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, the CLI and the bindings' plumbing stay as they are.

Build

cargo build --release              # library + `modelo` binary
cargo test                         # unit + integration tests (203 tests)
cargo clippy --all-targets         # lints
cargo doc --open                   # API documentation

The Python extension module is behind a feature flag, so the binary never links against libpython:

cargo build --release --features python

Validating files: the `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's ValidatedIntEnum.
Unknown fields are rejected wherever python-ort sets extra="forbid", and accepted where it sets extra="allow"/"ignore".
Loose scalars are coerced as python-ort's mode="before" validators do (an integer start_lines, non-string options values).

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/

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python-modelo 0.5.0

modelo

Namespaces

Build

Validating files: the modelo CLI

Interactive TUI

Using it from Python

Type checking

Examples

Checking parity against python-ort

Continuous integration

Deployment

PyPI — .github/workflows/release-pypi.yml

crates.io — .github/workflows/release-crates.yml

Local dry runs

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Validating files: the `modelo` CLI

PyPI — `.github/workflows/release-pypi.yml`

crates.io — `.github/workflows/release-crates.yml`

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