| name | minimal-example |
| description | Write a minimal, self-contained, reproducible example for a HoloViz behavior or bug. Use when drafting a bug report, an issue reproducer, a PR "How to test" snippet, or any code sample a maintainer must be able to paste and run unchanged. |
| metadata | {"version":"0.1.0","author":"holoviz"} |
Minimal Examples
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')
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'))
