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14. CLI reference

This page is the authoritative CLI reference for ModSSC commands and options. For registry lists and IDs, see Catalogs and registries.

Each command section below follows the same pattern (purpose, syntax, options, examples), so you can skim and copy quickly. Use the navigation to jump to the brick you need.

14.1 How the CLI is installed and invoked

The CLI entry points are defined in pyproject.toml and implemented as Typer apps in src/modssc/cli/. [1][2]

Primary entry point:

modssc --help
modssc --version

Direct entry points (also declared in pyproject.toml): [1]

Use modssc when you want a single entry point with shared logging and doctor. Use the direct entry points when you prefer shorter commands or want to scope scripts to a single brick. Both map to the same Typer apps. For lists of datasets, steps, methods, and metrics, see Catalogs and registries. [1][2][3]

modssc-datasets --help
modssc-sampling --help
modssc-preprocess --help
modssc-graph --help
modssc-inductive --help
modssc-transductive --help
modssc-augmentation --help
modssc-evaluation --help

14.2 Commands and subcommands

14.2.1 modssc

  • Purpose: Root CLI that wires all bricks and provides doctor and --version. [3]

  • Syntax: modssc [--version] [--log-level <level>] <command> [OPTIONS]

  • Options:
  • --version: print the package version and exit.
  • --log-level / --log: logging level (none, basic, detailed).
  • Examples:
modssc doctor
modssc --log-level detailed datasets list

14.2.2 modssc doctor

  • Purpose: Report which optional CLI bricks are available and which extras are missing. [3]

  • Syntax: modssc doctor [--json]

  • Options:
  • --json: emit machine-readable JSON.
  • Examples:
modssc doctor
modssc doctor --json

14.2.3 modssc datasets

  • Purpose: List, inspect, and download datasets plus manage cache. [4]

  • Syntax: modssc datasets <providers|list|info|download|cache> [OPTIONS]

  • Options (selected):
  • list --modalities <modality>
  • info --dataset <id>
  • download --dataset <id> | --all plus --force, --cache-dir, --skip-cached, --modalities.
  • Examples:
modssc datasets list
modssc datasets info --dataset toy

14.2.4 modssc datasets cache

  • Purpose: Inspect and clean the dataset cache. [4]

  • Syntax: modssc datasets cache <ls|purge|gc> [OPTIONS]

  • Options:
  • ls --cache-dir <path>
  • purge <dataset_or_fp> [--fingerprint]
  • gc [--keep-latest/--no-keep-latest]
  • Examples:
modssc datasets cache ls
modssc datasets cache purge toy

14.2.5 modssc sampling

  • Purpose: Create and inspect deterministic SSL splits. [5]

  • Syntax: modssc sampling <create|show|validate> [OPTIONS]

  • Options:
  • create --dataset <id> --plan <file> --out <dir> [--seed <n>] [--overwrite]
  • show <split_dir>
  • validate <split_dir> --dataset <id>
  • Examples:
modssc sampling create --dataset toy --plan sampling_plan.yaml --out splits/toy
modssc sampling show splits/toy

14.2.6 modssc preprocess

  • Purpose: Run preprocessing plans and inspect registries. [6]

  • Syntax: modssc preprocess <steps|models|run> [OPTIONS]

  • Options:
  • steps list [--json]
  • steps info <step_id>
  • models list [--modality <modality>] [--json]
  • models info <model_id>
  • run --plan <file> --dataset <id> [--seed <n>] [--no-cache] [--purge-unused]
  • Examples:
modssc preprocess steps list
modssc preprocess run --plan preprocess_plan.yaml --dataset toy

14.2.7 modssc graph

  • Purpose: Build graphs and graph-derived views; inspect caches. [7]

  • Syntax: modssc graph <build|views|cache> [OPTIONS]

  • Options (build):
  • --dataset <id>

  • --spec <file> (optional; full spec supports symmetrize/weights/normalize/self_loops). [8]

  • --scheme knn|epsilon|anchor, --metric cosine|euclidean, --k, --radius, --backend auto|numpy|sklearn|faiss

  • --chunk-size, --n-anchors, --anchors-k, --anchors-method, --candidate-limit
  • --faiss-exact, --faiss-hnsw-m, --faiss-ef-search, --faiss-ef-construction
  • --seed, --cache, --cache-dir, --edge-shard-size, --resume
  • Examples:
modssc graph build --dataset toy --scheme knn --metric euclidean --k 8
modssc graph views build --dataset toy --views attr diffusion

14.2.8 modssc graph views

  • Purpose: Build graph-derived views and inspect the views cache. [7]

  • Syntax: modssc graph views <build|cache-ls> [OPTIONS]

  • Options (build, selected):
  • --dataset <id>
  • --views <name> (repeatable; attr, diffusion, struct)
  • --diffusion-steps, --diffusion-alpha
  • --struct-method, --struct-dim, --walk-length, --num-walks-per-node, --window-size, --p, --q
  • --scheme, --metric, --k-graph, --radius
  • Examples:
modssc graph views build --dataset toy --views attr --views diffusion --diffusion-steps 5
modssc graph views cache-ls

14.2.9 modssc graph cache

  • Purpose: Inspect or purge graph caches. [7]

  • Syntax: modssc graph cache <ls|purge>

  • Examples:
modssc graph cache ls
modssc graph cache purge

14.2.10 modssc augmentation

  • Purpose: List augmentation ops and inspect defaults. [9]

  • Syntax: modssc augmentation <list|info> [OPTIONS]

  • Options:
  • list [--modality <modality>]
  • info <op_id> [--as-json]
  • Examples:
modssc augmentation list --modality text
modssc augmentation info text.word_dropout --as-json

14.2.11 modssc evaluation

  • Purpose: List metrics and compute scores from .npy files. [10]

  • Syntax: modssc evaluation <list|compute> [OPTIONS]

  • Options:
  • list [--json]
  • compute --y-true <path> --y-pred <path> [--metric <name>] [--json]
  • Examples:
modssc evaluation list
modssc evaluation compute --y-true y_true.npy --y-pred y_pred.npy --metric accuracy

14.2.12 modssc inductive

  • Purpose: Inspect inductive method registry. [11]

  • Syntax: modssc inductive methods <list|info> [OPTIONS]

  • Options:
  • list [--all/--available-only]
  • info <method_id>
  • Examples:
modssc inductive methods list
modssc inductive methods info pseudo_label

14.2.13 modssc transductive

  • Purpose: Inspect transductive method registry. [12]

  • Syntax: modssc transductive methods <list|info> [OPTIONS]

  • Options:
  • list [--all/--available-only]
  • info <method_id>
  • Examples:
modssc transductive methods list
modssc transductive methods info label_propagation

14.2.14 modssc supervised

  • Purpose: List supervised baselines and their backends. [13]

  • Syntax: modssc supervised <list|info> [OPTIONS]

  • Options:
  • list [--available-only] [--json]
  • info <classifier_id>
  • Examples:
modssc supervised list --available-only
modssc supervised info logreg
Sources
  1. pyproject.toml
  2. src/modssc/cli/
  3. src/modssc/cli/app.py
  4. src/modssc/cli/datasets.py
  5. src/modssc/cli/sampling.py
  6. src/modssc/cli/preprocess.py
  7. src/modssc/cli/graph.py
  8. src/modssc/graph/specs.py
  9. src/modssc/cli/augmentation.py
  10. src/modssc/cli/evaluation.py
  11. src/modssc/cli/inductive.py
  12. src/modssc/cli/transductive.py
  13. src/modssc/cli/supervised.py