L’interface est localisée ; les présentations et documents des Skills sont traduits automatiquement par IA dans votre langue. Le code, les commandes, chemins et termes techniques restent en version originale, et le document de l’auteur fait foi.
Explorer les Skills
Productivité · SKILL.md

external-integrations

external-integrations

Use Scanpy optional integrations, scanpy.external wrappers, Dask-backed arrays, and GPU/RAPIDS handoffs without over-installing optional dependencies.

Independent GitHub snapshot · Automated classification · Original documentation governs

Documentation de la Skill

GitHub

name: external-integrations description: "Use Scanpy optional integrations, scanpy.external wrappers, Dask-backed arrays, and GPU/RAPIDS handoffs without over-installing optional dependencies." disable-model-invocation: true metadata: disco-role: operating license: BSD 3-Clause

Scanpy External Integrations

Use this sub-skill when a task involves optional dependency extras, scanpy.external, Dask-backed arrays, RAPIDS/GPU acceleration, external exporting, or integration/imputation/demultiplexing/trajectory wrappers outside Scanpy's core preprocessing and tool APIs.

Route By Need

  • Optional extras planning: Read references/optional-dependencies.md before recommending installs; choose the narrow extra or upstream package for the requested feature and do not suggest installing every extra.
  • External wrapper selection: Read references/external-api-map.md to map scanpy.external.pp, scanpy.external.tl, scanpy.external.pl, and scanpy.external.exporting methods to prerequisites, outputs, and moved APIs.
  • Dask or large arrays: Read references/dask-and-rapids.md before promising distributed support; Scanpy supports selected Dask-backed preprocessing paths, not every algorithm or external package.
  • GPU acceleration: Route GPU requests to references/dask-and-rapids.md; GPU workflows are usually delegated to rapids-singlecell, while Scanpy's RAPIDS neighbor backend requires a compatible cuML stack.
  • Import/install failures: Use references/troubleshooting.md plus scripts/check_scanpy_optional_deps.py to diagnose missing optional packages without installing or importing heavy dependencies.

Safe Helper

Run the bundled checker from this sub-skill directory when you need a machine-readable optional-dependency inventory:

python scripts/check_scanpy_optional_deps.py --feature scanorama --feature magic --json
python scripts/check_scanpy_optional_deps.py --list-features

The helper uses importlib.util.find_spec and package metadata only. It has no network, install, import-heavy, or package-mutation side effects.

Boundaries

  • Prefer core Scanpy guidance for ordinary normalization, PCA, neighbors, clustering, plotting, and AnnData handling unless the task explicitly needs optional integrations, Dask-backed arrays, or GPU handoffs.
  • Prefer sc.pp.harmony_integrate, sc.pp.scrublet, and sc.pp.scrublet_simulate_doublets for moved APIs; legacy scanpy.external.pp aliases are deprecated compatibility routes.
  • Keep install advice minimal: scanpy[leiden], scanpy[skmisc], scanpy[plotting], scanpy[magic], scanpy[scanorama], scanpy[bbknn], scanpy[dask], scanpy[dask-ml], and scanpy[scrublet] are targeted choices for specific features.
  • For wrappers without Scanpy extras, recommend the named upstream package only for that method, such as mnnpy, phate, palantir, trimap, sc-sam, phenograph, harmonyTS, wishbone, pypairs, or cellbrowser.
  • Do not recommend broad optional extras, development/test dependency groups, source checkout scripts, or original repository paths for runtime use.
Skills enregistrées