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name: installation description: "Install, inspect, and troubleshoot Fairlearn runtimes, optional plotting/adversarial dependencies, and version diagnostics." disable-model-invocation: true metadata: disco-role: operating license: MIT

Fairlearn installation

Use this sub-skill when the task is about installing Fairlearn, confirming imports, inspecting versions, optional dependencies, plotting extras, PyTorch/TensorFlow adversarial backends, show_versions, missing dependency errors, or package-runtime diagnostics.

Quick workflow

1. Determine whether the user is using a released package, a local checkout, or a prepared environment.
2. Install the smallest dependency set needed for the requested workflow.
3. Run the root check script or the wrapper in this sub-skill.
4. If optional plotting or adversarial backends are absent, decide whether the requested workflow actually requires them before installing.
5. Route back to the workflow-owning sub-skill after imports and optional dependencies are resolved.

Read these references

• ../../references/installation.md for root install commands, optional dependency table, raw import checks, and show_versions guidance.
• references/runtime-and-version-checks.md for workflow-specific runtime probes and version diagnostics.
• references/troubleshooting.md for install/import, extras, show_versions, backend, and version-skew recovery.
• scripts/check_runtime.py wraps the root installation check from this sub-skill location.

Core facts

• Package name: fairlearn.
• Python requirement in the inspected source: >=3.11.
• Core dependencies: narwhals, numpy, pandas, scikit-learn, and scipy.
• Public version check: import fairlearn; print(fairlearn.__version__).
• Environment report: fairlearn.show_versions().
• No Fairlearn-specific CLI entry points were found in the inspected source.

Optional dependency ownership

Dependency	Owned workflow	First route
matplotlib	assessment and postprocessing plots	../assessment/ or ../postprocessing/
torch	PyTorch adversarial backend	../adversarial/
tensorflow / keras	TensorFlow adversarial backend	../adversarial/ with explicit unverified-backend note
OpenML/network/cache	dataset loaders	../datasets/

Fast validation

From this skill directory:

python sub-skills/installation/scripts/check_runtime.py --include-optional

Or from the root skill directory:

python scripts/check_install.py --include-optional

If the check passes but a workflow still fails, switch to that workflow's troubleshooting reference.