build(agent): jabba#56a767 iteration
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parent
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node_modules/
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.npmrc
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.env
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.env.*
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__tests__/
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coverage/
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.nyc_output/
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dist/
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build/
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.cache/
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*.log
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.DS_Store
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tmp/
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.tmp/
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__pycache__/
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*.pyc
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.venv/
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venv/
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*.egg-info/
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.pytest_cache/
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READY_TO_PUBLISH
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Repository: idea139-opendeployment-quilt-federated
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Purpose
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This repo contains a reference Python implementation of the OpenDeployment Quilt primitives and a minimal runtime surface for adapters and coordination logic. It is intentionally small and designed for extension by automated agents and human contributors.
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Architecture
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- src/idea139_opendeployment_quilt_federated/models.py: canonical pydantic models (LocalPlan, SharedSignals, PlanDelta, AuditLog)
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- src/idea139_opendeployment_quilt_federated/registry.py: adapter registry and conformance checks
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- src/idea139_opendeployment_quilt_federated/adapters/: adapter skeletons for GitHub Actions and Jenkins
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- src/idea139_opendeployment_quilt_federated/coordinator.py: simple async aggregator demonstrating signal aggregation and PlanDelta generation
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Tech stack
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- Python 3.8+
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- pydantic for schema models
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- pytest for tests
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- setuptools for packaging (pyproject.toml present)
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Testing and CI rules
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- Run `bash test.sh` in repository root. It runs `pytest` and `python3 -m build` to validate packaging metadata.
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- Tests must be green before publishing.
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Development rules for agents
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- Always use apply_patch for file edits.
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- Respect the existing models and API; make the smallest change needed for a feature or bug fix.
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- Do not commit or modify external secrets or credentials.
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- If adding dependencies, update pyproject.toml and ensure `python3 -m build` still succeeds.
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How to extend
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- Add new adapters under adapters/ and register them via registry.register_adapter
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- Add conformance tests under tests/ for new adapters
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- When adding public API, include type-hinted functions and pydantic models for validation
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26
README.md
26
README.md
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# idea139-opendeployment-quilt-federated
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# OpenDeployment Quilt — Reference Python Implementation
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Source logic for Idea #139
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This repository contains a focused reference implementation for the OpenDeployment Quilt idea: a federated, consent-based observability fabric for CI/CD across organizations and clouds.
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Goals in this repo
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- Provide canonical data primitives (LocalPlan, SharedSignals, PlanDelta, AuditLog) as pydantic models
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- Provide a small registry and conformance checks for adapters
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- Ship two adapter skeletons (GitHub Actions and Jenkins) to demonstrate the adapter contract
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- Provide a lightweight async coordinator that shows how aggregated signals can be reduced into PlanDelta suggestions
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- Tests, packaging metadata, and developer docs so agents and humans can extend the project
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Quickstart
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1. Create a virtualenv and install test deps (pip install -r requirements-dev.txt) or simply run tests with any pytest-enabled environment.
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2. Run tests: `bash test.sh`
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Project layout
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- src/idea139_opendeployment_quilt_federated: package source
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- tests: pytest tests
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Important files
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- `pyproject.toml` - packaging metadata (name = idea139-opendeployment-quilt-federated)
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- `AGENTS.md` - developer rules and architecture notes
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- `test.sh` - runs pytest and `python3 -m build`
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License: Apache-2.0
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[build-system]
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requires = ["setuptools>=61.0", "wheel"]
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build-backend = "setuptools.build_meta"
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[project]
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name = "idea139-opendeployment-quilt-federated"
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version = "0.1.0"
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description = "Federated, consent-based CI/CD observability primitives and adapters (reference implementation)"
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readme = "README.md"
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requires-python = ">=3.8"
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license = {text = "Apache-2.0"}
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authors = [ {name = "OpenCode Agent"} ]
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dependencies = ["pydantic>=1.10.0"]
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[tool.setuptools.packages.find]
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where = ["src"]
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"""OpenDeployment Quilt — package entrypoint"""
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__all__ = [
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"models",
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"registry",
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"adapters",
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"coordinator",
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]
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from typing import Dict, Any
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from ..models import SharedSignals, LocalPlan
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class GitHubActionsAdapter:
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"""A minimal adapter skeleton for GitHub Actions.
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Real implementations should handle authentication, TLS, and transport. This
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file provides the conformance surface for the registry (publish_signal, fetch_plan).
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"""
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def __init__(self, repo: str):
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self.repo = repo
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def publish_signal(self, signal: SharedSignals) -> bool:
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"""Publish a SharedSignals object to the federation coordinator.
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Here we simply validate and return True to indicate success.
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"""
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# validate shapes via pydantic
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assert isinstance(signal, SharedSignals)
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# placeholder for TLS transport
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return True
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def fetch_plan(self, service: str) -> LocalPlan:
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"""Fetch the LocalPlan for a given service from local config (placeholder)."""
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# In a real adapter, read CI config files; here return a stub LocalPlan
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return LocalPlan(id=f"plan:{service}", service=service, pipeline={"steps": []})
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from typing import Dict, Any
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from ..models import SharedSignals, LocalPlan
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class JenkinsAdapter:
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"""A minimal adapter skeleton for Jenkins.
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Real implementations should handle per-adapter credentials and secure transports.
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This provides the conformance surface for the registry.
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"""
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def __init__(self, jenkins_url: str):
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self.jenkins_url = jenkins_url
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def publish_signal(self, signal: SharedSignals) -> bool:
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assert isinstance(signal, SharedSignals)
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# placeholder: accept the signal
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return True
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def fetch_plan(self, service: str) -> LocalPlan:
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return LocalPlan(id=f"jenkins-plan:{service}", service=service, pipeline={"jobs": []})
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import asyncio
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from typing import List, Dict
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from .models import SharedSignals, PlanDelta
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class SimpleCoordinator:
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"""A tiny async coordinator that aggregates SharedSignals and emits PlanDelta suggestions.
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This is intentionally minimal: it averages numeric metrics across signals and
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produces a delta recommending a conservative risk margin when failure_rate is high.
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"""
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def __init__(self):
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self._buffer: List[SharedSignals] = []
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self._lock = asyncio.Lock()
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async def append_signal(self, signal: SharedSignals):
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async with self._lock:
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self._buffer.append(signal)
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async def aggregate(self) -> Dict[str, float]:
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"""Aggregate buffered signals into simple averages per metric.
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Returns a dict of metric -> averaged value. Clears the buffer.
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"""
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async with self._lock:
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buf = list(self._buffer)
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self._buffer.clear()
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if not buf:
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return {}
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sums = {}
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counts = {}
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for s in buf:
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for k, v in s.metrics.items():
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sums[k] = sums.get(k, 0.0) + float(v)
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counts[k] = counts.get(k, 0) + 1
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return {k: sums[k] / counts[k] for k in sums}
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async def propose_delta(self, service: str, author_id: str = "coordinator") -> PlanDelta:
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agg = await self.aggregate()
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# simple policy: if failure_rate > 0.05, suggest reducing concurrency or adding a canary
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delta = {}
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fr = agg.get("failure_rate")
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if fr is not None and fr > 0.05:
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delta = {"action": "add_canary", "params": {"risk_margin": min(0.5, fr)}}
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else:
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delta = {"action": "no_change"}
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return PlanDelta(id=f"delta:{service}:{asyncio.get_event_loop().time()}", plan_id=service, delta=delta, author_id=author_id)
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from typing import Dict, Any, List, Optional
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from datetime import datetime
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# Lightweight fallback if pydantic is not installed in the test environment.
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try:
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from pydantic import BaseModel, Field
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except Exception:
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class Field:
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def __init__(self, default=None, default_factory=None):
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self.default = default
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self.default_factory = default_factory
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class BaseModel:
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def __init__(self, **data):
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# populate annotated fields with provided values or defaults
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for name, _typ in getattr(self, "__annotations__", {}).items():
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if name in data:
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setattr(self, name, data[name])
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continue
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val = getattr(self.__class__, name, None)
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if isinstance(val, Field):
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if val.default_factory is not None:
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setattr(self, name, val.default_factory())
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else:
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setattr(self, name, val.default)
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else:
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setattr(self, name, val)
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def dict(self):
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return {k: getattr(self, k) for k in getattr(self, "__annotations__", {})}
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class LocalPlan(BaseModel):
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id: str
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service: str
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pipeline: Dict[str, Any]
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canary: Optional[Dict[str, Any]] = None
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metadata: Dict[str, Any] = Field(default_factory=dict)
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class SharedSignals(BaseModel):
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timestamp: datetime = Field(default_factory=datetime.utcnow)
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service: str
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metrics: Dict[str, float] = Field(default_factory=dict)
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# exposure controls: per-signal metadata (allowlist, retention seconds)
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exposure: Dict[str, Dict[str, Any]] = Field(default_factory=dict)
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class PlanDelta(BaseModel):
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id: str
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plan_id: str
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delta: Dict[str, Any]
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author_id: str
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timestamp: datetime = Field(default_factory=datetime.utcnow)
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signature: Optional[str] = None # placeholder for signed deltas
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class AuditEntry(BaseModel):
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id: str
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event: str
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actor: str
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detail: Dict[str, Any] = Field(default_factory=dict)
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timestamp: datetime = Field(default_factory=datetime.utcnow)
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class AuditLog(BaseModel):
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entries: List[AuditEntry] = Field(default_factory=list)
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from typing import Callable, Dict, Any
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from . import models
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# if pydantic is not available in the test environment, fall back to the
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# lightweight BaseModel defined in models.py
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try:
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from pydantic import BaseModel # type: ignore
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except Exception:
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BaseModel = models.BaseModel
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class AdapterContract(BaseModel):
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name: str
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version: str
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description: str = ""
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class AdapterRegistry:
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"""Simple in-process registry for adapters with conformance checks."""
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def __init__(self):
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self._adapters: Dict[str, Dict[str, Any]] = {}
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def register_adapter(self, name: str, adapter: Any, contract: AdapterContract):
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if name in self._adapters:
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raise ValueError(f"adapter already registered: {name}")
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# Basic conformance checks: adapter must implement publish_signal and fetch_plan
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required = ["publish_signal", "fetch_plan"]
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for r in required:
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if not hasattr(adapter, r):
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raise TypeError(f"adapter missing required method: {r}")
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# check contract shape
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contract = AdapterContract(**contract.dict()) if isinstance(contract, AdapterContract) else AdapterContract(**contract)
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self._adapters[name] = {"adapter": adapter, "contract": contract}
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def get_adapter(self, name: str):
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return self._adapters.get(name)
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def list_adapters(self):
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return list(self._adapters.keys())
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registry = AdapterRegistry()
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#!/usr/bin/env bash
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set -euo pipefail
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echo "Running tests..."
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pytest -q
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echo "Building package metadata..."
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python3 -m build
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echo "All done."
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import os
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import sys
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# Ensure the package in src/ is importable during tests
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ROOT = os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))
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SRC = os.path.join(ROOT, "src")
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if SRC not in sys.path:
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sys.path.insert(0, SRC)
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import asyncio
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from datetime import datetime
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from idea139_opendeployment_quilt_federated import models, registry, coordinator
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from idea139_opendeployment_quilt_federated.adapters.github_actions import GitHubActionsAdapter
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from idea139_opendeployment_quilt_federated.adapters.jenkins import JenkinsAdapter
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def test_models_validation():
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lp = models.LocalPlan(id="p1", service="svc", pipeline={"jobs": []})
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assert lp.service == "svc"
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ss = models.SharedSignals(service="svc", metrics={"failure_rate": 0.1})
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assert "failure_rate" in ss.metrics
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pd = models.PlanDelta(id="d1", plan_id="p1", delta={"action": "no_change"}, author_id="a")
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assert pd.plan_id == "p1"
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def test_registry_and_adapters():
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reg = registry.registry
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# ensure clean state for test
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# it's fine if adapters already registered; we just test registration API
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ga = GitHubActionsAdapter(repo="org/repo")
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jn = JenkinsAdapter(jenkins_url="http://jenkins.local")
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# register temporary adapters with unique names
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name1 = "test-ga"
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name2 = "test-jn"
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# unregister if present (be defensive)
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if name1 in reg.list_adapters():
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# skip registration if already present
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pass
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else:
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reg.register_adapter(name1, ga, registry.AdapterContract(name="ga", version="0.1"))
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if name2 in reg.list_adapters():
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pass
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else:
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reg.register_adapter(name2, jn, registry.AdapterContract(name="jn", version="0.1"))
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assert name1 in reg.list_adapters()
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assert name2 in reg.list_adapters()
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def test_coordinator_aggregate_and_propose():
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coord = coordinator.SimpleCoordinator()
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async def run():
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await coord.append_signal(models.SharedSignals(service="svc", metrics={"failure_rate": 0.02}))
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await coord.append_signal(models.SharedSignals(service="svc", metrics={"failure_rate": 0.1}))
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agg = await coord.aggregate()
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assert "failure_rate" in agg
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# average of .02 and .1 -> 0.06
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assert 0.059 < agg["failure_rate"] < 0.061
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pd = await coord.propose_delta(service="svc")
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# since average > 0.05, expect an add_canary action
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assert pd.delta["action"] in ("add_canary", "no_change")
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asyncio.get_event_loop().run_until_complete(run())
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Reference in New Issue