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Horus Runtime

Reproducible scientific workflows, from your laptop to the HPC cluster.

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Horus Runtime is the open-source engine behind the Temple Compute platform: you describe a pipeline once, in YAML or Python, and run it wherever the compute lives. It tracks every artifact a task produces, moves those artifacts between machines for you, and skips work that is already done when you run it again.

Horus Runtime TUI

Quickstart

Install it:

uv add horus-runtime     # or: pip install horus-runtime

Save this as workflow.yaml:

name: example_pipeline
kind: horus_workflow

tasks:
  - id: producer
    name: Produce data
    kind: horus_task
    runtime:
      kind: command
      # $data renders to the on-target path of the "data" output artifact.
      command: "mkdir -p /tmp/horus_example && echo 42 > $data"
    executor:
      kind: shell
    target:
      kind: local
    outputs:
      - id: data
        kind: file
        path: /tmp/horus_example/data.txt

  - id: consumer
    name: Summarize data
    kind: horus_task
    runtime:
      kind: command
      command: "wc -l ${data_in} > $summary"
    executor:
      kind: shell
    target:
      kind: local
    inputs:
      - id: data_in
        kind: file
        path: /tmp/horus_example/data.txt
    outputs:
      - id: summary
        kind: file
        path: /tmp/horus_example/summary.txt

# Edges are the DAG: producer.data feeds consumer.data_in, so producer runs
# first and its output is transferred before the consumer starts.
edges:
  - source: producer
    source_output: data
    target: consumer
    target_input: data_in

Run it:

horus run workflow.yaml
[HorusTask._run] Task Produce data started.
[TaskTimeMiddleware.after] Task Produce data completed in 0.01 seconds.
[HorusTask._run] Task Summarize data started.
[TaskTimeMiddleware.after] Task Summarize data completed in 0.03 seconds.
[WorkflowTimeMiddleware.after] Workflow example_pipeline completed in 0.05 seconds.

Run it a second time and nothing re-executes, because both tasks' output artifacts already exist:

[BaseTask.run] Skipping task Produce data. Already complete.
[BaseTask.run] Skipping task Summarize data. Already complete.

Delete the outputs, or pass --no-skip-all, to force a fresh run.

Why Horus

  • Write once, run anywhere. A task declares what to run (runtime), how to run it (executor), and where (target). Moving a stage from your laptop to a SLURM cluster is a change to the target block, not a rewrite.
  • Artifacts, not filenames. Inputs and outputs are typed, addressable objects. Horus resolves them into your commands, transfers them between targets when an edge crosses machines, and knows when they already exist.
  • Restartable by default. Completed tasks are skipped on re-run, so a pipeline that failed at hour nine picks up at hour nine.
  • Everything is a plugin. Targets, runtimes, executors, artifacts, tasks, transfer strategies, and middleware are all registered kinds. Adding one is a package with an entry point, never a fork.
  • Built for real science. Resource requests, subworkflows, mapped fan-out, run packaging, and a live TUI, driven from a file you can commit and diff.

CLI

Command What it does
horus run WORKFLOW_YAML Execute the workflow. --trigger picks the starting task, --no-tui streams plain logs, --no-skip TASK_ID / --no-skip-all force re-runs, --debug turns on debug logging.
horus package WORKFLOW_YAML Bundle the workflow and every file it references into a zip, so it runs on a machine that never had your directory.
horus sanitize WORKFLOW_YAML Promote implicit root inputs into declared top-level artifacts, which is what lets a UI offer them as workflow inputs.

Full CLI and SDK reference: docs.templecompute.com.

Built-in kinds

Everything below ships with the runtime and is usable straight after install.

Category Kinds
Targets local
Runtimes command, python, python_string, python_script
Executors shell, python_exec, python_fn, python_fn_external
Artifacts file, folder, json, pickle, number, boolean, string
Tasks horus_task, subworkflow
Workflows horus_workflow

Ecosystem

Official plugins, installable alongside the runtime:

Plugin Adds
horus-slurm Run tasks as SLURM jobs on an HPC cluster.
horus-docker Execute tasks inside Docker containers.
horus-singularity Execute tasks inside Singularity/Apptainer containers.
horus-environments Auto-provision per-task Python environments with uv or conda.

And for ready-made science: Pantheon is a curated library of production workflows, from drug discovery (Boltz-2 virtual screening, AutoDock Vina docking) to molecular dynamics setup with BioExcel Building Blocks (GROMACS, AMBER). Contributions welcome there too.

Writing your own plugin

A plugin is an ordinary Python package that declares a horus.* entry point:

[project.entry-points."horus.target"]
my_cluster = "my_package.target"

Once installed, kind: my_cluster works in any workflow. Start from the plugin template and see the SDK docs for the base classes.

Contributing

Contributions are very welcome, from bug reports to new plugins.

Found a security issue? Please follow SECURITY.md instead of opening an issue.

Funding & Credits

Developed by Temple Compute.

License

horus-runtime is licensed under the GNU Affero General Public License v3.0 (AGPL-3.0). See the LICENSE file for details.

For commercial licensing and support, contact Temple Compute at christian@templecompute.com.

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