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Download this notebook from GitHub (right-click to download).

import panel as pn
import numpy as np
import holoviews as hv

pn.extension(sizing_mode = 'stretch_width')

For a large variety of use cases we do not need complete control over the exact layout of each individual component on the page, as could be achieved with a custom template, we just want to achieve a more polished look and feel. For these cases Panel ships with a number of default templates, which are defined by declaring four main content areas on the page, which can be populated as desired:

  • header: The header area of the HTML page

  • sidebar: A collapsible sidebar

  • main: The main area of the application

  • modal: A modal area which can be opened and closed from Python

These four areas behave very similarly to other Panel layout components and have list-like semantics. This means we can easily append new components into these areas. Unlike other layout components however, the contents of the areas is fixed once rendered. If you need a dynamic layout you should therefore insert a regular Panel layout component (e.g. a Column or Row) and modify it in place once added to one of the content areas.

Templates can allow for us to quickly and easily create web apps for displaying our data. Panel comes with a default Template, and includes multiple Templates that extend the default which add some customization for a better display.


In addition to the four different areas we can populate the default templates also provide a few additional parameters:

  • busy_indicator (BooleanIndicator): Visual indicator of application busy state.

  • header_background (str): Optional header background color override.

  • header_color (str): Optional header text color override.

  • logo (str): URI of logo to add to the header (if local file, logo is base64 encoded as URI).

  • site (str): Name of the site. Will be shown in the header. Default is ‘’, i.e. not shown.

  • site_url (str): Url of the site and logo. Default is “/”.

  • title (str): A title to show in the header.

  • theme (Theme): A Theme class (available in panel.template.theme)

  • sidebar_width (int): The width of the sidebar in pixels. Default is 330.

In this case we are using the BootstrapTemplate, built on Bootstrap v4, which is a light weight CSS framework. Here is an example of how you can set up a display using this template:

bootstrap = pn.template.BootstrapTemplate(title='Bootstrap Template')

xs = np.linspace(0, np.pi)
freq = pn.widgets.FloatSlider(name="Frequency", start=0, end=10, value=2)
phase = pn.widgets.FloatSlider(name="Phase", start=0, end=np.pi)

@pn.depends(freq=freq, phase=phase)
def sine(freq, phase):
    return hv.Curve((xs, np.sin(xs*freq+phase))).opts(
        responsive=True, min_height=400)

@pn.depends(freq=freq, phase=phase)
def cosine(freq, phase):
    return hv.Curve((xs, np.cos(xs*freq+phase))).opts(
        responsive=True, min_height=400)


        pn.Card(hv.DynamicMap(sine), title='Sine'),
        pn.Card(hv.DynamicMap(cosine), title='Cosine')

BootstrapTemplate with DefaultTheme

BootstrapTemplate with DarkTheme

The app can be displayed within the notebook by using .servable(), or rendered in another tab by replacing it with .show().

Themes can be added using the optional keyword argument theme. Each template comes with a DarkTheme and a DefaultTheme, which can be set BootstrapTemplate(theme=DarkTheme). If no theme is set, then DefaultTheme will be applied.

It should be noted that Templates may not render correctly in a notebook, and for the best performance the should ideally be deployed to a server.

This web page was generated from a Jupyter notebook and not all interactivity will work on this website. Right click to download and run locally for full Python-backed interactivity.

Download this notebook from GitHub (right-click to download).