spec-objects-safety
Index of artifacts in this directory.
Open source Repository Open in the app JSON README (API)
About
# spec-objects-safety
## Contents
* [spec.md](./spec.md)
* [tests.md](./tests.md)
* [stakeholder](./stakeholder/index.md)
* [usecase](./usecase/index.md)
* [functional](./functional/index.md)
* [non-functional](./non-functional/index.md)
* [integration](./integration/index.md)
Details
- Kind
- OKF bundles
- Topic
- Files & documents
- Publisher
- agent-ix
- Origin
- okf_github
- Category
- dados
- Version
- 0.1
- Last push
- 2026-09-04T22:05:42Z
- Repository state
- ativo
- Language
- Python
- License
- AGPL-3.0
- Added
- 2026-09-08 09:04:14
- Updated
- 2026-09-08 09:04:14
- Origin id
agent-ix/spec-objects-safety:spec/index.md
README
# 🐍 spec-objects-safety > Filament Module: safety ObjectTypes (hazard, failure_mode) — IEC 61508 / ISO 26262 / FMEA --- ## 🧭 What this module ships The package root **is** the Filament module. `spec_objects_safety/manifest.yaml` declares two object types — `hazard` (a system state that can lead to harm) and `failure_mode` (the manner in which a component fails) — with their body contracts, their authoring skeletons, the domain lexicon, and the `traceability` model that reports a hazard nothing mitigates. Since 0.3.0 it is a **semantic module** (quoin FR-070): the archetypes are authored in `typespec/main.tsp` against `@agent-ix/semantic-core`, emitted to JSON Schema 2020-12 under `spec_objects_safety/schemas/`, and referenced from the manifest by path and digest. The rule those schemas exist to enforce: every scored axis — severity, likelihood, ISO 26262 exposure and controllability, FMEA detection — admits either its own ordinal scale **or** one of `unknown`, `not_assessed`, `not_applicable`. Those three share no member with any scale, so an axis nobody looked at can never be read, sorted or scored as a safe one. Nothing here defaults a safety judgement, and `status: accepted` requires a `provenance` naming who accepted the risk and when. ### Working on the schemas ```bash make schemas # re-emit spec_objects_safety/schemas/ from typespec/main.tsp make schemas-check # fail on schema or digest drift (also run by `make lint`) make dev-quire # install the Quire wheel the semantic tests need ``` `make schemas` needs `npm ci` first and a user-level npm config that routes `@agent-ix` to npm.ix; the repository carries no `.npmrc`. A wrong schema is fixed in `typespec/main.tsp` and regenerated — never hand-edited. `make dev-quire` exists because the Quire build exposing `extract_semantic` is on no index this repository may commit a dependency against (`agent-ix/quire-rs#392`). Without it the semantic tests **fail**; they never skip, because a skipped row is not coverage. --- ## 📐 Project Structure and Development Philosophy - **Library Name:** `spec_objects_safety` - **Layout:** Flat project layout (package at root, no `src/`) - **Language:** Python 3.13+ - **Dependency Management:** [Poetry](https://python-poetry.org/) - **Build and CI:** GitHub Actions - **Publishing:** Google Artifact Registry (PyPI-compatible) --- ## 🛠 Prerequisites - **Python 3.13+** installed on your system - **Poetry 2.x** installed (`pip install poetry` or [official installer](https://python-poetry.org/docs/#installation)) - **devpi-client** (optional, for local publishing): `pip install devpi-client` --- ## 🚀 Quick Start ```bash # Install dependencies and create venv make install # Run tests make test # Format code make format # Lint code make lint # Build distribution make build ``` --- ## 📦 Build Process - **Local Development**: - `make install` - Install dependencies in Poetry venv - `make test` - Run tests - `make format` - Auto-format code (Black + Ruff) - `make lint` - Run linting checks - **Artifact Building**: - `make build` - Build wheel and sdist under `dist/` - **Artifact Upload**: - Artifacts uploaded via `twine upload` in CI --- ## 🚀 Continuous Integration (CI) - **GitHub Actions Workflow**: - Triggers: `push`, `pull_request`, `tag v*.*.*` - Runs tests and lint checks - Builds artifacts with `poetry build` - Publishes to Google Artifact Registry using `twine upload -r internal-pypi` --- ## 🔑 Required GitHub Secrets | Secret Name | Purpose | |:------------|:--------| | `GCP_SERVICE_ACCOUNT_KEY` | Raw JSON of GCP Service Account Key | | Variable Name | Purpose | |:------------|:--------| | `GCP_REGION` | GCP Region for Artifact Registry (e.g., `us-west1`) | | `GCP_PROJECT_NAME` | GCP Project ID (e.g., `agent-ix`) | | `GCP_PYPI` | Artifact Registry repository name (e.g., `internal-pypi`) | --- ## 🐳 Makefile Targets | Target | Description | |:-------|:------------| | `install` | Install dependencies in Poetry venv | | `build` | Build wheel and sdist artifacts | | `test` | Run tests | | `lint` | Run linting (Ruff + Black check + schema drift gate) | | `schemas` | Re-emit `spec_objects_safety/schemas/` from `typespec/main.tsp` | | `schemas-check` | Fail on schema or manifest-digest drift | | `dev-quire` | Install the Quire wheel the semantic tests need | | `format` | Auto-format code (Black + Ruff --fix) | | `shell` | Open Poetry shell | | `clean` | Remove all build artifacts | | `version` | Show project version | | `info` | Show Git and version info | | `update-lock` | Update poetry.lock | | `update-packages` | Update all dependencies | | `add-package p=<name>` | Add a production dependency | | `add-dev-package p=<name>` | Add a dev dependency | | `local-publish` | Build and publish to local PyPI | --- ## 🏠 Local Development with Local PyPI For local development and testing, you can publish packages to the local PyPI proxy. ### Prerequisites 1. **Local Kubernetes cluster** running with PyPI proxy: ```bash # In the local repo make up make pypi-up ``` 2. **devpi-client** installed locally: ```bash pip install devpi-client ``` ### Publishing Locally ```bash make local-publish ``` ### Installing from Local PyPI ```bash pip install --index-url http://pypi.ix/root/dev/+simple/ spec_objects_safety ``` --- ## 📜 Design Philosophy - Native Poetry-based development (no Docker required for development) - Isolated Poetry virtualenv (no global pip pollution) - Direct uploads to Artifact Registry using correct PyPI-style authentication - Always source-driven — no hand-editing built artifacts - Dynamic, Git-tag-based versioning - Clear Makefile and CI workflows matching production standards ---