ofplang schedule
A scheduler for Object-flow Programming Language v0 — a YAML-based dataflow workflow IR with linear Object tracking. The language is defined in the ofplang/spec repository.
The scheduler takes a portable v0 workflow plus an execution environment definition and plans when its work runs; it also replans from an execution status. The design is documented in docs/SPECIFICATIONS.md.
Status: the schema validators (environment definition and execution document, spec §9) and the scheduler are implemented: it produces an optimal plan for a single workflow with mode selection, spot/device occupancy, and transport, pins a workflow's boundary material to spots via an
interface(spec §6.8), respects device-local consumable resources — what a mode draws and what a replenishment puts back (spec §4.7) — and replans from an execution document (--document) by fixing completed/running activities and re-optimising the rest at or afternow. Avisualizecommand renders a plan as a self-contained SVG/HTML Gantt chart. The model is documented in docs/FORMULATION.md.
This is a fresh implementation that targets the spec directly. The prototype
ofp-scheduler (OR-Tools CP-SAT) is a reference
for ideas but not a dependency.
Install
pip install ofplang-schedule
Requires Python 3.10+. Runtime dependencies are PyYAML, OR-Tools (the CP-SAT
solver used by the scheduler), and the sibling
ofplang-validate (pulled in
automatically), which the CLI's front-door check uses. The scheduler library
never imports validate, so embedders that only call ofplang.schedule take no
validation overhead.
For development, install editable with the test extra from a clone:
pip install -e ".[test]"
Command line
ofp-schedule validate <file>... # validate an environment or a plan/status
ofp-schedule schedule <workflow> --env <env> [--document doc.yaml] [--running-margin N] [--seed N] [--no-validate] [-o plan.yaml] [--format yaml|json]
ofp-schedule visualize <plan|status> [--view device|workflow|lane] [--theme light|dark|auto] [--format svg|html] [-o FILE]
validate auto-detects whether the file is an environment definition or an
execution document (pass --kind to force it); diagnostics are reported as
file:line:col: <severity> <code>. schedule produces an execution plan (§6),
minimising the objective the document declares (§4.8; makespan, then the number of
refills). A --document (execution document, §6) supplies the interface boundary
constraint (§6.8, where a workflow's entry inputs / final outputs sit), the
inventories a run starts with (§6.10) where devices hold consumables, the
objective (§6.1, now its only declaration site) and, when it sets now, the prior status to replan from (§7) —
emitting the full timeline (fixed history + re-optimised future) that round-trips
as the next status input. By default the solve is non-deterministic
(a multi-worker search that may return a different equally-optimal schedule each
run); --seed N makes it reproducible by fixing the CP-SAT seed and using a
single worker. --ignore-resources switches consumables off (§4.7.3): the
declarations are still checked for shape but nothing is applied, and the plan is
shaped as it would be from an environment that never declared one — a relaxation,
so it never turns a solvable instance unsolvable. --no-validate skips the one-shot ofplang-validate front-door
check of the workflow — use it when the workflow was already validated upstream
(e.g. by the ofp umbrella CLI); $import is still resolved, since that is
structural rather than a validation check. visualize renders any §6 execution
document — a plan, or the status a finished run produced — as a self-contained
Gantt chart, either SVG (fixed colours, transparent background, PowerPoint-safe)
or HTML. --format chooses; without it the output is SVG, except that an -o
path ending in .html or .htm is taken as asking for HTML, and an explicit
--format always wins — --format svg -o chart.html writes SVG. Exit codes:
0 success, 1 validation errors or no feasible schedule, 2 usage/input
error.
This tool is also the schedule subcommand of the umbrella ofp CLI
(ofplang), which forwards to it in-process
with this CLI's own subcommands intact: ofp schedule schedule …,
ofp schedule visualize …, each with the same options and exit codes as above.
Feature support
v0 defines seven optional features (spec §4.2), and a document requiring one an
implementation does not have "is valid v0 but unsupported by that implementation"
(§4.1). So ofp-validate accepting a workflow does not mean this scheduler can
plan it:
| v0 feature | ofplang-schedule |
|---|---|
python_script_processes |
Supported. A script process is scheduled like any atomic one; its mode duration is the estimate of the compute cost. Running the script is the runner's job. |
scheduling_policies |
Accepted, then ignored: §23 makes these best-effort preferences, and a composite's scheduling section is dropped when the composite is flattened. The report's diagnostics carry a scheduling_policies_ignored warning. |
node_map, node_fold, node_do_while, node_branch |
Not supported. A structured node reshapes dataflow in ways the flat scheduler graph cannot represent, so it is refused with unsupported_feature. |
generic_processes |
Not supported. Refused with unsupported_feature. |
Library
from ofplang.schedule import schedule
report = schedule(workflow, environment, document_path=status) # -> ScheduleReport
Each input is either a path or an already-loaded document (a mapping), so an
embedder that holds them in memory — a rolling-horizon runner rendering a fresh
status every replan — passes them straight in, with no temporary files and nothing
re-parsed. An in-memory document is read, never written to, and the plan it
produces shares no structure with it. Because such a document has no file to point
at, its diagnostics carry no file:line:col and locate by their path instead,
and the plan's meta provenance reads <in-memory> unless the caller names the
original file (workflow_source / environment_source / document_source).
The package lives under the ofplang PEP 420 namespace (ofplang.schedule),
shared across the organization's tools.
Examples
examples/ holds complete workflow + environment pairs used
to drive and eyeball the scheduler: a minimal source → target, a workflow with
boundary material pinned by an interface, two jobs on a two-transporter fleet, a
plate-reformatting DAG, and a parametric generator that scales the instance up.
Each comes with its solved plan and a rendered chart under examples/outputs/.
Tests
pytest
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