A generic, domain-agnostic pipeline for running constraint-modelling and planning solvers: Conjure / Savile Row (+ SAT/CP backends), Fast Downward, SymK, ENHSP, and UPF-constructed models. It handles the mechanics that every such run needs — building solver command lines from a model registry, spawning subprocesses with timeouts and clean teardown, naming the per-run files, parsing solver output into a uniform timing / cost-layer model, and driving the horizon (increasing-difficulty) loop.
It carries no notion of any particular problem domain or objective. A consumer supplies:
- its own model registry (a
models.yaml) via a config path — the loader is generic, the model content is the consumer's; - its scoring / objective strategy via injection — the core reports the raw objective a solver emits and lets the consumer interpret it (is-this-an- optimisation-model, how to read the objective, any reporting multiplier).
Alpha. The pipeline is in day-to-day use by two consumers and is covered by its own test suite, but this is the first public release and the API may still shift between 0.x versions.
The package ships unwired: a bare import solver_support gives a pipeline
that resolves no model registry and interprets no objective, because it has no
way to guess either. A consumer registers its scoring, registry paths, warning
logger and UPF CLI once, before first use.
pip install solver-supportRequires Python 3.9 or newer (3.9.6 is the system Python on macOS, and is
supported deliberately). The only runtime dependencies are psutil and PyYAML.
See docs/injection-api.md
for the four injection points a consumer wires — model-registry paths, objective
extraction, warning logger, UPF CLI — with a worked example.
injection-api.md— the four seams a consumer wires.solver-runner.md— running a solver as a subprocess:SolverResult, timeout vs duration, phases.timing-model.md— how solver timing is recorded, how the backends map onto one shape, and the invariants parsers rely on.
Clone and install editable. A consumer under development alongside it is normally installed into the same virtualenv, so both are importable and edits to either take effect immediately:
git clone https://github.com/ott2/solver-support
pip install -e solver-supportpytest tests/ — the core's own suite, and the home for solver-level
development. It runs against solver_support alone: no consumer need be
installed, and none is imported.
Since the core ships unwired, a test that needs a seam wired wires a stand-in
(tests/conftest.py):
| fixture | supplies |
|---|---|
fixture_registry |
a ModelRegistry over tests/fixtures/models.yaml, this suite's own synthetic config — never a consumer's |
wired_stdout_score |
a consumer-style Score: N extractor, so a score reaches solver_stats |
wired_timeout_score |
a consumer-style extractor for a salvaged timeout solution |
Wiring a fixture config rather than mocking the registry keeps the real loader
and accessors in the path. Anything a test needs from the registry goes in
tests/fixtures/models.yaml, keeping its shape faithful to a real consumer
config — that shape is the contract the loader implements.
BSD-3-Clause — see
LICENSE.
By András Salamon, with Claude Opus 4.8 and 5.