name: datasets-and-loaders
description: "Routes pyts dataset loading, cached toy datasets, synthetic
generators, and UCR/UEA fetch workflows."
disable-model-invocation: true
metadata:
disco-role: operating
license: BSD 3-Clause
datasets-and-loaders
Use this sub-skill when a user asks how to load, inspect, fetch, or generate
pyts time-series datasets.
What this covers
- Packaged toy loaders:
load_basic_motions, load_coffee, load_gunpoint,
load_pig_central_venous_pressure.
- Synthetic generation:
make_cylinder_bell_funnel.
- Metadata and catalog helpers:
ucr_dataset_list, ucr_dataset_info,
uea_dataset_list, uea_dataset_info.
- Network-backed fetch helpers:
fetch_ucr_dataset, fetch_uea_dataset.
- Shape, split, and cached-data expectations for downstream preprocessing,
metrics, and classifier workflows.
What this excludes
- Preprocessing and symbolic transforms: use
../preprocessing-and-symbols/SKILL.md.
- Feature extraction, images, and decomposition: use
../feature-extraction-and-images/SKILL.md.
- Metrics and classifiers: use
../metrics-and-classifiers/SKILL.md.
- Multivariate wrappers: use
../multivariate-workflows/SKILL.md.
Start here
- Read
references/workflows.md for the supported dataset-loading patterns.
- Read
references/data-formats.md when you need shapes, split structure,
or dataset catalog facts.
- Read
references/troubleshooting.md for network, cache, and naming errors.
- Run
scripts/smoke.py from this sub-skill directory to confirm the installed
package can load the bundled datasets.
Useful triggers
- "load GunPoint"
- "fetch UCR dataset metadata"
- "make a synthetic cylinder-bell-funnel dataset"
- "what shape does BasicMotions return?"
- "does pyts need network access for dataset helpers?"
Routing hints
- If the user needs a dataset before scaling, discretizing, or modeling, stay
here only long enough to identify the dataset shape and then route to the
downstream workflow.
- If the user only needs network-free toy data for a smoke test, prefer the
packaged loaders and
make_cylinder_bell_funnel.
- If the user needs remote downloads, explain the cache and network dependency
before promising a reproducible result.
Links
- Read
references/workflows.md for example loader calls and return shapes.
- Read
references/data-formats.md for bundled dataset layouts and return
conventions.
- Read
references/troubleshooting.md when a loader name, cache path, or
network fetch fails.
- Run
scripts/smoke.py when you want a quick installed-package check.