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name: cli-workflows description: "Use Dipy console entry points, workflow parser behavior, and safe CLI probes." disable-model-invocation: true metadata: disco-role: operating license: NOASSERTION

Dipy CLI Workflows

Use this sub-skill when a task asks for Dipy command-line entry points, dipy_* workflow discovery, help/version probes, workflow parser behavior, output naming, or translation between an API recipe and a command-line workflow. Dipy exposes 61 current console entry points through dipy.workflows.cli:run; each command dispatches to a workflow class through dipy.workflows.cli.cli_flows.

Quick Start

1. Start with references/cli-reference.md to choose the command family and route scientific details to the owning Dipy sub-skill.
2. Run python scripts/dipy_cli_probe.py --format text to list installed flows from the Python API without network access.
3. Run python scripts/dipy_cli_probe.py --check-help dipy_info dipy_fit_dti --timeout 8 --format json before trusting shell entry points in a new environment.
4. Use references/workflow-parser.md when explaining positional arguments, optional flags, out_dir, out_*, --force, --out_strat, --mix_names, logging, or sub-workflow flags.
5. Use references/troubleshooting.md when a command is missing, optional dependencies are unavailable, help exits unexpectedly, or deprecated aliases appear.

Routing

• Use ../io-data/ for b-values/b-vectors, gradient tables, NIfTI, tractogram, PAM, fetch, split, extract, conversion, and data-shape questions.
• Use ../reconstruction-models/ for dipy_fit_* model choice, metric interpretation, ODF/peaks, tensor/CSD/DKI/DSI/GQI/MAPMRI/SFM details, and dipy_fit_dti parameter meaning.
• Use ../denoising-preprocessing/ for NLMeans, LPCA, MPPCA, Patch2Self, Gibbs removal, motion-prep, masks, and bias-correction caveats.
• Use ../registration-alignment/ for affine/SyN registration, apply-transform, motion correction, reslice, SLR, and BundleWarp details.
• Use ../tracking-segmentation/ for tracking, PFT, RecoBundles, LabelsBundles, clustering, masks, tissue classification, BUAN, and streamline outputs.

Safe CLI Pattern

python scripts/dipy_cli_probe.py --format text
python scripts/dipy_cli_probe.py --check-help dipy_info dipy_fit_dti --timeout 8 --format json
COMMAND --help
COMMAND --version
COMMAND inputs... --out_dir outputs --log_level INFO --log_file run.log

Prefer --help first because Dipy builds each command parser from the workflow class docstring and signature. Use explicit --out_dir and output filenames for reproducible paths; add --force only when overwriting expected outputs is safe.

Important Version Facts

• The inspected Dipy runtime is 1.13.0.dev0+git20260617.ac9380d; the distribution version is 1.13.0.dev0.
• cli_flows values are (module_name, class_name) tuples, not class objects.
• The correct peaks API import is dipy.direction.peaks.peaks_from_model; route peaks/model questions to ../reconstruction-models/.
• Base installation lacks fury, matplotlib, torch, and tensorflow; visualization and neural-network workflows are optional surfaces.
• dipy_sh_convert_mrtrix is deprecated; prefer dipy_convert_sh when converting spherical harmonics.

Bundled References

• references/cli-reference.md catalogs all current CLI commands by task family and gives API-to-CLI routing hints.
• references/workflow-parser.md explains how Dipy turns workflow run signatures and NumPy-style docstrings into argparse CLIs.
• references/troubleshooting.md covers missing commands, optional dependencies, parser surprises, output overwrites, and deprecated aliases.
• scripts/dipy_cli_probe.py lists installed cli_flows and can run bounded --help checks for selected entry points.