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Version: v0.3.0

FAQ

Why don’t --resume / --task work?​

Because the current CLI/implementation explicitly marks them as “not implemented yet”; calling them errors immediately:

  • sflow run --resume ...: NotImplementedError
  • sflow run --task ...: typer.BadParameter

This guide treats them as planned features, not currently supported behavior.

Why does --set say the variable doesn't exist?​

Today, --set KEY=VALUE only overrides variables already declared in the config file. If you want a new variable, you must declare it under variables: first (even with a default value).

Does dry-run create output directories?​

No. Dry-run computes planned output paths but does not mkdir or write log files.

Do artifacts automatically download from HuggingFace / pull Docker images?​

In v0.1, only fs:// / file:// are resolved to real local paths. Other schemes are kept as strings (no download/pull behavior yet).

Visualization to png/svg/pdf fails: dot not found?​

That output format depends on Graphviz. You can:

  • Install Graphviz (provides dot)
  • Or use --format mermaid / --format dot

How do I check which sflow version I'm running?​

Run sflow --version (or sflow -V). It prints the package version plus runtime/build details — binary path, Python path, install mode, source label, repo path, and git branch/commit when available. Each sflow run logs the same details, which helps confirm whether a local editable checkout, a branch build, or a released package is running.

How do I restrict a run to (or away from) specific nodes?​

Use --include-nodes to pin a run to a set of hosts, or --exclude-nodes to keep it off flaky ones. Both work on sflow run and sflow batch, accept comma-separated and/or repeated values, and apply to whatever backend the recipe uses. You can also set include_nodes / exclude_nodes on a backend in YAML; CLI values are unioned with the recipe's. See Backends.

How do I pass extra flags to the backend (salloc / docker run / kubectl)?​

Use the generic --extra-args / -e to forward a flag to whichever backend the recipe uses — it is merged into each Slurm backend's salloc, each docker backend's docker run, and every kubectl call. For backend-specific flags use --extra-salloc-args, --extra-docker-args, or --extra-kubectl-args; the more specific form wins on a conflicting option, and CLI values win over the recipe.

How do I connect to a Kubernetes cluster?​

Kube access is provided by CLI flags, so the recipe stays cluster-agnostic: --kubeconfig, --kube-context, and --kube-namespace select the cluster and namespace, while --kube-node-selector, --kube-compute-domain-channel, and --kube-compute-domain-create / --no-kube-compute-domain-create tune placement and Multi-Node NVLink. Credentials always live in the kubeconfig, never in YAML. See Backends.

How do I install sflow from a private PyPI index in batch mode?​

Pass --sflow-index-url <url> to sflow batch (e.g. an Artifactory registry). When it's set, --sflow-version is interpreted as a PyPI version specifier: a bare version is pinned (0.3.0 → sflow==0.3.0), an operator spec (>=0.3,<0.4) is passed through, and omitting it installs the latest available. Credentials must be available on the compute node via ~/.netrc or a credential helper (URLs with embedded credentials are rejected).

What does --sflow-venv-path do in sflow batch?​

It's the parent directory under which each Slurm job builds its own fresh, disposable per-job venv (.sflow_venv-<job id>/), installs sflow into it, and removes it when the job exits. The venv is built on the compute node with the node's python3, so it always matches the node architecture (x86/arm). It defaults to compute-node-local scratch; pass a shared-filesystem path to override.

Which optional extras can I install?​

  • pip install 'sflow[s3]' — S3 artifact/result uploads (credentials from the boto3 default chain).
  • pip install 'sflow[monitor]' — PNG charts for the hardware monitor.

How do I get the AI-agent skills for writing sflow YAML?​

Run sflow skill to copy the bundled agent skills into your project (sflow skill --list to see them, -o <dir> to choose the output directory). These teach coding agents how to author sflow YAML and diagnose failed runs.