slurmate 0.2.1

Interactive TUI wizard for generating and submitting Slurm sbatch scripts

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⚡ Stop hand-writing sbatch scripts. Let the wizard do it.

A fast, friendly TUI wizard + CLI that builds and submits Slurm batch jobs — on any cluster, as long as sbatch is on your PATH.

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✨ Why Slurmate?

Writing #SBATCH headers by hand is fiddly and error-prone: which partition has H100s? what's the memory limit? did I get the --gres syntax right for this cluster? Slurmate turns that into a guided conversation — it reads your cluster live, validates as you go, and hands you a clean, ready-to-submit script.

slurmate

That's it. Answer a few prompts, watch the script build itself in a live preview, and submit — or save it for later.

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🚀 Quick start

# Recommended: isolated install
pipx install slurmate

# or plain pip
pip install slurmate

Install from source / for development

git clone https://github.com/PursuitOfDataScience/slurmate.git
cd slurmate
pip install -e ".[dev]"     # editable + dev tools (pytest, ruff, mypy)

Interactive mode (the TUI)

slurmate

A full-screen wizard walks you through name → resources → environment → command. The generated script grows live in a preview pane as you answer. A final Review & Submit screen shows your full configuration and the generated script side by side, then a single menu lets you submit, go back to edit your answers, open the script in $EDITOR, save it, or quit.

💡 You can leave any step blank and come back to it — anything still missing is flagged before you submit. Esc / Shift+Tab go back at any step (including from the action menu, to re-edit your answers); navigation is fully keyboard-driven.

Batch mode (scriptable, no TUI)

slurmate \
  --job-name train_job \
  --partition gpu \
  --cpus 8 --memory 32G --time 04:00:00 \
  --gpus 1 --gpu-type h100 \
  --command "python train.py"

Submit immediately, no prompts:

slurmate --partition gpu --command "python train.py" --yes

Just want the script? Print it (great for piping or CI):

slurmate --partition gpu --command "python train.py" --print > job.sbatch

Run slurmate --help for the full flag list.

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🎯 Features

🧠 Live cluster awareness	Pulls real partitions, GPU types, QoS, accounts, conda envs, and modules from sinfo / scontrol / sacctmgr / conda.
👀 Live preview	The #SBATCH script builds incrementally as you answer — what you see is exactly what gets submitted.
🛡️ Partition-aware validation	Inline warnings when CPU / memory / time / GPU requests exceed the selected partition's limits.
📁 Path autocomplete	Tab-complete file paths while typing your command, virtualenv path, or output files — no more retyping long project paths.
↩️ Skip & come back	Leave steps blank, navigate freely with Esc, and get reminded of anything missing before submit.
📋 Copy-friendly	Mouse capture is off so you can select/copy the preview natively; navigation is fully keyboard-driven.
🧩 Cluster-agnostic GPU syntax	Choose --gres=gpu:type:N, --gres + --constraint, or --gpus to match your site.
🐍 Env activation	Conda, Mamba, virtualenv, or none — generated automatically.
🗂️ Smart output paths	Set a custom log name/pattern (%j = job ID); error path is derived and log dirs are auto-created.
♻️ Reproducible	Every submission is saved locally as <job>-<job-id>.sh; you can also save manually or edit in $EDITOR before submitting.
🧪 Safe to explore	No Slurm? It falls back to realistic mock data so you can try the whole flow anywhere.

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⚙️ Configuration file

Stop retyping the same account and partition every run. Slurmate reads defaults from a TOML file (first match wins):

1. .slurmate.toml in the current directory
2. ~/.config/slurmate/config.toml

These prefill the wizard and act as fallbacks in batch mode. Explicit CLI flags always win.

# .slurmate.toml — keys may be top-level or under a [defaults] table
account     = "my_lab"
partition   = "gpu-shared"
cpus        = 8
memory      = "32G"
time_limit  = "04:00:00"
gpu_format  = "gres_type"            # gres_type | constraint | gpus
env_type    = "conda"                # conda | mamba | venv | none
modules     = ["cuda/12.1", "gcc/9.3.0"]
output_dir  = "logs"

Recognized keys: job_name, account, partition, qos, cpus, memory, time_limit, nodes, ntasks_per_node, gpus, gpu_type, gpu_format, array_spec, modules, env_type, env_name, output_dir, output_file, command, custom_sbatch.

Real TOML is used when available (tomllib on 3.11+, tomli otherwise); without either, a minimal flat key = value reader is used as a fallback.

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🔧 Environment variables

Variable	Effect
SLURMATE_MOCK=1	Force mock mode even when Slurm is installed (great for demos/tests).
SLURMATE_GPU_FORMAT	Default GPU syntax: gres_type (default) · constraint · gpus.
SLURMATE_LOG_DIR=…	Save a copy of every submitted script there for reproducibility.
SLURMATE_NO_BANNER=1	Hide the startup banner.
SLURMATE_BANNER_ANIMATE=1	Force the animated banner even when not a TTY.
SLURMATE_DEBUG=1	Verbose debug logging.

NO_COLOR and non-TTY output are respected automatically.

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🛠️ How it works

1. Gather — query the cluster (or fall back to mock data) for partitions, limits, GPU types, environments, and modules.
2. Guide — a keyboard-first wizard collects name, resources, dependencies, and the command, validating against the chosen partition as you go.
3. Generate & submit — produce a clean #SBATCH script, optionally edit it in $EDITOR, then pipe it straight to sbatch (or save / print it).

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🧪 Status

Slurmate is experimental and pre-1.0 — the CLI, config keys, and defaults may change between releases. It's already useful day-to-day; pin a version if you script around it. Bug reports and cluster-specific quirks are very welcome.

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🤝 Contributing

Issues and PRs are welcome! For local development:

pip install -e ".[dev]"
ruff check src/        # lint
mypy src/              # types (strict)
pytest                 # tests

CI runs the same three checks on Python 3.10–3.12 for every push and PR.

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📄 License

Released under the MIT License.