---

name: python-api description: "Routes evo programmatic usage, notebook workflows, plotting, and optional Rerun/contextily integration." disable-model-invocation: true metadata: disco-role: operating license: GPL 3.0

python-api

Use this sub-skill when the user wants to call evo from Python, build a notebook workflow, or embed evo plotting and visualization into their own script.

Route here when the user asks for

• custom Python code built on evo's public APIs
• notebook or IPython-friendly usage of evo
• plotting with PlotCollection, plot.traj, plot.error_array, or plot.traj_colormap
• pandas round-tripping of trajectories or results
• optional Rerun or contextily integration
• examples like examples/custom_app.py or examples/alignment_demo.py

Do not route here when the task is mainly about

• CLI-only APE/RPE workflows
• trajectory-file minutiae or converters
• saved-result comparison and tables
• package settings, logfile, or shell management

Start with

1. references/api-reference.md
2. references/workflows.md
3. references/rerun-and-plotting.md
4. references/troubleshooting.md
5. scripts/programmatic_api_smoke.py

Rules of thumb

• ape and rpe mutate their trajectory inputs in place, so copy any object you need to keep unchanged.
• plot.apply_settings() respects IPython/Jupyter and will not force a backend change inside an interactive shell.
• If you need a headless session, prefer an Agg-style backend before importing plotting code.
• rerun-sdk is optional and must be installed separately when you want Rerun support.
• The source examples are good recipes, but the bundled references and smoke helper are the runtime entry points future agents should use.