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 behaviours 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 the need to use 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 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
var a = 10;
// the model that triggered the callback is cb_obj:
var 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 (i.e. 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, e.g. "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 CustomJS, ColumnDataSource, 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(plot_width=400, plot_height=400)
plot.line('x', 'y', source=source, line_width=3, line_alpha=0.6)
callback = CustomJS(args=dict(source=source), code="""
var data = source.data;
var f = cb_obj.value
var x = data['x']
var y = data['y']
for (var 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 when interacted with, displays the corresponding
event on the right:
import numpy as np
from bokeh.io import show, output_file
from bokeh.plotting import figure
from bokeh import events
from bokeh.models import CustomJS, Div, Button
from bokeh.layouts import column, row
def display_event(div, attributes=[], style = 'float:left;clear:left;font_size=10pt'):
"Build a suitable CustomJS to display the current event in the div model."
return CustomJS(args=dict(div=div), code="""
var attrs = %s; var args = [];
for (var i = 0; i<attrs.length; i++) {
args.push(attrs[i] + '=' + Number(cb_obj[attrs[i]]).toFixed(2));
}
var line = "<span style=%r><b>" + cb_obj.event_name + "</b>(" + args.join(", ") + ")</span>\\n";
var text = div.text.concat(line);
var 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=1000)
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.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)
CustomJS for Specialized Events¶
In addition to the generic mechanisms described above for adding CustomJS
callbacks to Bokeh models, there are also a 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 Widgets¶
Bokeh lets you express even more advanced callbacks that must be called on the Javascript side in order to add custom logic and interactivity when a widget is used. For instance, we may want to change the data of a plot when a user clicks on a button or changes a slider Widget.
Custom callbacks like these can be set using a CustomJS object and passing it
as the callback argument to a Widget object.
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 CustomJS, ColumnDataSource, 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(plot_width=400, plot_height=400)
plot.line('x', 'y', source=source, line_width=3, line_alpha=0.6)
callback = CustomJS(args=dict(source=source), code="""
var data = source.data;
var f = cb_obj.value
var x = data['x']
var y = data['y']
for (var 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", callback=callback)
layout = column(slider, plot)
show(layout)
CustomJS for Tools¶
Bokeh allows for some tool events to trigger custom Javascript callbacks that have access to the tool’s attributes. Below, a callback on the BoxSelectTool uses the selection box dimensions (accessed in the geometry field of the cb_data object that is injected into the Callback code attribute), in order to add a Rect glyph to the plot with identical dimensions.
from bokeh.models import CustomJS, ColumnDataSource, BoxSelectTool, Range1d, Rect
from bokeh.plotting import figure, output_file, show
output_file("boxselecttool_callback.html")
source = ColumnDataSource(data=dict(x=[], y=[], width=[], height=[]))
callback = CustomJS(args=dict(source=source), code="""
// get data source from Callback args
var data = source.data;
/// get BoxSelectTool dimensions from cb_data parameter of Callback
var geometry = cb_data['geometry'];
/// calculate Rect attributes
var width = geometry['x1'] - geometry['x0'];
var height = geometry['y1'] - geometry['y0'];
var x = geometry['x0'] + width/2;
var 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();
""")
box_select = BoxSelectTool(callback=callback)
p = figure(plot_width=400,
plot_height=400,
tools=[box_select],
title="Select Below",
x_range=Range1d(start=0.0, end=1.0),
y_range=Range1d(start=0.0, end=1.0))
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)
show(p)
CustomJS for Selections¶
Bokeh also provides the means 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 CustomJS, ColumnDataSource
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(plot_width=400, plot_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(plot_width=400, plot_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="""
var inds = cb_obj.indices;
var d1 = s1.data;
var d2 = s2.data;
d2['x'] = []
d2['y'] = []
for (var 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 CustomJS, ColumnDataSource
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(plot_width=400, plot_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.callback = CustomJS(args=dict(s2=s2), code="""
var inds = cb_obj.selected.indices;
var d = cb_obj.data;
var ym = 0
if (inds.length == 0)
return;
for (var i = 0; i < d['color'].length; i++) {
d['color'][i] = "navy"
}
for (var i = 0; i < inds.length; i++) {
d['color'][inds[i]] = "firebrick"
ym += d['y'][inds[i]]
}
ym /= inds.length
s2.data['ym'] = [ym, ym]
cb_obj.change.emit();
s2.change.emit();
""")
show(p)
CustomJS for Hover¶
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.plotting import figure, output_file, show
from bokeh.models import ColumnDataSource, HoverTool, CustomJS
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(plot_width=400, plot_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 = """
var links = %s;
var data = {'x0': [], 'y0': [], 'x1': [], 'y1': []};
var cdata = circle.data;
var indices = cb_data.index['1d'].indices;
for (var i = 0; i < indices.length; i++) {
var ind0 = indices[i]
for (var j = 0; j < links[ind0].length; j++) {
var ind1 = links[ind0][j];
data['x0'].push(cdata.x[ind0]);
data['y0'].push(cdata.y[ind0]);
data['x1'].push(cdata.x[ind1]);
data['y1'].push(cdata.y[ind1]);
}
}
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)
CustomJS for Range Update¶
With Bokeh, ranges have a callback attribute that accept a Callback instance and execute Javascript code on range updates that are triggered by tool interactions such as a box zoom, wheel scroll or pan.
import numpy as np
from bokeh.layouts import row
from bokeh.models import ColumnDataSource, CustomJS, Rect
from bokeh.plotting import output_file, figure, 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)
]
source = ColumnDataSource({'x': [], 'y': [], 'width': [], 'height': []})
jscode="""
var data = source.data;
var start = cb_obj.start;
var end = cb_obj.end;
data['%s'] = [start + (end - start) / 2];
data['%s'] = [end - start];
source.change.emit();
"""
p1 = figure(title='Pan and Zoom Here', x_range=(0, 100), y_range=(0, 100),
tools='box_zoom,wheel_zoom,pan,reset', plot_width=400, plot_height=400)
p1.scatter(x, y, radius=radii, fill_color=colors, fill_alpha=0.6, line_color=None)
p1.x_range.callback = CustomJS(
args=dict(source=source), code=jscode % ('x', 'width'))
p1.y_range.callback = CustomJS(
args=dict(source=source), code=jscode % ('y', 'height'))
p2 = figure(title='See Zoom Window Here', x_range=(0, 100), y_range=(0, 100),
tools='', plot_width=400, plot_height=400)
p2.scatter(x, y, radius=radii, fill_color=colors, fill_alpha=0.6, line_color=None)
rect = Rect(x='x', y='y', width='width', height='height', fill_alpha=0.1,
line_color='black', fill_color='black')
p2.add_glyph(source, rect)
layout = row(p1, p2)
show(layout)
CustomJS with CoffeeScript code¶
It is possible to write the code for CustomJS callbacks in CoffeeScript.
To accomplish this, use the from_coffeescript class method, which accepts
the same args and code parameters:
callback = CustomJS.from_coffeescript(args=dict(p=plot), code="""
# coffeescript code here
""")
CustomJS with a Python function¶
A CustomJS callback can also be implemented as a Python function, which
is then translated to JavaScript using PScript. This makes it easier
for users to define client-side interactions without having to learn
JavaScript. To use this functionality you need the PScript library
(install with conda install -c conda-forge pscript or pip install pscript).
Warning
It is critical to note that no python code is ever executed when
a CustomJS callback is used. This is true even when the callback is
supplied as python code to be translated to JavaScript as described in
this section. A CustomJS callback is only executed inside a browser
JavaScript interpreter, and can only directly interact JavaScript data
and functions (e.g., BokehJS models).
For more information about the subset of Python that is supported in callbacks, see the PScript documentation.
We recommend using window.x for variables specific to JavaScript
to avoid confusion and help static code analysis tools. You can add
window as an argument to the callback function to help readability
(and pyflakes), as in the example below.
from bokeh.layouts import column
from bokeh.models import CustomJS, ColumnDataSource, 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(plot_width=400, plot_height=400)
plot.line('x', 'y', source=source, line_width=3, line_alpha=0.6)
def callback(source=source, window=None):
data = source.data
f = cb_obj.value
x, y = data['x'], data['y']
for i in range(len(x)):
y[i] = window.Math.pow(x[i], f)
source.change.emit()
slider = Slider(start=0.1, end=4, value=1, step=.1, title="power",
callback=CustomJS.from_py_func(callback))
layout = column(slider, plot)
show(layout)
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 users 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(plot_width=400, plot_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.colors.commutercreative.com/@color/"
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.