modelo
modelo is a Rust multi-model validation library and a Python bindings extension intended as a drop-in replacement for python-ort.
Namespaces
Each model family lives in its own namespace, so families can be added without disturbing the others. Currently there is one: ort, the OSS Review Toolkit model.
| ORT model | Shared validation engine | |
|---|---|---|
| Rust | modelo::models::ort::* (src/models/ort/) |
modelo::models::{Model, ValidationError} |
| Python | modelo.ort |
— |
Adding a family means a new src/models/<name>/ directory whose types implement
models::Model, plus a modelo.<name> submodule in src/python/mod.rs. The engine and the
bindings' plumbing stay as they are.
Workspace layout
This repository is a Cargo workspace with two crates, so the library stays free of CLI/TUI
dependencies (clap, ratatui, crossterm):
| Crate | Contents | Dependencies |
|---|---|---|
modelo |
The validation engine and models (src/), plus the optional Python bindings |
serde, serde_yaml, thiserror, purl, pyo3 (feature-gated) |
modelo-cli |
The modelo binary: CLI subcommands and the TUI |
modelo, clap, ratatui, crossterm, anyhow |
Build
cargo build --release --workspace # library + `modelo` binary
cargo test --workspace # unit + integration tests (203 tests)
cargo clippy --workspace --all-targets # lints
cargo doc --workspace --open # API documentation
The Python extension module is behind a feature flag on the modelo library crate, so the
modelo binary never links against libpython:
cargo build --release --features python
Validating files: the modelo CLI
The modelo binary lives in the modelo-cli crate:
cargo install modelo-cli
modelo license-classifications tests/data/license-classifications.yml
modelo repository-configuration tests/data/repo_config/curations.yml
modelo ort-result tests/data/evaluation-result.yml
The subcommands are still flat rather than grouped per family (modelo ort ort-result ...); that
regrouping is worth doing when a second family lands, not before.
Each subcommand prints valid <kind> file. and exits 0, or reports the first parse/validation
error and exits non-zero. --debug additionally pretty-prints the parsed model. This is the
equivalent of python-ort's ort-validate (src/tools/ort_validate.py).
Interactive TUI
modelo tui [FILE] (or modelo with no arguments) opens a ratatui interface: pick the model kind,
type a file path, see the validation result. ↑/↓ (or k/j) move and scroll, Enter
confirms, b goes back from the result screen, q/Esc quits.
Using it from Python
pip install modelo
or, from a checkout:
pip install maturin
maturin develop --features python # into the active virtualenv
# or: pip install . # maturin is the build backend
The modelo.ort submodule exposes the three top-level ORT models, each parsed from YAML and
navigated with plain attribute access, the way python-ort's pydantic models are:
from pprint import pprint
from modelo.ort import LicenseClassifications, OrtResult, RepositoryConfiguration
result = OrtResult.from_yaml_file("tests/data/evaluation-result.yml")
config = RepositoryConfiguration.from_yaml_str(open(".ort.yml").read())
pprint(result.analyzer) # AnalyzerRun(start_time=..., ...)
result.analyzer.environment.ort_version
result.analyzer.result.projects[0].id
result.repository.vcs.url
Invalid input raises ValueError (with the failing field path, as pydantic's ValidationError
does); an unreadable path raises OSError.
Every nested model is an instance of a class named after it (type(result.analyzer).__name__ == "AnalyzerRun"), all of them subclasses of modelo.ort.Object. Besides attribute access they
support keys(), values(), items(), obj["field"], "field" in obj, len(obj), == and
to_dict():
import json
result.to_dict() # nested plain dicts and lists
json.loads(result.to_json()) == result.to_dict() # True — one source of truth
Fields that ORT itself serializes as scalars stay scalars: Identifier is a string
("PIP::requirements.txt:1.0"), enums are their member names, and free-form maps such as
labels are dicts.
Type checking
The wheel is a PEP 561 typed package: modelo/py.typed ships alongside modelo/ort.pyi, so mypy,
pyright and ty resolve import modelo.ort and the model classes without falling back to Any.
The compiled extension lives at modelo._modelo; modelo.ort is a thin Python re-export of it, which is
what makes the module statically resolvable.
Examples
Runnable counterparts of python-ort's examples/, using only the standard library:
python examples/license_classifications.py tests/data/license-classifications.yml
python examples/repo_config.py tests/data/repo_config/curations.yml
python examples/ort_result.py tests/data/evaluation-result.yml --analyzer
Checking parity against python-ort
examples/parity_check.py parses every fixture in tests/data/ with both libraries and diffs the
serialized result, ignoring set-backed field ordering (arbitrary in both):
pip install . python-ort
python examples/parity_check.py
All 9 fixtures agree; analyzer-result.yml is rejected by both libraries for the same unknown
field. The behaviours this covers:
- Int-backed enums (
Severity,*Reason, …) accept the numeric value or the case-sensitive member name, and serialize as the member name — python-ort'sValidatedIntEnum. - Unknown fields are rejected wherever python-ort sets
extra="forbid", and accepted where it setsextra="allow"/"ignore". - Loose scalars are coerced as python-ort's
mode="before"validators do (an integerstart_lines, non-stringoptionsvalues).
Continuous integration
.github/workflows/ci.yml runs on every push and pull request: format (rustfmt), lint
(clippy, warnings denied), test (Linux/macOS/Windows), python (bindings built and smoke-tested
on 3.10 and 3.13) and parity (the diff above against python-ort).
Every third-party action is pinned to a full commit SHA with the released tag in a trailing comment
(uses: actions/checkout@3d3c42e... # v7.0.1), so a moving tag cannot change what runs. To bump
one, resolve the new tag's SHA (gh api repos/<owner>/<repo>/commits/<tag> --jq .sha) and update
both the SHA and the comment. actionlint .github/workflows/*.yml validates the files.
Deployment
Both registries publish from a v* tag (git tag -s v0.1.0 && git push origin v0.1.0) or a
manual Run workflow dispatch. Bump the version in Cargo.toml and pyproject.toml first —
they are separate files and must agree.
PyPI — .github/workflows/release-pypi.yml
Builds wheels with maturin-action for Linux (x86_64, aarch64), macOS (x86_64, aarch64) and
Windows (x64), plus an sdist, then uploads everything in one publish job via
pypa/gh-action-pypi-publish (maturin upload only authenticates with an API token, so it cannot
do the OIDC exchange trusted publishing needs).
One-time setup: on PyPI, add a trusted
publisher for the modelo project pointing at this
repository and the workflow file release-pypi.yml with environment pypi; then create a GitHub
environment named pypi. No API token is stored — the job authenticates with the OIDC token from
id-token: write.
crates.io — .github/workflows/release-crates.yml
Runs the test suite and cargo package first, then cargo publish.
One-time setup: create a crates.io API token scoped to publish-update for this crate, and store
it as the secret CARGO_REGISTRY_TOKEN in a GitHub environment named crates-io.
Local dry runs
cargo publish --dry-run
maturin build --release --features python # wheel lands in target/wheels/
License
MIT — see LICENSE. Copyright 2026 Helio Chissini de Castro dev@heliocastro.info.
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