build(agent): new-agents-4#58ba63 iteration
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README.md
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README.md
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# CommonsGrid: Community-Managed, Privacy-Preserving Energy Commons
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This repository holds a production-oriented prototype for CommonsGrid: a community-managed, privacy-preserving energy marketplace designed for neighborhood-scale pilots. It includes a lightweight DSL sketch and toy adapters to bootstrap interoperability with a CatOpt-like intermediate representation (IR).
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Overview
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Key components added in this patch:
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- A neighborhood-scale energy commons platform enabling residents to co-create and govern an energy marketplace using local PV, storage, EVs, and flexible loads.
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- idea165_commonsgrid_community_managed/dsl.py: Minimal DataClass-based DSL for LocalProblem, SharedSignals, PlanDelta, PrivacyBudget, and AuditLog.
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- Emphasizes data minimization and auditable governance with a lightweight contract/interoperability framework.
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- idea165_commonsgrid_community_managed/adapters/: Two starter adapters (InverterControllerAdapter and NeighborhoodBatteryAdapter) that map signals to the canonical LocalProblem representation.
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Key features (high level)
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How to use:
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- Community Governance Ledger: versioned policy blocks, crypto-signed approvals, and an auditable decision log.
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- Instantiate adapters and call map_to_local_problem to generate a dictionary representation that can be consumed by the interoperability bridge.
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- Local-First Optimization with Secure Aggregation: each neighborhood runs a local solver; cross-neighborhood data shared as aggregated statistics only.
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- Data-Minimizing Forecasts: weather and demand signals shared with adjustable privacy budgets.
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- Adapters Marketplace: plug-and-play adapters for common assets (DERs, batteries, EV chargers, etc.).
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- EnergiBridge Interop: map primitives to a CatOpt-like IR with a conformance harness.
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- Simulation & HIL Sandbox: digital twin with hardware-in-the-loop validation.
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What you will find here
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This is a seed for a production-grade MVP; further work should flesh out governance ledger, secure aggregation, and interop contracts.
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- A Python package with core primitives, toy adapters, a simple governance ledger, and a small solver scaffold.
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"""
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- Lightweight tests validating governance and adapter mappings.
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- A minimal README linking to packaging metadata and test commands.
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Usage
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- Run tests: ./test.sh
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- Build and package: python3 -m build
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- This repository is designed to be extended by multiple teams to plug in real components over time.
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Licensing
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- All code is provided as a starting point for research and pilot deployments; please review LICENSE when available.
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See also: AGENTS.md for contributor guidelines.
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"""Idea165 CommonsGrid – Community-Managed, Privacy-Preserving Energy Commons (minimal core).
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This package provides a small, well-typed core that can be used to bootstrap a larger project.
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It includes:
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- GovernanceLedger: versioned, signed policy blocks with an auditable log
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- LocalProblem: neighborhood energy representation
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- Adapters: base adapter and two toy adapters
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- EnergiBridge: lightweight IR mapping between commons primitives and a CatOpt-like representation
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- Simulator: tiny dispatcher that operates on the primitives
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"""
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"""
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Core package for CommonsGrid community-managed prototype.
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This package includes lightweight DSL sketches and toy adapters
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to bootstrap interoperability with a CatOpt-like IR.
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"""
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from . import dsl as dsl
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from . import adapters as adapters
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from .governance import GovernanceLedger
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__all__ = ["dsl", "adapters"]
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from .models import LocalProblem
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from .adapters import BaseAdapter, DERAdapter, BatteryAdapter, InverterControllerAdapter, NeighborhoodBatteryAdapter
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from .energi_bridge import EnergiBridge, IRBlock
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from .simulator import Simulator
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from .privacy import PrivacyBudget
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__all__ = [
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"GovernanceLedger",
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"LocalProblem",
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"BaseAdapter",
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"DERAdapter",
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"BatteryAdapter",
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"InverterControllerAdapter",
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"NeighborhoodBatteryAdapter",
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"EnergiBridge",
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"IRBlock",
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"Simulator",
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"PrivacyBudget",
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]
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from .inverter_adapter import InverterControllerAdapter
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from .neighborhood_battery_adapter import NeighborhoodBatteryAdapter
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from .der_adapter import DERAdapter
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from .battery_adapter import BatteryAdapter
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__all__ = [
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"InverterControllerAdapter",
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"NeighborhoodBatteryAdapter",
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"DERAdapter",
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"BatteryAdapter",
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]
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from typing import Dict, Any
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from ..models import LocalProblem
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class BatteryAdapter:
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"""Tiny adapter converting LocalProblem into a Battery-shared representation."""
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def to_shared(self, lp: LocalProblem) -> Dict[str, Any]:
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return {
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"type": "Battery",
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"neighborhood_id": getattr(lp, "neighborhood_id", None),
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"demand_kw": getattr(lp, "demand_kw", 0.0),
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"pv_kw": getattr(lp, "pv_kw", 0.0),
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"storage_kwh": getattr(lp, "storage_kwh", 0.0),
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"evs": getattr(lp, "evs", 0),
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}
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from typing import Dict, Any
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from ..models import LocalProblem
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class DERAdapter:
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"""Tiny adapter converting LocalProblem into a DER-shared representation."""
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def to_shared(self, lp: LocalProblem) -> Dict[str, Any]:
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return {
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"type": "DER",
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"neighborhood_id": getattr(lp, "neighborhood_id", None),
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"demand_kw": getattr(lp, "demand_kw", 0.0),
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"pv_kw": getattr(lp, "pv_kw", 0.0),
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"storage_kwh": getattr(lp, "storage_kwh", 0.0),
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"evs": getattr(lp, "evs", 0),
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}
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from typing import Dict, Any
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from ..dsl import LocalProblem
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class InverterControllerAdapter:
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"""
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Toy adapter that maps rooftop PV inverter signals to a canonical LocalProblem delta.
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"""
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def __init__(self, neighborhood_id: str):
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self.neighborhood_id = neighborhood_id
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def map_to_local_problem(self, pv_output_kw: float, demand_kw: float) -> Dict[str, Any]:
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lp = LocalProblem(
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neighborhood_id=self.neighborhood_id,
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objective="minimize_cost",
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data_sources=["pv_inverter"],
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constraints={"pv_output_kw": pv_output_kw, "demand_kw": demand_kw},
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)
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# Simple LocalProblem dictionary representation
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return lp.to_dict()
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from typing import Dict, Any
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from ..dsl import LocalProblem
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class NeighborhoodBatteryAdapter:
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"""
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Toy adapter for a neighborhood battery manager.
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"""
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def __init__(self, neighborhood_id: str):
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self.neighborhood_id = neighborhood_id
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def map_to_local_problem(self, soc: float, capacity_kwh: float) -> Dict[str, Any]:
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lp = LocalProblem(
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neighborhood_id=self.neighborhood_id,
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objective="minimize_cost",
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data_sources=["neighborhood_battery"],
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constraints={"state_of_charge": soc, "capacity_kwh": capacity_kwh},
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)
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return lp.to_dict()
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"""DSL Sketches for CommonsGrid core primitives.
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This module provides lightweight dataclass-backed DSL primitives that sketch
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the intended canonical representations used for CommunityPolicy, LocalProblem,
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SharedSignals, PlanDelta, PrivacyBudget, and AuditLog blocks.
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These are intentionally small and opinionated scaffolds to bootstrap a DSL
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without pulling in heavy dependencies. They can be extended to integrate with the
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GovernanceLedger and EnergiBridge as the project matures.
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"""
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from __future__ import annotations
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from __future__ import annotations
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from dataclasses import dataclass, field
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from dataclasses import dataclass, field
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from typing import Dict, Any, Optional
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from typing import Any, Dict, List, Optional
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@dataclass
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@dataclass
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class LocalProblemDSL:
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class LocalProblem:
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neighborhood_id: str
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neighborhood_id: str
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demand_kw: float
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objective: str = "minimize_cost"
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pv_kw: float
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data_sources: List[str] = field(default_factory=list)
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storage_kwh: float
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constraints: Dict[str, Any] = field(default_factory=dict)
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metadata: Dict[str, float] = field(default_factory=dict)
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def to_model(self) -> "LocalProblem":
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# Import locally to avoid a hard coupling at import time
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from .models import LocalProblem
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return LocalProblem(
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neighborhood_id=self.neighborhood_id,
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demand_kw=self.demand_kw,
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pv_kw=self.pv_kw,
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storage_kwh=self.storage_kwh,
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evs=0,
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metadata=self.metadata,
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)
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def to_dict(self) -> Dict[str, Any]:
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return {
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"type": "LocalProblem",
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"neighborhood_id": self.neighborhood_id,
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"objective": self.objective,
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"data_sources": self.data_sources,
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"constraints": self.constraints,
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}
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@dataclass
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@dataclass
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class SharedSignalsDSL:
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class SharedSignals:
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weather_forecast: Dict[str, float] = field(default_factory=dict)
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signals: Dict[str, Any] = field(default_factory=dict)
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demand_signals: Dict[str, float] = field(default_factory=dict)
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privacy_budget: Optional[float] = None
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def to_dict(self) -> Dict[str, Any]:
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return {
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"type": "SharedSignals",
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"signals": self.signals,
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"privacy_budget": self.privacy_budget,
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}
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@dataclass
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@dataclass
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class PlanDeltaDSL:
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class PlanDelta:
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delta_kw: float
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delta_pv: float
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description: Optional[str] = None
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@dataclass
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class PrivacyBudgetDSL:
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total_budget: float
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spent: float = 0.0
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def spend(self, amount: float) -> bool:
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if self.spent + amount > self.total_budget:
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return False
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self.spent += amount
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return True
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def remaining(self) -> float:
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return max(self.total_budget - self.spent, 0.0)
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@dataclass
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class AuditLogBlock:
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entry: str
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timestamp: float
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timestamp: float
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block_hash: str
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delta: Dict[str, Any]
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def to_dict(self) -> Dict[str, Any]:
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return {"type": "PlanDelta", "timestamp": self.timestamp, "delta": self.delta}
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@dataclass
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class PrivacyBudget:
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signal: str
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budget: float
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def to_dict(self) -> Dict[str, Any]:
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return {"type": "PrivacyBudget", "signal": self.signal, "budget": self.budget}
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@dataclass
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class AuditLog:
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entries: List[Dict[str, Any]] = field(default_factory=list)
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def add(self, entry: Dict[str, Any]) -> None:
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self.entries.append(entry)
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def to_dict(self) -> Dict[str, Any]:
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return {"type": "AuditLog", "entries": self.entries}
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__all__ = ["LocalProblem", "SharedSignals", "PlanDelta", "PrivacyBudget", "AuditLog"]
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