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name: orange3 description: "Route Orange3 data mining, modeling, visualization, and widget-development workflows across the Orange data/API and Canvas widget surfaces." disable-model-invocation: true metadata: disco-role: operating license: NOASSERTION

Orange3

Use this repo skill when a task involves Orange3 / Orange Data Mining: the Orange.data.Table data model, file/SQL ingestion, preprocessing widgets, supervised learners and evaluation, exploratory plots/projections/clustering, or Orange Canvas widget development.

Orange3 combines a Python data-mining library with a Qt Canvas visual-programming application. Start from the user's surface area: API code, GUI widget workflow, .ows Canvas workflow, or widget-framework maintenance.

First decision

1. Data loading, cleaning, schema repair, SQL, or save/export → use sub-skills/data-preparation/SKILL.md.
2. Classification, regression, fitted models, predictions, or Orange.evaluation scoring → use sub-skills/supervised-modeling/SKILL.md.
3. Plots, distances, projections, clustering, statistics, or unsupervised widgets → use sub-skills/exploration-visualization/SKILL.md.
4. Building, previewing, testing, discovering, or loading Orange widgets / Canvas workflows → use sub-skills/widget-development/SKILL.md.
5. For install/import, orange-canvas, optional SQL, PyQt/headless, or cross-cutting package issues, read references/troubleshooting.md.
6. For package architecture, install commands, CLI entry points, and native verification surfaces, read references/package-overview.md.

Common task signals

Route to this skill when the request mentions any of these signals:

• Orange, Orange3, Orange Data Mining, Orange Canvas, orange-canvas, .ows, widgets, widget workflows, or add-ons.
• Orange.data.Table, Domain, Variable, .tab, OWFile, OWCSVImport, OWSave, OWPreprocess, or OWSql.
• Orange learners such as LogisticRegressionLearner, RandomForestLearner, TreeLearner, KNNLearner, SVMLearner, MeanLearner, ConstantLearner, or Orange.modelling fitters.
• CrossValidation, TestOnTestData, Test and Score, Predictions, CA, AUC, F1, RMSE, R2, or Results.failed.
• Scatter Plot, Box Plot, Distributions, Heat Map, Distance Matrix/Map, PCA, MDS, t-SNE, k-Means, DBSCAN, Hierarchical Clustering, Silhouette Plot, FreeViz, Linear Projection, or Radviz.
• OWWidget, Input, Output, Setting, ContextSetting, DomainContextHandler, WidgetPreview, WidgetTest, widget discovery, or Canvas workflow loading.

Minimal package check

For a quick installed-package check, run the bundled helper:

python scripts/orange3_smoke.py --skip-gui

If Qt/PyQt is installed and a headless display is needed:

QT_QPA_PLATFORM=offscreen python scripts/orange3_smoke.py --with-gui

A basic manual import check is:

import Orange
from Orange.data import Table
iris = Table("iris")
print(Orange.__version__, len(iris), iris.domain)

Operating rules

• Treat Orange's Table/Domain/Variable model as the shared substrate. Even widget tasks usually pass Table, Learner, Model, Results, or DistMatrix objects through signals.
• For GUI/widget work, distinguish method semantics from widget framework mechanics. Use method sub-skills for data/model/visualization behavior and widget-development for OWWidget, signals, settings, preview, tests, and Canvas workflows.
• SQL support is optional and service-bound. Do not block core Orange3 guidance on PostgreSQL or SQL Server unless the user's task explicitly requires live SQL.
• Use QT_QPA_PLATFORM=offscreen for headless widget discovery, widget tests, Canvas workflow loads, or catalog/icon rendering.
• Do not assume CUDA/ROCm/MPS. The selected Orange3 skill scope needs CPU plus GUI dependencies; no accelerator backend is required.
• Do not depend on a source checkout at runtime. Use the bundled references and scripts in this skill plus an installed Orange3 package.

What this skill does not cover

• Generic scikit-learn or pandas tasks that do not use Orange's data model, widgets, or Canvas.
• Deep-learning GPU training frameworks, LLM workflows, or distributed training unless they are only incidental dependencies of an Orange task.
• Writing or exporting DisCo skills themselves; this is an operating skill for Researcher mode.

Provenance

See references/repo-provenance.md for the source commit, dirty-state baseline, package version, and relative evidence paths distilled into this skill.