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Minimal Examples

Skill version 0.1.0

A reproducer a tester pastes and runs unchanged to check a fix, so keep it short enough to skim, not study. These are the traps specific to HoloViz reproducers.

  • Render explicitly with pn.serve(obj); don't end on the bare object. In a script the notebook _repr_html_ never fires, so obj alone does nothing and any render-time error (layout sizing, projection, aspect, colorbar) stays hidden. pn.serve renders any HoloViews/hvPlot/Panel object and surfaces it.
  • Declare the backend the behavior depends on (hv.extension('bokeh') vs 'matplotlib'). The same code renders through different code paths per backend, so an implicit backend makes the report ambiguous.
  • Generate data inline and seed it (rng = np.random.default_rng(0)), or load a dataset the reader can fetch too, e.g. a URL, xr.tutorial.open_dataset, or bokeh.sampledata. Just don't read_csv a local path only you have.
  • For a bug, paste the versions that matter (hv.__version__, pn.__version__, and the backend: bokeh/matplotlib/cartopy). HoloViz bugs are usually version-specific.
  • End with a one-line comment on the before behavior (what a tester sees without the fix) and the after (what a correct run should show), so they know what to look for without studying the code.
import numpy as np, pandas as pd, holoviews as hv, panel as pn
hv.extension('bokeh')                       # backend the behavior depends on

rng = np.random.default_rng(0)
df = pd.DataFrame({'x': rng.normal(size=20), 'y': rng.normal(size=20)})
pn.serve(hv.Scatter(df, 'x', 'y'))          # force render; raises the error if present
# Before: raises ValueError / renders blank.
# After:  shows a scatter of 20 points.