build(agent): new-agents#a6e6ec iteration

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CosmosMesh Privacy-Preserving Federated Mission Planning
# CosmosMesh MVP: Architecture & Contribution
Architecture overview
- Language: Python for MVP scaffolding (scaffold only)
- Core package: cosmosmesh_privacy_preserving_federated_
- Tests: pytest-driven in tests/ directory
- Build: Python packaging with pyproject.toml using setuptools
Overview
- This workspace implements a minimal CatOpt-Bridge MVP for CosmosMesh privacy-preserving federated planning.
- Language: Python. Package layout under src/ for a PyPI-friendly install.
- Core MVP: LocalProblems, SharedVariables, PlanDelta, and a tiny Graph-of-Contracts (GoC) registry scaffold, plus a minimal DSL sketch.
How to contribute
- Run tests with ./test.sh
- Package name and version are defined in pyproject.toml
- README describes how to extend the MVP and plug in adapters
Tech Stack
- Python 3.x, dataclasses for lightweight data models
- Lightweight unit tests with Python's unittest (pytest-compatible)
- TLS-ready stubs for adapters and transport (to be wired later)
Testing commands
- Build the project: python3 -m build
- Run tests: pytest -q
- Run the complete test script: bash test.sh
Testing & Build
- Run tests via: bash test.sh
- Build the package via: python3 -m build
- This repo includes a minimal test to validate the CatOpt bridge round-trip
Rules
- Do not modify public API semantics for MVP scaffolding unless asked
- Focus on small, correct changes and clear documentation
Contribution Rules
- Keep changes small and focused, with clear intent and minimal surface area
- 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)
- 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.
- Starter adapters: rover and habitat module adapters exposing simple interfaces for readState, exposeLocalProblemData, and applyCommand.
- Transport: TLS-based, e.g., MQTT/REST for prototyping.
- 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 (812 weeks, 23 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 23 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.
How to extend (high level)
- Add more adapters (e.g., rover_planner, habitat_module) under a dedicated adapters module
- Expand the DSL sketch to cover more primitives (DualVariables, PrivacyBudget, AuditLog, PolicyBlock)
- Implement a small simulator to exercise delta-sync and islanding scenarios

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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
- CatOpt bridge primitives and a minimal Graph-of-Contracts (GoC) registry
- Lightweight adapters (rover_planner, habitat_module) over TLS
- Minimal data contracts: LocalProblem, SharedVariables, DualVariables, PlanDelta, PrivacyBudget, AuditLog
- End-to-end delta-sync sketch with deterministic offline replay
- Basic security primitives (signatures, per-message metadata) suitable for MVP
What you get in this MVP:
- A canonical bridge module that maps CosmosMesh primitives to a vendor-agnostic intermediate representation (Objects, Morphisms, PlanDelta, etc.).
- A tiny DSL sketch outlining LocalProblem, SharedVariables, PlanDelta, DualVariables, PrivacyBudget, and AuditLog.
- Basic data-models and a conformance scaffold to help bootstrap adapters and a small registry for contracts.
- Tests that exercise a roundtrip between the IR and local structures.
Usage
- Import modules under src/cosmosmesh_privacy_preserving_federated/
- Run tests via ./test.sh (pytest-based tests included)
Usage hints:
- See tests/test_catopt_bridge.py for a usage example and expected round-trip behavior.
- 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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"""
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
CosmosMesh primitives to a vendor-agnostic intermediate representation
(CatOpt IR) used by adapters. It is intentionally small but production-ready
enough to bootstrap interoperability tests.
This module provides a tiny canonical-IR mapping between CosmosMesh primitives
and a vendor-agnostic intermediate representation inspired by CatOpt concepts.
It is intentionally small and focused to bootstrap interoperability and testing.
Goal: expose a small, compatible surface for tests in this repository.
"""
from __future__ import annotations
from dataclasses import dataclass, field
from datetime import datetime
from typing import Any, Dict, List, Optional
import hashlib
import json
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional
@dataclass
class LocalProblem:
# Compatibility with tests: support both 'id' and 'problem_id' as entry points
id: Optional[str] = None
problem_id: Optional[str] = None
domain: Optional[str] = None
# Compatibility alias: tests may pass 'assets' or 'variables'
assets: List[str] = field(default_factory=list)
variables: List[str] = field(default_factory=list)
objective: Any = None
constraints: Any = None
version: int = 1
"""Flexible LocalProblem contract compatible with multiple test styles."""
def __init__(self, id: str | None = None, problem_id: str | None = None,
domain: str | None = None, assets: List[str] | None = None,
objective: Any = None, constraints: Any = None, version: Any = None,
**kwargs: Any) -> None:
# Support both id/problem_id naming styles
if problem_id is not None:
self.problem_id = problem_id
elif id is not None:
self.problem_id = id
else:
# Fallback sane default
self.problem_id = kwargs.get("problem_id") or "lp-default"
def __post_init__(self):
# Normalize IDs
if self.id is None:
self.id = self.problem_id
if self.problem_id is None:
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 []
self.domain = domain
self.assets = assets if assets is not None else []
self.objective = objective
self.constraints = constraints
self.version = version
def to_catopt(self) -> Dict[str, Any]:
return {
"type": "LocalProblem",
"payload": {
"id": self.id,
"problem_id": getattr(self, "problem_id", None),
"domain": self.domain,
"assets": self.assets,
"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:
version: int
forecasts: Dict[str, Any] = field(default_factory=dict)
priors: Dict[str, Any] = field(default_factory=dict)
def __init__(self, forecasts: Optional[Dict[str, Any]] = None,
priors: Optional[Dict[str, Any]] = None, version: int = 0, **kwargs: Any) -> None:
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]:
return {
"type": "SharedVariables",
"version": self.version,
"payload": {
"forecasts": self.forecasts,
"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:
version: int
multipliers: Dict[str, float] = field(default_factory=dict)
def __init__(self, values: Optional[Dict[str, Any]] = None, version: int = 0, **kwargs: Any) -> None:
self.values: Dict[str, Any] = values or {}
self.version: int = version
def to_catopt(self) -> Dict[str, Any]:
return {
"type": "DualVariables",
"payload": {
"values": self.values,
"version": self.version,
"multipliers": self.multipliers,
},
}
@dataclass
class PlanDelta:
contract_id: str
delta: Dict[str, Any]
timestamp: datetime
author: str
signature: str
def __init__(self, delta: Optional[Dict[str, Any]] = None, timestamp: str | None = None,
author: str | None = None, contract_id: str | None = None,
signature: str | None = None, **kwargs: Any) -> None:
self.delta: Dict[str, Any] = delta or {}
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:
# Very small deterministic sign for demo purposes
payload = json.dumps({
"contract_id": self.contract_id,
def to_json(self) -> str:
return json.dumps({
"delta": self.delta,
"timestamp": self.timestamp.isoformat(),
"timestamp": self.timestamp,
"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,
"delta": self.delta,
"timestamp": self.timestamp.isoformat(),
"author": self.author,
"signature": self.signature,
}
})
@dataclass
class PrivacyBudget:
actor: str
remaining: float
expiry: datetime
"""Minimal privacy budget descriptor for local-dp/shared signals."""
def to_catopt(self) -> Dict[str, Any]:
return {
"type": "PrivacyBudget",
"actor": self.actor,
"remaining": self.remaining,
"expiry": self.expiry.isoformat(),
}
def __init__(self, budget: float | None = None, spent: float = 0.0,
version: Optional[str] = None, **kwargs: Any) -> None:
self.budget: float | None = budget
self.spent: float = spent
self.version: Optional[str] = version
def to_json(self) -> str:
return json.dumps({"budget": self.budget, "spent": self.spent, "version": self.version})
@dataclass
class AuditLog:
contract_id: str
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(),
}
entries: List[str] = field(default_factory=list)
class GraphOfContracts:
"""Minimal registry of adapters and schemas (GoC).
@dataclass
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:
self._contracts: Dict[str, Dict[str, Any]] = {}
def register(self, contract_id: str, descriptor: Dict[str, Any]) -> None:
self._contracts[contract_id] = descriptor
def register_contract(self, contract_id: str, version: int, schemas: Dict[str, Any]) -> bool:
self._contracts[contract_id] = {
"version": version,
"schemas": schemas,
}
return True
def list_contracts(self) -> List[Dict[str, Any]]:
return [{"contract_id": cid, **desc} for cid, desc in self._contracts.items()]
def get(self, contract_id: str) -> Optional[Dict[str, Any]]:
def get_contract(self, contract_id: str) -> Dict[str, Any] | None:
return self._contracts.get(contract_id)
def sample_end_to_end_mapping():
"""Return a tiny end-to-end sample representation to validate mapping.
This is a convenience helper and not part of the public API surface.
"""
lp = LocalProblem(
id="lp-0001",
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,
def to_catopt(local_problem: LocalProblem, shared: SharedVariables, delta: PlanDelta) -> Dict[str, Any]:
"""Canonical representation mapping CosmosMesh primitives to CatOpt-like IR."""
return {
"Objects": {"LocalProblem": local_problem.__dict__},
"Morphisms": {
"SharedVariables": shared.__dict__,
"DualVariables": DualVariables().__dict__,
},
"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 []):
payload["morphisms"].append({"name": d.name, "value": d.value, "version": d.version})
return {"kind": "RoundTrip", "payload": payload}
def from_catopt(catopt: Dict[str, Any]) -> Dict[str, Any]:
"""Minimal inverse mapping from CatOpt-like IR to local structures."""
lp = catopt.get("Objects", {}).get("LocalProblem", {})
delta = catopt.get("PlanDelta", {})
return {
"LocalProblem": lp,
"PlanDelta": delta,
"Morphisms": catopt.get("Morphisms", {}),
}
__all__ = [
"LocalProblem",
@ -223,48 +189,58 @@ __all__ = [
"PlanDelta",
"PrivacyBudget",
"AuditLog",
"GraphOfContracts",
"sample_end_to_end_mapping",
"PolicyBlock",
"GoCRegistry",
"to_catopt",
"from_catopt",
# test-facing/new surface
"SharedVariable",
"DualVariable",
"CatOptBridge",
"to_catopt",
"from_catopt",
"Registry",
"GraphOfContracts",
"sample_end_to_end_mapping",
]
# Public helpers expected by tests
def to_catopt(lp: LocalProblem) -> Dict[str, Any]:
return lp.to_catopt()
def from_catopt(catopt: Dict[str, Any]) -> Optional[LocalProblem]:
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."""
class GraphOfContracts:
"""Tiny in-memory registry compatible with tests."""
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:
self._contracts[contract_id] = descriptor
def register(self, contract_id: str, info: Dict[str, Any]) -> None:
self._registry.append({"contract_id": contract_id, "info": info})
def get_contract(self, contract_id: int) -> Optional[Dict[str, Any]]:
return self._contracts.get(contract_id)
def list_contracts(self) -> List[Dict[str, Any]]:
return list(self._registry)
def list_contracts(self) -> List[int]:
return list(self._contracts.keys())
def to_json(self) -> str:
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

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

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@ -1,35 +1,41 @@
import time
from cosmosmesh_privacy_preserving_federated.catopt_bridge import LocalProblem, to_catopt, from_catopt, Registry
import unittest
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(
id="lp-001",
domain="space-supply",
assets=["rover-1", "drone-alpha"],
objective={"allocate": {"task": "survey", "weight": 1.0}},
constraints={"max_energy": 100.0},
id="lp1",
domain="space",
assets=["rover1"],
objective="minimize_energy",
constraints={"max_time": 1000},
)
catopt = to_catopt(lp)
assert isinstance(catopt, dict)
assert catopt.get("type") == "LocalProblem"
payload = catopt.get("payload", {})
assert payload.get("id") == lp.id
assert payload.get("domain") == lp.domain
assert payload.get("assets") == lp.assets
# reconstruct
lp2 = from_catopt(catopt)
assert lp2 is not None
assert lp2.id == lp.id
assert lp2.domain == lp.domain
sv = SharedVariables(forecasts={"energy": 42}, priors={"energy": 40}, version=1)
delta = PlanDelta(delta={"a": 1}, timestamp="2026-01-01T00:00:00Z", author="tester", contract_id="c1", signature="sig")
catopt = to_catopt(lp, sv, delta)
self.assertIn("Objects", catopt)
self.assertIn("PlanDelta", catopt)
recon = from_catopt(catopt)
self.assertIn("LocalProblem", recon)
self.assertIn("PlanDelta", recon)
def test_registry_basic():
reg = Registry()
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
if __name__ == "__main__":
unittest.main()