JavaScript callbacks

While the main goal of Bokeh is to provide a path to create rich interactive visualizations in the browser purely from Python, there will always be specialized use-cases that are outside the capabilities of the core library. For this reason, Bokeh provides different ways for users to supply custom JavaScript when necessary, so that users may add custom or specialized behaviors in response to property changes and other events.

One mechanism is the ability to add entire new custom extension models, as described in Extending Bokeh. However, it is also possible to supply small snippets of JavaScript as callbacks to use, e.g when property values change or when UI or other events occur. This kind of callback can be used to add interesting interactions to Bokeh documents without requiring a Bokeh server (but can also be used in conjunction with a Bokeh server).

Warning

The explicit purpose of these callbacks is to embed raw JavaScript code for a browser to execute. If any part of the code is derived from untrusted user inputs, then you must take appropriate care to sanitize the user input prior to passing it to Bokeh.

CustomJS callbacks

To supply a snippet of JavaScript code that should be executed (in the browser) when some event occurs, use the CustomJS model:

from bokeh.models.callbacks import CustomJS

callback = CustomJS(args=dict(xr=plot.x_range), code="""

// JavaScript code goes here

const a = 10;

// the model that triggered the callback is cb_obj:
const b = cb_obj.value;

// models passed as args are automagically available
xr.start = a;
xr.end = b;

""")

Note that in addition to the code property, CustomJS also accepts an args property that maps string names to Bokeh models. Any Bokeh models that are configured in args (on the “Python side”) will automatically be available to the JavaScript code by the corresponding name. Additionally, the model that triggers the callback (that is the model that the callback is attached to) will be available as cb_obj.

CustomJS for model property events

These CustomJS callbacks can be attached to property change events on any Bokeh model, using the js_on_change method of Bokeh models:

p = figure()

# execute a callback whenever p.x_range.start changes
p.x_range.js_on_change('start', callback)

It should be mentioned that the first parameter to js_on_change is actually the name of a BokehJS event. The full format for a property change event is, for example, "change:start", but Bokeh will automatically convert any property name into one of these BokehJS change events for you. Additionally, some Bokeh models have additional specialized events. For example, the ColumnDataSource also supports "patch" and "stream" events, for executing CustomJS callbacks whenever the data source is patched or streamed to.

Below is an example that shows how to attach a CustomJS callback to a Slider widget, so that whenever the slider value updates, the callback is executed to update some data:

from bokeh.layouts import column
from bokeh.models import ColumnDataSource, CustomJS, Slider
from bokeh.plotting import Figure, output_file, show

output_file("js_on_change.html")

x = [x*0.005 for x in range(0, 200)]
y = x

source = ColumnDataSource(data=dict(x=x, y=y))

plot = Figure(width=400, height=400)
plot.line('x', 'y', source=source, line_width=3, line_alpha=0.6)

callback = CustomJS(args=dict(source=source), code="""
    const data = source.data;
    const f = cb_obj.value
    const x = data['x']
    const y = data['y']
    for (let i = 0; i < x.length; i++) {
        y[i] = Math.pow(x[i], f)
    }
    source.change.emit();
""")

slider = Slider(start=0.1, end=4, value=1, step=.1, title="power")
slider.js_on_change('value', callback)

layout = column(slider, plot)

show(layout)

CustomJS for user interaction events

In addition to responding to property change events using js_on_change, Bokeh allows CustomJS callbacks to be triggered by specific interaction events with the plot canvas, on button click events, and on LOD events.

These event callbacks are defined on models using the js_on_event method, with the callback receiving the event object as a locally defined cb_obj variable:

from bokeh.models.callbacks import CustomJS

callback = CustomJS(code="""
// the event that triggered the callback is cb_obj:
// The event type determines the relevant attributes
console.log('Tap event occurred at x-position: ' + cb_obj.x)
""")

p = figure()
# execute a callback whenever the plot canvas is tapped
p.js_on_event('tap', callback)

The event can be specified as a string such as 'tap' above, or an event class import from the bokeh.events module (i.e. from bokeh.events import Tap).

The following code imports bokeh.events and registers all of the available event classes using the display_event function in order to generate the CustomJS objects. This function is used to update the Div with the event name (always accessible from the event_name attribute) as well as all the other applicable event attributes. The result is a plot that displays the corresponding event on the right when the user interacts with it:

import numpy as np

from bokeh import events
from bokeh.io import output_file, show
from bokeh.layouts import column, row
from bokeh.models import Button, CustomJS, Div
from bokeh.plotting import figure


def display_event(div, attributes=[], style = 'float:left;clear:left;font_size=13px'):
    "Build a suitable CustomJS to display the current event in the div model."
    return CustomJS(args=dict(div=div), code="""
        const attrs = %s;
        const args = [];
        for (let i = 0; i<attrs.length; i++) {
            args.push(attrs[i] + '=' + Number(cb_obj[attrs[i]]).toFixed(2));
        }
        const line = "<span style=%r><b>" + cb_obj.event_name + "</b>(" + args.join(", ") + ")</span>\\n";
        const text = div.text.concat(line);
        const lines = text.split("\\n")
        if (lines.length > 35)
            lines.shift();
        div.text = lines.join("\\n");
    """ % (attributes, style))

x = np.random.random(size=4000) * 100
y = np.random.random(size=4000) * 100
radii = np.random.random(size=4000) * 1.5
colors = ["#%02x%02x%02x" % (int(r), int(g), 150) for r, g in zip(50+2*x, 30+2*y)]

p = figure(tools="pan,wheel_zoom,zoom_in,zoom_out,reset")
p.scatter(x, y, radius=np.random.random(size=4000) * 1.5,
          fill_color=colors, fill_alpha=0.6, line_color=None)

div = Div(width=400, height=p.height, height_policy="fixed")
button = Button(label="Button", button_type="success")
layout = column(button, row(p, div))

## Events with no attributes
button.js_on_event(events.ButtonClick, display_event(div)) # Button click
p.js_on_event(events.LODStart, display_event(div))         # Start of LOD display
p.js_on_event(events.LODEnd, display_event(div))           # End of LOD display

## Events with attributes
point_attributes = ['x', 'y', 'sx', 'sy']                  # Point events
wheel_attributes = point_attributes + ['delta']            # Mouse wheel event
pan_attributes = point_attributes + ['delta_x', 'delta_y'] # Pan event
pinch_attributes = point_attributes + ['scale']            # Pinch event

point_events = [
    events.Tap, events.DoubleTap, events.Press, events.PressUp,
    events.MouseMove, events.MouseEnter, events.MouseLeave,
    events.PanStart, events.PanEnd, events.PinchStart, events.PinchEnd,
]

for event in point_events:
    p.js_on_event(event, display_event(div, attributes=point_attributes))

p.js_on_event(events.MouseWheel, display_event(div, attributes=wheel_attributes))
p.js_on_event(events.Pan,        display_event(div, attributes=pan_attributes))
p.js_on_event(events.Pinch,      display_event(div, attributes=pinch_attributes))

output_file("js_events.html", title="JS Events Example")
show(layout)

Examples

CustomJS for widgets

A common use case for property callbacks is responding to changes to widgets. The code below shows an example of CustomJS set on a slider Widget that changes the source of a plot when the slider is used.

from bokeh.layouts import column
from bokeh.models import ColumnDataSource, CustomJS, Slider
from bokeh.plotting import figure, output_file, show

output_file("callback.html")

x = [x*0.005 for x in range(0, 200)]
y = x

source = ColumnDataSource(data=dict(x=x, y=y))

plot = figure(width=400, height=400)
plot.line('x', 'y', source=source, line_width=3, line_alpha=0.6)

callback = CustomJS(args=dict(source=source), code="""
        const data = source.data;
        const f = cb_obj.value
        const x = data['x']
        const y = data['y']
        for (let i = 0; i < x.length; i++) {
            y[i] = Math.pow(x[i], f)
        }
        source.change.emit();
    """)

slider = Slider(start=0.1, end=4, value=1, step=.1, title="power")
slider.js_on_change('value', callback)

layout = column(slider, plot)

show(layout)

CustomJS for selections

Another common scenario is wanting to specify the same kind of callback to be executed whenever a selection changes. As a simple demonstration, the example below simply copies selected points on the first plot to the second. However, more sophisticated actions and computations are easily constructed in a similar way.

from random import random

from bokeh.layouts import row
from bokeh.models import ColumnDataSource, CustomJS
from bokeh.plotting import figure, output_file, show

output_file("callback.html")

x = [random() for x in range(500)]
y = [random() for y in range(500)]

s1 = ColumnDataSource(data=dict(x=x, y=y))
p1 = figure(width=400, height=400, tools="lasso_select", title="Select Here")
p1.circle('x', 'y', source=s1, alpha=0.6)

s2 = ColumnDataSource(data=dict(x=[], y=[]))
p2 = figure(width=400, height=400, x_range=(0, 1), y_range=(0, 1),
            tools="", title="Watch Here")
p2.circle('x', 'y', source=s2, alpha=0.6)

s1.selected.js_on_change('indices', CustomJS(args=dict(s1=s1, s2=s2), code="""
        const inds = cb_obj.indices;
        const d1 = s1.data;
        const d2 = s2.data;
        d2['x'] = []
        d2['y'] = []
        for (let i = 0; i < inds.length; i++) {
            d2['x'].push(d1['x'][inds[i]])
            d2['y'].push(d1['y'][inds[i]])
        }
        s2.change.emit();
    """)
)

layout = row(p1, p2)

show(layout)

Another more sophisticated example is shown below. It computes the average y value of any selected points (including multiple disjoint selections) and draws a line through that value.

from random import random

from bokeh.models import ColumnDataSource, CustomJS
from bokeh.plotting import figure, output_file, show

output_file("callback.html")

x = [random() for x in range(500)]
y = [random() for y in range(500)]
color = ["navy"] * len(x)

s = ColumnDataSource(data=dict(x=x, y=y, color=color))
p = figure(width=400, height=400, tools="lasso_select", title="Select Here")
p.circle('x', 'y', color='color', size=8, source=s, alpha=0.4)

s2 = ColumnDataSource(data=dict(x=[0, 1], ym=[0.5, 0.5]))
p.line(x='x', y='ym', color="orange", line_width=5, alpha=0.6, source=s2)

s.selected.js_on_change('indices', CustomJS(args=dict(s=s, s2=s2), code="""
    const inds = s.selected.indices;
    const d = s.data;
    let ym = 0

    if (inds.length == 0)
        return;

    for (let i = 0; i < d['color'].length; i++) {
        d['color'][i] = "navy"
    }
    for (let i = 0; i < inds.length; i++) {
        d['color'][inds[i]] = "firebrick"
        ym += d['y'][inds[i]]
    }

    ym /= inds.length
    s2.data['ym'] = [ym, ym]

    s.change.emit();
    s2.change.emit();
"""))

show(p)

CustomJS for ranges

The properties of range objects may also be connected to CustomJS callbacks in order to perform specialized work whenever a range changes:

import numpy as np

from bokeh.layouts import row
from bokeh.models import BoxAnnotation, CustomJS
from bokeh.plotting import figure, output_file, show

output_file('range_update_callback.html')

N = 4000

x = np.random.random(size=N) * 100
y = np.random.random(size=N) * 100
radii = np.random.random(size=N) * 1.5
colors = [
    "#%02x%02x%02x" % (int(r), int(g), 150) for r, g in zip(50+2*x, 30+2*y)
]

box = BoxAnnotation(left=0, right=0, bottom=0, top=0,
    fill_alpha=0.1, line_color='black', fill_color='black')

jscode = """
    box[%r] = cb_obj.start
    box[%r] = cb_obj.end
"""

p1 = figure(title='Pan and Zoom Here', x_range=(0, 100), y_range=(0, 100),
            tools='box_zoom,wheel_zoom,pan,reset', width=400, height=400)
p1.scatter(x, y, radius=radii, fill_color=colors, fill_alpha=0.6, line_color=None)

xcb = CustomJS(args=dict(box=box), code=jscode % ('left', 'right'))
ycb = CustomJS(args=dict(box=box), code=jscode % ('bottom', 'top'))

p1.x_range.js_on_change('start', xcb)
p1.x_range.js_on_change('end', xcb)
p1.y_range.js_on_change('start', ycb)
p1.y_range.js_on_change('end', ycb)

p2 = figure(title='See Zoom Window Here', x_range=(0, 100), y_range=(0, 100),
            tools='', width=400, height=400)
p2.scatter(x, y, radius=radii, fill_color=colors, fill_alpha=0.6, line_color=None)
p2.add_layout(box)

layout = row(p1, p2)

show(layout)

CustomJS for tools

Selection tools emit events that can drive useful callbacks. Below, a callback for SelectionGeometry uses the BoxSelectTool geometry (accessed via the geometry field of the cb_data callback object), in order to update a Rect glyph.

from bokeh.events import SelectionGeometry
from bokeh.models import ColumnDataSource, CustomJS, Rect
from bokeh.plotting import figure, output_file, show

output_file("box_select_tool_callback.html")

source = ColumnDataSource(data=dict(x=[], y=[], width=[], height=[]))

callback = CustomJS(args=dict(source=source), code="""
    const geometry = cb_obj['geometry']
    const data = source.data

    // calculate Rect attributes
    const width = geometry['x1'] - geometry['x0']
    const height = geometry['y1'] - geometry['y0']
    const x = geometry['x0'] + width/2
    const y = geometry['y0'] + height/2

    // update data source with new Rect attributes
    data['x'].push(x)
    data['y'].push(y)
    data['width'].push(width);
    data['height'].push(height)

    // emit update of data source
    source.change.emit()
""")

p = figure(width=400, height=400, tools="box_select",
           title="Select Below", x_range=(0, 1), y_range=(0, 1))

rect = Rect(x='x', y='y', width='width', height='height',
            fill_alpha=0.3, fill_color='#009933')

p.add_glyph(source, rect, selection_glyph=rect, nonselection_glyph=rect)

p.js_on_event(SelectionGeometry, callback)

show(p)

CustomJS for specialized events

In addition to the generic mechanisms described above for adding CustomJS callbacks to Bokeh models, there are also some Bokeh models that have a .callback property specifically for executing CustomJS in response to specific events or situations.

Warning

The callbacks described below were added early to Bokeh in an ad-hoc fashion. Many of them can be accomplished with the generic mechanism described above, and as such, may be deprecated in favor of the generic mechanism in the future.

CustomJS for hover tool

The HoverTool has a callback which comes with two pieces of built-in data: the index and the geometry. The index is the indices of any points that the hover tool is over.

from bokeh.models import ColumnDataSource, CustomJS, HoverTool
from bokeh.plotting import figure, output_file, show

output_file("hover_callback.html")

# define some points and a little graph between them
x = [2, 3, 5, 6, 8, 7]
y = [6, 4, 3, 8, 7, 5]
links = {
    0: [1, 2],
    1: [0, 3, 4],
    2: [0, 5],
    3: [1, 4],
    4: [1, 3],
    5: [2, 3, 4]
}

p = figure(width=400, height=400, tools="", toolbar_location=None, title='Hover over points')

source = ColumnDataSource({'x0': [], 'y0': [], 'x1': [], 'y1': []})
sr = p.segment(x0='x0', y0='y0', x1='x1', y1='y1', color='olive', alpha=0.6, line_width=3, source=source, )
cr = p.circle(x, y, color='olive', size=30, alpha=0.4, hover_color='olive', hover_alpha=1.0)

# add a hover tool that sets the link data for a hovered circle
code = """
const links = %s
const data = {'x0': [], 'y0': [], 'x1': [], 'y1': []}
const indices = cb_data.index.indices
for (let i = 0; i < indices.length; i++) {
    const start = indices[i]
    for (let j = 0; j < links[start].length; j++) {
        const end = links[start][j]
        data['x0'].push(circle.data.x[start])
        data['y0'].push(circle.data.y[start])
        data['x1'].push(circle.data.x[end])
        data['y1'].push(circle.data.y[end])
    }
}
segment.data = data
""" % links

callback = CustomJS(args={'circle': cr.data_source, 'segment': sr.data_source}, code=code)
p.add_tools(HoverTool(tooltips=None, callback=callback, renderers=[cr]))

show(p)

OpenURL

Opening an URL when users click on a glyph (for instance a circle marker) is a very popular feature. Bokeh lets users enable this feature by exposing an OpenURL callback object that can be passed to a Tap tool in order to have that action called whenever the user clicks on the glyph.

The following code shows how to use the OpenURL action combined with a TapTool to open an URL whenever the user clicks on a circle.

from bokeh.models import ColumnDataSource, OpenURL, TapTool
from bokeh.plotting import figure, output_file, show

output_file("openurl.html")

p = figure(width=400, height=400,
           tools="tap", title="Click the Dots")

source = ColumnDataSource(data=dict(
    x=[1, 2, 3, 4, 5],
    y=[2, 5, 8, 2, 7],
    color=["navy", "orange", "olive", "firebrick", "gold"]
    ))

p.circle('x', 'y', color='color', size=20, source=source)

# use the "color" column of the CDS to complete the URL
# e.g. if the glyph at index 10 is selected, then @color
# will be replaced with source.data['color'][10]
url = "http://www.html-color-names.com/@color.php"
taptool = p.select(type=TapTool)
taptool.callback = OpenURL(url=url)

show(p)

Please note that OpenURL callbacks specifically and only work with TapTool, and are only invoked when a glyph is hit. That is, they do not execute on every tap. If you would like to execute a callback on every mouse tap, please see CustomJS for user interaction events.

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