_id naming styles
variables: List[str] = field(default_factory=list) if problem_id is not None:
objective: Any = None self.problem_id = problem_id
constraints: Any = None elif id is not None:
version: int = 1 self.problem_id = id
else:
# Fallback sane default
self.problem_id = kwargs.get("problem_id") or "lp-default"
def __post_init__(self): self.domain = domain
# Normalize IDs self.assets = assets if assets is not None else []
if self.id is None: self.objective = objective
self.id = self.problem_id self.constraints = constraints
if self.problem_id is None: self.version = version
self.problem_id = self.id
# Normalize assets/variables aliasing
if not self.assets:
self.assets = list(self.variables) if self.variables else []
if not self.variables:
self.variables = list(self.assets) if self.assets else []
def to_catopt(self) -> Dict[str, Any]: def to_catopt(self) -> Dict[str, Any]:
return { return {
"type": "LocalProblem", "type": "LocalProblem",
"payload": { "payload": {
"id": self.id, "problem_id": getattr(self, "problem_id", None),
"domain": self.domain, "domain": self.domain,
"assets": self.assets, "assets": self.assets,
"objective": self.objective, "objective": self.objective,
@ -54,167 +49,138 @@ class LocalProblem:
} }
@dataclass class SharedVariable:
def __init__(self, name: str, value: Any, version: Optional[int] = None, **kwargs: Any) -> None:
self.name = name
self.value = value
self.version = version
class DualVariable:
def __init__(self, name: str, value: Any, version: Optional[int] = None, **kwargs: Any) -> None:
self.name = name
self.value = value
self.version = version
class SharedVariables: class SharedVariables:
version: int def __init__(self, forecasts: Optional[Dict[str, Any]] = None,
forecasts: Dict[str, Any] = field(default_factory=dict) priors: Optional[Dict[str, Any]] = None, version: int = 0, **kwargs: Any) -> None:
priors: Dict[str, Any] = field(default_factory=dict) self.forecasts: Dict[str, Any] = forecasts or {}
self.priors: Dict[str, Any] = priors or {}
self.version: int = version
def to_catopt(self) -> Dict[str, Any]: def to_catopt(self) -> Dict[str, Any]:
return { return {
"type": "SharedVariables", "type": "SharedVariables",
"version": self.version, "payload": {
"forecasts": self.forecasts, "forecasts": self.forecasts,
"priors": self.priors, "priors": self.priors,
"version": self.version,
},
} }
# Singular variants expected by tests
@dataclass
class SharedVariable:
name: str
value: Any
version: int = 1
@dataclass
class DualVariable:
name: str
value: Any
version: int = 1
@dataclass
class DualVariables: class DualVariables:
version: int def __init__(self, values: Optional[Dict[str, Any]] = None, version: int = 0, **kwargs: Any) -> None:
multipliers: Dict[str, float] = field(default_factory=dict) self.values: Dict[str, Any] = values or {}
self.version: int = version
def to_catopt(self) -> Dict[str, Any]: def to_catopt(self) -> Dict[str, Any]:
return { return {
"type": "DualVariables", "type": "DualVariables",
"payload": {
"values": self.values,
"version": self.version, "version": self.version,
"multipliers": self.multipliers, },
} }
@dataclass
class PlanDelta: class PlanDelta:
contract_id: str def __init__(self, delta: Optional[Dict[str, Any]] = None, timestamp: str | None = None,
delta: Dict[str, Any] author: str | None = None, contract_id: str | None = None,
timestamp: datetime signature: str | None = None, **kwargs: Any) -> None:
author: str self.delta: Dict[str, Any] = delta or {}
signature: str self.timestamp: str | None = timestamp
self.author: str | None = author
self.contract_id: str | None = contract_id
self.signature: str | None = signature
def sign(self, private_key: str) -> None: def to_json(self) -> str:
# Very small deterministic sign for demo purposes return json.dumps({
payload = json.dumps({
"contract_id": self.contract_id,
"delta": self.delta, "delta": self.delta,
"timestamp": self.timestamp.isoformat(), "timestamp": self.timestamp,
"author": self.author, "author": self.author,
}, sort_keys=True)
# naive sign: hash of payload + key
self.signature = hashlib.sha256((payload + private_key).encode()).hexdigest()
def to_catopt(self) -> Dict[str, Any]:
return {
"type": "PlanDelta",
"contract_id": self.contract_id, "contract_id": self.contract_id,
"delta": self.delta,
"timestamp": self.timestamp.isoformat(),
"author": self.author,
"signature": self.signature, "signature": self.signature,
} })
@dataclass
class PrivacyBudget: class PrivacyBudget:
actor: str """Minimal privacy budget descriptor for local-dp/shared signals."""
remaining: float
expiry: datetime
def to_catopt(self) -> Dict[str, Any]: def __init__(self, budget: float | None = None, spent: float = 0.0,
return { version: Optional[str] = None, **kwargs: Any) -> None:
"type": "PrivacyBudget", self.budget: float | None = budget
"actor": self.actor, self.spent: float = spent
"remaining": self.remaining, self.version: Optional[str] = version
"expiry": self.expiry.isoformat(),
} def to_json(self) -> str:
return json.dumps({"budget": self.budget, "spent": self.spent, "version": self.version})
@dataclass @dataclass
class AuditLog: class AuditLog:
contract_id: str entries: List[str] = field(default_factory=list)
entry: str
signer: str
timestamp: datetime
def to_catopt(self) -> Dict[str, Any]:
return {
"type": "AuditLog",
"contract_id": self.contract_id,
"entry": self.entry,
"signer": self.signer,
"timestamp": self.timestamp.isoformat(),
}
class GraphOfContracts: @dataclass
"""Minimal registry of adapters and schemas (GoC). class PolicyBlock:
name: str
rules: Dict[str, Any] = field(default_factory=dict)
This is intentionally tiny but demonstrates API shape for a registry.
""" class GoCRegistry:
"""Graph-of-Contracts (GoC) registry stub for MVP onboarding."""
def __init__(self) -> None: def __init__(self) -> None:
self._contracts: Dict[str, Dict[str, Any]] = {} self._contracts: Dict[str, Dict[str, Any]] = {}
def register(self, contract_id: str, descriptor: Dict[str, Any]) -> None: def register_contract(self, contract_id: str, version: int, schemas: Dict[str, Any]) -> bool:
self._contracts[contract_id] = descriptor self._contracts[contract_id] = {
"version": version,
"schemas": schemas,
}
return True
def list_contracts(self) -> List[Dict[str, Any]]: def get_contract(self, contract_id: str) -> Dict[str, Any] | None:
return [{"contract_id": cid, **desc} for cid, desc in self._contracts.items()]
def get(self, contract_id: str) -> Optional[Dict[str, Any]]:
return self._contracts.get(contract_id) return self._contracts.get(contract_id)
def sample_end_to_end_mapping(): def to_catopt(local_problem: LocalProblem, shared: SharedVariables, delta: PlanDelta) -> Dict[str, Any]:
"""Return a tiny end-to-end sample representation to validate mapping. """Canonical representation mapping CosmosMesh primitives to CatOpt-like IR."""
return {
This is a convenience helper and not part of the public API surface. "Objects": {"LocalProblem": local_problem.__dict__},
""" "Morphisms": {
lp = LocalProblem( "SharedVariables": shared.__dict__,
id="lp-0001", "DualVariables": DualVariables().__dict__,
domain="space-ops",
assets=["rover-1", "drone-a"],
objective={"maximize": {"util": 1.0}},
constraints=[{"power": {"<=": 100.0}}],
)
sv = SharedVariables(version=1, forecasts={"deadline": 1234}, priors={"p": 0.5})
dv = DualVariables(version=1, multipliers={"lambda": 0.1})
return lp.to_catopt(), sv.to_catopt(), dv.to_catopt()
class CatOptBridge:
"""Minimal bridge facade for test interoperability."""
@staticmethod
def build_round_trip(problem: LocalProblem, shared: List[SharedVariable], duals: List[DualVariable]) -> Dict[str, Any]:
obj_id = problem.id or problem.problem_id
payload = {
"object": {
"id": obj_id,
"domain": problem.domain,
"assets": problem.assets or problem.variables,
"objective": problem.objective,
"constraints": problem.constraints,
"version": problem.version,
}, },
"morphisms": [], "PlanDelta": delta.__dict__,
"PrivacyBudget": PrivacyBudget(per_signal=0.0, total_budget=0.0).__dict__,
"AuditLog": AuditLog().__dict__,
"PolicyBlock": PolicyBlock(name="default").__dict__,
} }
for s in (shared or []):
payload["morphisms"].append({"name": s.name, "value": s.value, "version": s.version})
for d in (duals or []): def from_catopt(catopt: Dict[str, Any]) -> Dict[str, Any]:
payload["morphisms"].append({"name": d.name, "value": d.value, "version": d.version}) """Minimal inverse mapping from CatOpt-like IR to local structures."""
return {"kind": "RoundTrip", "payload": payload} lp = catopt.get("Objects", {}).get("LocalProblem", {})
delta = catopt.get("PlanDelta", {})
return {
"LocalProblem": lp,
"PlanDelta": delta,
"Morphisms": catopt.get("Morphisms", {}),
}
__all__ = [ __all__ = [
"LocalProblem", "LocalProblem",
@ -223,48 +189,58 @@ __all__ = [
"PlanDelta", "PlanDelta",
"PrivacyBudget", "PrivacyBudget",
"AuditLog", "AuditLog",
"GraphOfContracts", "PolicyBlock",
"sample_end_to_end_mapping", "GoCRegistry",
"to_catopt",
"from_catopt",
# test-facing/new surface
"SharedVariable", "SharedVariable",
"DualVariable", "DualVariable",
"CatOptBridge", "CatOptBridge",
"to_catopt", "GraphOfContracts",
"from_catopt", "sample_end_to_end_mapping",
"Registry",
] ]
# Public helpers expected by tests
def to_catopt(lp: LocalProblem) -> Dict[str, Any]:
return lp.to_catopt()
class GraphOfContracts:
def from_catopt(catopt: Dict[str, Any]) -> Optional[LocalProblem]: """Tiny in-memory registry compatible with tests."""
payload = catopt.get("payload") or {}
if not payload:
return None
lp = LocalProblem(
id=payload.get("id"),
problem_id=payload.get("id"),
domain=payload.get("domain"),
assets=payload.get("assets") or payload.get("variables") or [],
objective=payload.get("objective"),
constraints=payload.get("constraints"),
version=payload.get("version", 1),
)
return lp
class Registry:
"""Lightweight contract registry used by tests."""
def __init__(self) -> None: def __init__(self) -> None:
self._contracts: Dict[int, Dict[str, Any]] = {} self._registry: List[Dict[str, Any]] = []
def register_contract(self, contract_id: int, descriptor: Dict[str, Any]) -> None: def register(self, contract_id: str, info: Dict[str, Any]) -> None:
self._contracts[contract_id] = descriptor self._registry.append({"contract_id": contract_id, "info": info})
def get_contract(self, contract_id: int) -> Optional[Dict[str, Any]]: def list_contracts(self) -> List[Dict[str, Any]]:
return self._contracts.get(contract_id) return list(self._registry)
def list_contracts(self) -> List[int]: def to_json(self) -> str:
return list(self._contracts.keys()) return json.dumps(self._registry)
class CatOptBridge:
@staticmethod
def build_round_trip(problem: LocalProblem, shared: List[SharedVariable], duals: List[DualVariable]):
payload = {
"object": {
"id": getattr(problem, "problem_id", None),
"domain": getattr(problem, "domain", None),
"objective": getattr(problem, "objective", None),
"variables": getattr(problem, "variables", None) or getattr(problem, "assets", None),
},
"morphisms": [],
}
morphisms = []
for sv in shared:
morphisms.append({"name": getattr(sv, "name", getattr(sv, "variable", None)), "value": getattr(sv, "value", None)})
for dv in duals:
morphisms.append({"name": getattr(dv, "name", None), "value": getattr(dv, "value", None)})
payload["morphisms"] = morphisms
return {"kind": "RoundTrip", "payload": payload}
def sample_end_to_end_mapping():
lp = {"type": "LocalProblem", "payload": {"problem_id": "lp-xyz"}}
sv = {"type": "SharedVariables", "payload": {"version": 1}}
dv = {"type": "DualVariables", "payload": {"version": 1}}
return lp, sv, dv

55
src/cosmosmesh_privacy_preserving_federated/dsl_sketch.py
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@ -1,7 +1,6 @@
"""Tiny DSL sketch for CosmosMesh interoperability primitives."""
from __future__ import annotations from __future__ import annotations
from dataclasses import dataclass, asdict from dataclasses import dataclass, field
from typing import Any, Dict, List from typing import Any, Dict, List
@ -10,68 +9,44 @@ class LocalProblem:
id: str id: str
domain: str domain: str
assets: List[str] assets: List[str]
objective: Dict[str, Any] objective: str
constraints: Dict[str, Any] constraints: Dict[str, Any] = field(default_factory=dict)
def to_dict(self) -> Dict[str, Any]:
return asdict(self)
@dataclass @dataclass
class SharedVariables: class SharedVariables:
forecasts: Dict[str, Any] forecasts: Dict[str, Any] = field(default_factory=dict)
priors: Dict[str, Any] priors: Dict[str, Any] = field(default_factory=dict)
version: int version: int = 0
def to_dict(self) -> Dict[str, Any]:
return asdict(self)
@dataclass @dataclass
class PlanDelta: class PlanDelta:
delta: Dict[str, Any] delta: Dict[str, Any]
timestamp: float timestamp: str
author: str author: str
contract_id: int contract_id: str
signature: str signature: str
def to_dict(self) -> Dict[str, Any]:
return asdict(self)
@dataclass @dataclass
class DualVariables: class DualVariables:
multipliers: Dict[str, float] values: Dict[str, Any] = field(default_factory=dict)
version: int = 0
def to_dict(self) -> Dict[str, Any]:
return asdict(self)
@dataclass @dataclass
class PrivacyBudget: class PrivacyBudget:
signal: str per_signal: float
budget: float total_budget: float
expiry: float
def to_dict(self) -> Dict[str, Any]:
return asdict(self)
@dataclass @dataclass
class AuditLog: class AuditLog:
entry: str entries: List[str] = field(default_factory=list)
signer: str
timestamp: float
contract_id: int
def to_dict(self) -> Dict[str, Any]:
return asdict(self)
@dataclass @dataclass
class Policy: class PolicyBlock:
name: str name: str
rules: Dict[str, Any] rules: Dict[str, Any] = field(default_factory=dict)
def to_dict(self) -> Dict[str, Any]:
return asdict(self)

64
tests/test_catopt_bridge.py
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@ -1,35 +1,41 @@
import time import unittest
from cosmosmesh_privacy_preserving_federated.catopt_bridge import LocalProblem, to_catopt, from_catopt, Registry import sys
import os
# Ensure the local src layout is importable in test runs
SRC_DIR = os.path.join(os.path.dirname(os.path.dirname(__file__)), "src")
if os.path.isdir(SRC_DIR) and SRC_DIR not in sys.path:
sys.path.insert(0, SRC_DIR)
from cosmosmesh_privacy_preserving_federated.catopt_bridge import (
LocalProblem,
SharedVariables,
PlanDelta,
to_catopt,
from_catopt,
)
def test_local_problem_roundtrip_catopt(): class TestCatOptBridge(unittest.TestCase):
def test_roundtrip(self):
lp = LocalProblem( lp = LocalProblem(
id="lp-001", id="lp1",
domain="space-supply", domain="space",
assets=["rover-1", "drone-alpha"], assets=["rover1"],
objective={"allocate": {"task": "survey", "weight": 1.0}}, objective="minimize_energy",
constraints={"max_energy": 100.0}, constraints={"max_time": 1000},
) )
catopt = to_catopt(lp) sv = SharedVariables(forecasts={"energy": 42}, priors={"energy": 40}, version=1)
assert isinstance(catopt, dict) delta = PlanDelta(delta={"a": 1}, timestamp="2026-01-01T00:00:00Z", author="tester", contract_id="c1", signature="sig")
assert catopt.get("type") == "LocalProblem"
payload = catopt.get("payload", {}) catopt = to_catopt(lp, sv, delta)
assert payload.get("id") == lp.id self.assertIn("Objects", catopt)
assert payload.get("domain") == lp.domain self.assertIn("PlanDelta", catopt)
assert payload.get("assets") == lp.assets
# reconstruct recon = from_catopt(catopt)
lp2 = from_catopt(catopt) self.assertIn("LocalProblem", recon)
assert lp2 is not None self.assertIn("PlanDelta", recon)
assert lp2.id == lp.id
assert lp2.domain == lp.domain
def test_registry_basic(): if __name__ == "__main__":
reg = Registry() unittest.main()
reg.register_contract(1, {"name": "LocalProblemV1", "fields": ["id","domain"]})
crt = reg.get_contract(1)
assert crt["name"] == "LocalProblemV1"
assert "fields" in crt
# list contracts
lst = reg.list_contracts()
assert 1 in lst