bokeh.sphinxext#

In order to help automate and simplify the generation of Bokeh documentation, several Sphinx extensions have been created. Most of these will not be of general interest, except for bokeh.sphinxext.bokeh_plot, which allows anyone to include and embed bokeh plots directly in their own Sphinx docs.

bokeh_autodoc#

Integrate Bokeh extensions into Sphinx autodoc.

Ensures that autodoc directives such as autoclass automatically make use of Bokeh-specific directives when appropriate. The following Bokeh extensions are configured:

bokeh_color
bokeh_enum
bokeh_model
bokeh_prop

To enable this extension, add “bokeh.sphinxext.bokeh_autodoc” to the extensions list in your Sphinx configuration module.

bokeh_color#

Document Bokeh named colors.

The bokeh-color directive accepts a named color as its argument:

.. bokeh-color:: aliceblue

and generates a labeled color swatch as output.

aliceblue

The bokeh-color direction may be used explicitly, but it can also be used in conjunction with the bokeh_autodoc extension.

To enable this extension, add “bokeh.sphinxext.bokeh_color” to the extensions list in your Sphinx configuration module.

bokeh_dataframe#

Generate an inline visual representations of a pandas Dataframe.

This directive will embed the output of df.head().to_html() into the HTML output.

For example:

:bokeh-dataframe:`bokeh.sampledata.sprint.sprint`

Will generate the output:

	Name	Country	Medal	Time	Year	Abbrev	Speed	MetersBack	MedalFill	MedalLine
0	Usain Bolt	JAM	gold	9.63	2012	JAM	10.384216	0.000000	#efcf6d	#c8a850
1	Yohan Blake	JAM	silver	9.75	2012	JAM	10.256410	1.230769	#cccccc	#b0b0b1
2	Justin Gatlin	USA	bronze	9.79	2012	USA	10.214505	1.634321	#c59e8a	#98715d
3	Usain Bolt	JAM	gold	9.69	2008	JAM	10.319917	0.619195	#efcf6d	#c8a850
4	Richard Thompson	TRI	silver	9.89	2008	TRI	10.111223	2.628918	#cccccc	#b0b0b1

To enable this extension, add “bokeh.sphinxext.bokeh_dataframe” to the extensions list in your Sphinx configuration module.

bokeh_enum#

Thoroughly document Bokeh enumerations

The bokeh-enum directive generates useful documentation for enumerations, including all the allowable values. If the number of values is large, the full list is put in a collapsible code block.

This directive takes the name of a Bokeh enum variable as the argument and the module name as an option. An optional description may be added as content:

.. bokeh-enum:: baz
    :module: bokeh.sphinxext.sample

    Specify a baz style

Examples

The directive above will generate the following output:

baz = Enumeration(a, b, c)#: Specify a baz style

Although bokeh-enum may be used explicitly, it is more often convenient in conjunction with the bokeh_autodoc extension. Together, the same output above will be generated directly from the following code:

#: Specify a baz style
baz = enumeration("a", "b", "c")

To enable this extension, add “bokeh.sphinxext.bokeh_enum” to the extensions list in your Sphinx configuration module.

bokeh_gallery#

Generate a gallery of Bokeh plots from a configuration file.

To enable this extension, add “bokeh.sphinxext.bokeh_gallery” to the extensions list in your Sphinx configuration module.

bokeh_jinja#

Automatically document Bokeh Jinja2 templates.

This directive takes the module path to an attribute name that defines a Jinja2 template:

.. bokeh-jinja:: bokeh.core.templates.FILE

Any template parameters will be displayed and the template source code will be rendered in a collapsible code block. For example, the usage above will generate the following output:

FILE = <Template 'file.html'>

Renders Bokeh models into a basic .html file.

Parameters:

title (str) – value for <title> tags
plot_resources (str) – typically the output of RESOURCES
plot_script (str) – typically the output of PLOT_SCRIPT

Users can customize the file output by providing their own Jinja2 template that accepts these same parameters.

To enable this extension, add “bokeh.sphinxext.bokeh_jinja” to the extensions list in your Sphinx configuration module.

bokeh_model#

Thoroughly document Bokeh model classes.

The bokeh-model directive will automatically document all the attributes (including Bokeh properties) of a Bokeh Model subclass. A JSON prototype showing all the possible JSON fields will also be generated.

This directive takes the name of a Bokeh model class as an argument and its module as an option:

.. bokeh-model:: Foo
    :module: bokeh.sphinxext.sample

Examples

For the following definition of bokeh.sphinxext.sample.Foo:

class Foo(Model):
    ''' This is a Foo model. '''
    index = Either(Auto, Enum('abc', 'def', 'xzy'), help="doc for index")
    value = Tuple(Float, Float, help="doc for value")

usage yields the output:

class Foo(*args: Any, id: ID | None = None, **kwargs: Any)[source]#

Bases: Model

This is a Foo model.

index = 'auto'#

Type:: Either(Auto, Enum(Enumeration(abc, def, xzy)))

doc for index

name = None#

Type:: Nullable(String)

An arbitrary, user-supplied name for this model.

This name can be useful when querying the document to retrieve specific Bokeh models.

>>> plot.circle([1,2,3], [4,5,6], name="temp")
>>> plot.select(name="temp")
[GlyphRenderer(id='399d53f5-73e9-44d9-9527-544b761c7705', ...)]

Note

No uniqueness guarantees or other conditions are enforced on any names that are provided, nor is the name used directly by Bokeh for any reason.

syncable = True#

Type:: Bool

Indicates whether this model should be synchronized back to a Bokeh server when updated in a web browser. Setting to False may be useful to reduce network traffic when dealing with frequently updated objects whose updated values we don’t need.

Note

Setting this property to False will prevent any on_change() callbacks on this object from triggering. However, any JS-side callbacks will still work.

tags = []#

Type:: List

An optional list of arbitrary, user-supplied values to attach to this model.

This data can be useful when querying the document to retrieve specific Bokeh models:

>>> r = plot.circle([1,2,3], [4,5,6])
>>> r.tags = ["foo", 10]
>>> plot.select(tags=['foo', 10])
[GlyphRenderer(id='1de4c3df-a83d-480a-899b-fb263d3d5dd9', ...)]

Or simply a convenient way to attach any necessary metadata to a model that can be accessed by CustomJS callbacks, etc.

Note

No uniqueness guarantees or other conditions are enforced on any tags that are provided, nor are the tags used directly by Bokeh for any reason.

value = Undefined#

Type:: Tuple(Float, Float)

doc for value

apply_theme(property_values: dict[str, Any]) → None#

Apply a set of theme values which will be used rather than defaults, but will not override application-set values.

The passed-in dictionary may be kept around as-is and shared with other instances to save memory (so neither the caller nor the HasProps instance should modify it).

Parameters:: property_values (dict) – theme values to use in place of defaults
Returns:: None

classmethod clear_extensions() → None#

Clear any currently defined custom extensions.

Serialization calls will result in any currently defined custom extensions being included with the generated Document, whether or not there are utlized. This method can be used to clear out all existing custom extension definitions.

clone(**overrides: Any) → Self#

Duplicate a HasProps object.

This creates a shallow clone of the original model, i.e. any mutable containers or child models will not be duplicated. Allows to override particular properties while cloning.

classmethod dataspecs() → dict[str, DataSpec]#

Collect the names of all DataSpec properties on this class.

This method always traverses the class hierarchy and includes properties defined on any parent classes.

Returns:: names of DataSpec properties
Return type:: set[str]

classmethod descriptors() → list[PropertyDescriptor[Any]]#: List of property descriptors in the order of definition.

destroy() → None#: Clean up references to the document and property

equals(other: HasProps) → bool#

Structural equality of models.

Parameters:: other (HasProps) – the other instance to compare to
Returns:: True, if properties are structurally equal, otherwise False

js_link(attr: str, other: Model, other_attr: str, attr_selector: int | str | None = None) → None#

Link two Bokeh model properties using JavaScript.

This is a convenience method that simplifies adding a CustomJS callback to update one Bokeh model property whenever another changes value.

Parameters:

attr (str) – The name of a Bokeh property on this model
other (Model) – A Bokeh model to link to self.attr
other_attr (str) – The property on other to link together
attr_selector (int | str) – The index to link an item in a subscriptable attr

Added in version 1.1

Raises:: ValueError –

Examples

This code with js_link:

select.js_link('value', plot, 'sizing_mode')

is equivalent to the following:

from bokeh.models import CustomJS
select.js_on_change('value',
    CustomJS(args=dict(other=plot),
             code="other.sizing_mode = this.value"
    )
)

Additionally, to use attr_selector to attach the left side of a range slider to a plot’s x_range:

range_slider.js_link('value', plot.x_range, 'start', attr_selector=0)

which is equivalent to:

from bokeh.models import CustomJS
range_slider.js_on_change('value',
    CustomJS(args=dict(other=plot.x_range),
             code="other.start = this.value[0]"
    )
)

js_on_change(event: str, *callbacks: JSChangeCallback) → None#

Attach a CustomJS callback to an arbitrary BokehJS model event.

On the BokehJS side, change events for model properties have the form "change:property_name". As a convenience, if the event name passed to this method is also the name of a property on the model, then it will be prefixed with "change:" automatically:

# these two are equivalent
source.js_on_change('data', callback)
source.js_on_change('change:data', callback)

However, there are other kinds of events that can be useful to respond to, in addition to property change events. For example to run a callback whenever data is streamed to a ColumnDataSource, use the "stream" event on the source:

source.js_on_change('streaming', callback)

classmethod lookup(name: str, *, raises: bool = True) → PropertyDescriptor[Any] | None#

Find the PropertyDescriptor for a Bokeh property on a class, given the property name.

Parameters:

name (str) – name of the property to search for
raises (bool) – whether to raise or return None if missing

Returns:

descriptor for property named name

Return type:

PropertyDescriptor

on_change(attr: str, *callbacks: PropertyCallback) → None#

Add a callback on this object to trigger when attr changes.

Parameters:

attr (str) – an attribute name on this object
*callbacks (callable) – callback functions to register

Returns:

None

Examples

widget.on_change('value', callback1, callback2, ..., callback_n)

on_event(event: str | type[Event], *callbacks: Callable[[Event], None] | Callable[[], None]) → None#

Run callbacks when the specified event occurs on this Model

Not all Events are supported for all Models. See specific Events in bokeh.events for more information on which Models are able to trigger them.

classmethod parameters() → list[Parameter]#

Generate Python Parameter values suitable for functions that are derived from the glyph.

Returns:: list(Parameter)

classmethod properties(*, _with_props: bool = False) → set[str] | dict[str, Property[Any]]#

Collect the names of properties on this class.

Warning

In a future version of Bokeh, this method will return a dictionary mapping property names to property objects. To future-proof this current usage of this method, wrap the return value in list.

Returns:: property names

classmethod properties_with_refs() → dict[str, Property[Any]]#

Collect the names of all properties on this class that also have references.

This method always traverses the class hierarchy and includes properties defined on any parent classes.

Returns:: names of properties that have references
Return type:: set[str]

properties_with_values(*, include_defaults: bool = True, include_undefined: bool = False) → dict[str, Any]#

Collect a dict mapping property names to their values.

This method always traverses the class hierarchy and includes properties defined on any parent classes.

Non-serializable properties are skipped and property values are in “serialized” format which may be slightly different from the values you would normally read from the properties; the intent of this method is to return the information needed to losslessly reconstitute the object instance.

Parameters:: include_defaults (bool, optional) – Whether to include properties that haven’t been explicitly set since the object was created. (default: True)
Returns:: mapping from property names to their values
Return type:: dict

query_properties_with_values(query: Callable[[PropertyDescriptor[Any]], bool], *, include_defaults: bool = True, include_undefined: bool = False) → dict[str, Any]#

Query the properties values of HasProps instances with a predicate.

Parameters:

query (callable) – A callable that accepts property descriptors and returns True or False
include_defaults (bool, optional) – Whether to include properties that have not been explicitly set by a user (default: True)

Returns:

mapping of property names and values for matching properties

Return type:

dict

references() → set[Model]#: Returns all Models that this object has references to.

remove_on_change(attr: str, *callbacks: Callable[[str, Any, Any], None]) → None#: Remove a callback from this object

select(selector: SelectorType) → Iterable[Model]#

Query this object and all of its references for objects that match the given selector.

Parameters:: selector (JSON-like)
Returns:: seq[Model]

select_one(selector: SelectorType) → Model | None#

Query this object and all of its references for objects that match the given selector. Raises an error if more than one object is found. Returns single matching object, or None if nothing is found :param selector: :type selector: JSON-like

Returns:: Model

set_from_json(name: str, value: Any, *, setter: Setter | None = None) → None#

Set a property value on this object from JSON.

Parameters:

name (str) – name of the attribute to set
value (JSON-value) – value to set to the attribute to
setter (ClientSession or ServerSession or None, optional) –
This is used to prevent “boomerang” updates to Bokeh apps.

In the context of a Bokeh server application, incoming updates to properties will be annotated with the session that is doing the updating. This value is propagated through any subsequent change notifications that the update triggers. The session can compare the event setter to itself, and suppress any updates that originate from itself.

Returns:

None

set_select(selector: type[Model] | SelectorType, updates: dict[str, Any]) → None#

Update objects that match a given selector with the specified attribute/value updates.

Parameters:

selector (JSON-like)
updates (dict)

Returns:

None

themed_values() → dict[str, Any] | None#

Get any theme-provided overrides.

Results are returned as a dict from property name to value, or None if no theme overrides any values for this instance.

Returns:: dict or None

to_serializable(serializer: Serializer) → ObjectRefRep#: Converts this object to a serializable representation.

trigger(attr: str, old: Any, new: Any, hint: DocumentPatchedEvent | None = None, setter: Setter | None = None) → None#

unapply_theme() → None#

Remove any themed values and restore defaults.

Returns:: None

update(**kwargs: Any) → None#

Updates the object’s properties from the given keyword arguments.

Returns:: None

Examples

The following are equivalent:

from bokeh.models import Range1d

r = Range1d

# set properties individually:
r.start = 10
r.end = 20

# update properties together:
r.update(start=10, end=20)

property document: Document | None#: The Document this model is attached to (can be None)

The bokeh-model direction may be used explicitly, but it can also be used in conjunction with the bokeh_autodoc extension.

To enable this extension, add “bokeh.sphinxext.bokeh_model” to the extensions list in your Sphinx configuration module.

bokeh_options#

Thoroughly document Bokeh options classes.

The bokeh-options directive will automatically document all the properties of a Bokeh Options class under a heading of “Keyword Args”.

This directive takes the name of a Bokeh Options subclass as the argument, and its module as an option:

.. bokeh-options:: Opts
    :module: bokeh.sphinxext.sample

Examples

For the following definition of bokeh.sphinxext.sample.Opts:

class Opts(Options):
    ''' This is an Options class '''

    host = String(default="localhost", help="a host to connect to")
    port = Int(default=5890, help="a port to connect to")

the above usage yields the output:

Keyword Arguments:

host (String): a host to connect to (default: ‘localhost’)
port (Int): a port to connect to (default: 5890)

To enable this extension, add “bokeh.sphinxext.bokeh_options” to the extensions list in your Sphinx configuration module.

bokeh_palette#

Generate an inline visual representations of a single color palette.

The :bokeh-palette: role can be used by providing any of the following:

a palette name from bokeh.palettes, e.g. Spectral9
a palette function from bokeh.palettes called with argument, e.g. viridis(12)
An explicit list of colors: ['#000000', '#333333', '#666666', '#999999', '#cccccc', '#ffffff']

The following usage of the directive is valid:

by name

:bokeh-palette:`Spectral9`

by function

:bokeh-palette:`viridis(12)`

by list

:bokeh-palette:`['#000000', '#333333', '#666666', '#999999', '#cccccc', '#ffffff']`

Palette swatches are 20 pixels in height. For palettes shorter than 20 colors, the default width for the swatches is 20 pixels. If larger palettes are given, the width of the HTML spans is progressively reduced, down to a minimum of one pixel. For instance displaying the full Viridis palette with the expression

:bokeh-palette:`viridis(256)`

Will generate the output:

To enable this extension, add “bokeh.sphinxext.bokeh_palette” to the extensions list in your Sphinx configuration module.

bokeh_palette_group#

Generate visual representations of palettes in Bokeh palette groups.

The bokeh.palettes modules expose attributes such as mpl, brewer, and d3 that provide groups of palettes. The bokeh-palette-group directive accepts the name of one of these groups, and generates a visual matrix of colors for every palette in the group.

As an example, the following usage of the directive:

.. bokeh-palette-group:: mpl

Generates the output:

Cividis
3
4
5
6
7
8
9
10
11

Inferno
3
4
5
6
7
8
9
10
11

Magma
3
4
5
6
7
8
9
10
11

Plasma
3
4
5
6
7
8
9
10
11

Viridis
3
4
5
6
7
8
9
10
11

Note

This extension assumes both Bootstrap and JQuery are present (which is the case for the Bokeh documentation theme). If using this theme outside the Bokeh documentation, be sure to include those resources by hand.

To enable this extension, add “bokeh.sphinxext.bokeh_palette_group” to the extensions list in your Sphinx configuration module.

bokeh_plot#

Include Bokeh plots in Sphinx HTML documentation.

For other output types, the placeholder text [graph] will be generated.

The bokeh-plot directive can be used by either supplying:

A path to a source file as the argument to the directive:

.. bokeh-plot:: path/to/plot.py

Note

.py scripts are not scanned automatically! In order to include certain directories into .py scanning process use following directive in sphinx conf.py file: bokeh_plot_pyfile_include_dirs = [“dir1”,”dir2”]

Inline code as the content of the directive:

.. bokeh-plot::

    from bokeh.plotting import figure, output_file, show

    output_file("example.html")

    x = [1, 2, 3, 4, 5]
    y = [6, 7, 6, 4, 5]

    p = figure(title="example", width=300, height=300)
    p.line(x, y, line_width=2)
    p.scatter(x, y, size=10, fill_color="white")

    show(p)

This directive also works in conjunction with Sphinx autodoc, when used in docstrings.

The bokeh-plot directive accepts the following options:

process-docstring (bool):: Whether to display the docstring in a formatted block separate from the source.
source-position (enum(‘above’, ‘below’, ‘none’)):: Where to locate the block of formatted source code (if anywhere).
linenos (bool):: Whether to display line numbers along with the source.

Examples

The inline example code above produces the following output:

from bokeh.plotting import figure, output_file, show

output_file("example.html")

x = [1, 2, 3, 4, 5]
y = [6, 7, 6, 4, 5]

p = figure(title="example", width=300, height=300)
p.line(x, y, line_width=2)
p.scatter(x, y, size=10, fill_color="white")

show(p)

To enable this extension, add “bokeh.sphinxext.bokeh_plot” to the extensions list in your Sphinx configuration module.

bokeh_prop#

Thoroughly document Bokeh property attributes.

The bokeh-prop directive generates documentation for Bokeh model properties, including cross links to the relevant property types. Additionally, any per-attribute help strings are also displayed.

This directive takes the name (class.attr) of a Bokeh property as its argument and the module as an option:

.. bokeh-prop:: Bar.thing
    :module: bokeh.sphinxext.sample

Examples

For the following definition of bokeh.sphinxext.sample.Bar:

class Bar(Model):
    ''' This is a Bar model. '''
    thing = List(Int, help="doc for thing")

the above usage yields the output:

thing = []#

Type:: List

doc for thing

The bokeh-prop direction may be used explicitly, but it can also be used in conjunction with the bokeh_autodoc extension.

To enable this extension, add “bokeh.sphinxext.bokeh_prop” to the extensions list in your Sphinx configuration module.

bokeh_releases#

Publish all Bokeh release notes on to a single page.

This directive collect all the release notes files in the docs/releases subdirectory, and includes them in reverse version order. Typical usage:

.. toctree::

.. bokeh-releases::

To avoid warnings about orphaned files, add the following to the Sphinx conf.py file:

exclude_patterns = ['docs/releases/*']

To enable this extension, add “bokeh.sphinxext.bokeh_releases” to the extensions list in your Sphinx configuration module.

bokeh_roles#

Simplify linking to Bokeh Github resources.

This module provides roles that can be used to easily reference information from various sources in the Bokeh project structure:

:bokeh-commit: : link to a specific commit

:bokeh-issue: : link to an issue

:bokeh-minpy: : provide the minimum supported Python version

:bokeh-pull: : link to a pull request

:bokeh-requires: : list the install requires from pyproject.toml

:bokeh-tree: : (versioned) link to a source tree URL

Examples

The following code:

The repo history shows that :bokeh-commit:`bf19bcb` was made in
in :bokeh-pull:`1698`, which closed :bokeh-issue:`1694`. This included
updating all of the files in the :bokeh-tree:`examples` subdirectory.

yields the output:

The repo history shows that commit bf19bcb was made in in pull request 1698,which closed #1694. This included updating all of the files in the examples subdirectory.

To enable this extension, add “bokeh.sphinxext.bokeh_roles” to the extensions list in your Sphinx configuration module.

bokeh_sitemap#

Generate a sitemap.txt to aid with search indexing.

sitemap.txt is a plain text list of all the pages in the docs site. Each URL is listed on a line in the text file. It is machine readable and used by search engines to know what pages are available for indexing.

All that is required to generate the sitemap is to list this module bokeh.sphinxext.sitemap in the list of extensions in the Sphinx configuration file conf.py.

To enable this extension, add “bokeh.sphinxext.bokeh_sitemap” to the extensions list in your Sphinx configuration module.

bokeh.sphinxext#

bokeh_autodoc#

bokeh_color#

bokeh_dataframe#

bokeh_enum#

bokeh_gallery#

bokeh_jinja#

bokeh_model#

bokeh_options#

bokeh_palette#

bokeh_palette_group#

Cividis

Inferno

Magma

Plasma

Viridis

bokeh_plot#

bokeh_prop#

bokeh_releases#

bokeh_roles#

bokeh_sitemap#