mappers#

Models for mapping values from one range or space to another in the client.

Mappers (as opposed to scales) are not presumed to be invertible.

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

Bases: CategoricalMapper, ColorMapper

Map categorical factors to colors.

Values that are passed to this mapper that are not in the factors list will be mapped to nan_color.

JSON Prototype
{
  "end": null, 
  "factors": {
    "name": "unset", 
    "type": "symbol"
  }, 
  "id": "p58915", 
  "js_event_callbacks": {
    "type": "map"
  }, 
  "js_property_callbacks": {
    "type": "map"
  }, 
  "name": null, 
  "nan_color": "gray", 
  "palette": {
    "name": "unset", 
    "type": "symbol"
  }, 
  "start": 0, 
  "subscribed_events": {
    "type": "set"
  }, 
  "syncable": true, 
  "tags": []
}
end = None#
Type:

Nullable(Int)

A start index to “slice” data factors with before mapping.

For example, if the data to color map consists of 2-level factors such as ["2016", "sales"] and ["2017", "marketing"], then setting end=1 will perform color mapping only based on the first sub-factor (i.e. in this case based on the year "2016" or "2017")

If None then all sub-factors from start to the end of the factor will be used for color mapping.

factors = Undefined#
Type:

FactorSeq

A sequence of factors / categories that map to the some target range. For example the following color mapper:

mapper = CategoricalColorMapper(palette=["red", "blue"], factors=["foo", "bar"])

will map the factor "foo" to red and the factor "bar" to blue.

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.

nan_color = 'gray'#
Type:

Color

Color to be used if data is NaN or otherwise not mappable.

Acceptable values are:

  • any of the named CSS colors, e.g 'green', 'indigo'

  • RGB(A) hex strings, e.g., '#FF0000', '#44444444'

  • CSS4 color strings, e.g., 'rgba(255, 0, 127, 0.6)', 'rgb(0 127 0 / 1.0)', or 'hsl(60deg 100% 50% / 1.0)'

  • a 3-tuple of integers (r, g, b) between 0 and 255

  • a 4-tuple of (r, g, b, a) where r, g, b are integers between 0 and 255, and a is between 0 and 1

  • a 32-bit unsigned integer using the 0xRRGGBBAA byte order pattern

palette = Undefined#
Type:

Seq(Color)

A sequence of colors to use as the target palette for mapping.

This property can also be set as a String, to the name of any of the palettes shown in bokeh.palettes.

start = 0#
Type:

Int

A start index to “slice” data factors with before mapping.

For example, if the data to color map consists of 2-level factors such as ["2016", "sales"] and ["2016", "marketing"], then setting start=1 will perform color mapping only based on the second sub-factor (i.e. in this case based on the department "sales" or "marketing")

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.

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

clone() 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.

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

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 (Union[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: EventCallback) 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

  • json – (JSON-value) : value to set to the attribute to

  • models (dict or None, optional) –

    Mapping of model ids to models (default: None)

    This is needed in cases where the attributes to update also have values that have references.

  • 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)

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

Bases: Mapper

Base class for mappers that map categorical factors to other values.

Note

This is an abstract base class used to help organize the hierarchy of Bokeh model types. It is not useful to instantiate on its own.

JSON Prototype
{
  "end": null, 
  "factors": {
    "name": "unset", 
    "type": "symbol"
  }, 
  "id": "p58924", 
  "js_event_callbacks": {
    "type": "map"
  }, 
  "js_property_callbacks": {
    "type": "map"
  }, 
  "name": null, 
  "start": 0, 
  "subscribed_events": {
    "type": "set"
  }, 
  "syncable": true, 
  "tags": []
}
end = None#
Type:

Nullable(Int)

A start index to “slice” data factors with before mapping.

For example, if the data to color map consists of 2-level factors such as ["2016", "sales"] and ["2017", "marketing"], then setting end=1 will perform color mapping only based on the first sub-factor (i.e. in this case based on the year "2016" or "2017")

If None then all sub-factors from start to the end of the factor will be used for color mapping.

factors = Undefined#
Type:

FactorSeq

A sequence of factors / categories that map to the some target range. For example the following color mapper:

mapper = CategoricalColorMapper(palette=["red", "blue"], factors=["foo", "bar"])

will map the factor "foo" to red and the factor "bar" to blue.

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.

start = 0#
Type:

Int

A start index to “slice” data factors with before mapping.

For example, if the data to color map consists of 2-level factors such as ["2016", "sales"] and ["2016", "marketing"], then setting start=1 will perform color mapping only based on the second sub-factor (i.e. in this case based on the department "sales" or "marketing")

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.

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

clone() 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.

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

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 (Union[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: EventCallback) 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

  • json – (JSON-value) : value to set to the attribute to

  • models (dict or None, optional) –

    Mapping of model ids to models (default: None)

    This is needed in cases where the attributes to update also have values that have references.

  • 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)

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

Bases: CategoricalMapper

Map categorical factors to marker types.

Values that are passed to this mapper that are not in the factors list will be mapped to default_value.

Note

This mappers is primarily only useful with the Scatter marker glyph that be parameterized by marker type.

JSON Prototype
{
  "default_value": "circle", 
  "end": null, 
  "factors": {
    "name": "unset", 
    "type": "symbol"
  }, 
  "id": "p58931", 
  "js_event_callbacks": {
    "type": "map"
  }, 
  "js_property_callbacks": {
    "type": "map"
  }, 
  "markers": {
    "name": "unset", 
    "type": "symbol"
  }, 
  "name": null, 
  "start": 0, 
  "subscribed_events": {
    "type": "set"
  }, 
  "syncable": true, 
  "tags": []
}
default_value = 'circle'#
Type:

MarkerType

A marker type to use in case an unrecognized factor is passed in to be mapped.

end = None#
Type:

Nullable(Int)

A start index to “slice” data factors with before mapping.

For example, if the data to color map consists of 2-level factors such as ["2016", "sales"] and ["2017", "marketing"], then setting end=1 will perform color mapping only based on the first sub-factor (i.e. in this case based on the year "2016" or "2017")

If None then all sub-factors from start to the end of the factor will be used for color mapping.

factors = Undefined#
Type:

FactorSeq

A sequence of factors / categories that map to the some target range. For example the following color mapper:

mapper = CategoricalColorMapper(palette=["red", "blue"], factors=["foo", "bar"])

will map the factor "foo" to red and the factor "bar" to blue.

markers = Undefined#
Type:

Seq(MarkerType)

A sequence of marker types to use as the target for mapping.

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.

start = 0#
Type:

Int

A start index to “slice” data factors with before mapping.

For example, if the data to color map consists of 2-level factors such as ["2016", "sales"] and ["2016", "marketing"], then setting start=1 will perform color mapping only based on the second sub-factor (i.e. in this case based on the department "sales" or "marketing")

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.

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

clone() 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.

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

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 (Union[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: EventCallback) 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

  • json – (JSON-value) : value to set to the attribute to

  • models (dict or None, optional) –

    Mapping of model ids to models (default: None)

    This is needed in cases where the attributes to update also have values that have references.

  • 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)

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

Bases: CategoricalMapper

Map categorical factors to hatch fill patterns.

Values that are passed to this mapper that are not in the factors list will be mapped to default_value.

Added in version 1.1.1

JSON Prototype
{
  "default_value": " ", 
  "end": null, 
  "factors": {
    "name": "unset", 
    "type": "symbol"
  }, 
  "id": "p58940", 
  "js_event_callbacks": {
    "type": "map"
  }, 
  "js_property_callbacks": {
    "type": "map"
  }, 
  "name": null, 
  "patterns": {
    "name": "unset", 
    "type": "symbol"
  }, 
  "start": 0, 
  "subscribed_events": {
    "type": "set"
  }, 
  "syncable": true, 
  "tags": []
}
default_value = ' '#
Type:

HatchPatternType

A hatch pattern to use in case an unrecognized factor is passed in to be mapped.

end = None#
Type:

Nullable(Int)

A start index to “slice” data factors with before mapping.

For example, if the data to color map consists of 2-level factors such as ["2016", "sales"] and ["2017", "marketing"], then setting end=1 will perform color mapping only based on the first sub-factor (i.e. in this case based on the year "2016" or "2017")

If None then all sub-factors from start to the end of the factor will be used for color mapping.

factors = Undefined#
Type:

FactorSeq

A sequence of factors / categories that map to the some target range. For example the following color mapper:

mapper = CategoricalColorMapper(palette=["red", "blue"], factors=["foo", "bar"])

will map the factor "foo" to red and the factor "bar" to blue.

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.

patterns = Undefined#
Type:

Seq(HatchPatternType)

A sequence of marker types to use as the target for mapping.

start = 0#
Type:

Int

A start index to “slice” data factors with before mapping.

For example, if the data to color map consists of 2-level factors such as ["2016", "sales"] and ["2016", "marketing"], then setting start=1 will perform color mapping only based on the second sub-factor (i.e. in this case based on the department "sales" or "marketing")

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.

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

clone() 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.

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

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 (Union[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: EventCallback) 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

  • json – (JSON-value) : value to set to the attribute to

  • models (dict or None, optional) –

    Mapping of model ids to models (default: None)

    This is needed in cases where the attributes to update also have values that have references.

  • 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)

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

Bases: Mapper

Base class for color mapper types.

Note

This is an abstract base class used to help organize the hierarchy of Bokeh model types. It is not useful to instantiate on its own.

JSON Prototype
{
  "id": "p58949", 
  "js_event_callbacks": {
    "type": "map"
  }, 
  "js_property_callbacks": {
    "type": "map"
  }, 
  "name": null, 
  "nan_color": "gray", 
  "palette": {
    "name": "unset", 
    "type": "symbol"
  }, 
  "subscribed_events": {
    "type": "set"
  }, 
  "syncable": true, 
  "tags": []
}
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.

nan_color = 'gray'#
Type:

Color

Color to be used if data is NaN or otherwise not mappable.

Acceptable values are:

  • any of the named CSS colors, e.g 'green', 'indigo'

  • RGB(A) hex strings, e.g., '#FF0000', '#44444444'

  • CSS4 color strings, e.g., 'rgba(255, 0, 127, 0.6)', 'rgb(0 127 0 / 1.0)', or 'hsl(60deg 100% 50% / 1.0)'

  • a 3-tuple of integers (r, g, b) between 0 and 255

  • a 4-tuple of (r, g, b, a) where r, g, b are integers between 0 and 255, and a is between 0 and 1

  • a 32-bit unsigned integer using the 0xRRGGBBAA byte order pattern

palette = Undefined#
Type:

Seq(Color)

A sequence of colors to use as the target palette for mapping.

This property can also be set as a String, to the name of any of the palettes shown in bokeh.palettes.

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.

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

clone() 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.

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

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 (Union[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: EventCallback) 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

  • json – (JSON-value) : value to set to the attribute to

  • models (dict or None, optional) –

    Mapping of model ids to models (default: None)

    This is needed in cases where the attributes to update also have values that have references.

  • 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)

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

Bases: ColorMapper

Base class for continuous color mapper types.

Note

This is an abstract base class used to help organize the hierarchy of Bokeh model types. It is not useful to instantiate on its own.

JSON Prototype
{
  "domain": [], 
  "high": null, 
  "high_color": null, 
  "id": "p58955", 
  "js_event_callbacks": {
    "type": "map"
  }, 
  "js_property_callbacks": {
    "type": "map"
  }, 
  "low": null, 
  "low_color": null, 
  "name": null, 
  "nan_color": "gray", 
  "palette": {
    "name": "unset", 
    "type": "symbol"
  }, 
  "subscribed_events": {
    "type": "set"
  }, 
  "syncable": true, 
  "tags": []
}
domain = []#
Type:

List

A collection of glyph renderers to pool data from for establishing data metrics. If empty, mapped data will be used instead.

high = None#
Type:

Nullable(Float)

The maximum value of the range to map into the palette. Values above this are clamped to high. If None, the value is inferred from data.

high_color = None#
Type:

Nullable(Color)

Color to be used if data is higher than high value. If None, values higher than high are mapped to the last color in the palette.

low = None#
Type:

Nullable(Float)

The minimum value of the range to map into the palette. Values below this are clamped to low. If None, the value is inferred from data.

low_color = None#
Type:

Nullable(Color)

Color to be used if data is lower than low value. If None, values lower than low are mapped to the first color in the palette.

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.

nan_color = 'gray'#
Type:

Color

Color to be used if data is NaN or otherwise not mappable.

Acceptable values are:

  • any of the named CSS colors, e.g 'green', 'indigo'

  • RGB(A) hex strings, e.g., '#FF0000', '#44444444'

  • CSS4 color strings, e.g., 'rgba(255, 0, 127, 0.6)', 'rgb(0 127 0 / 1.0)', or 'hsl(60deg 100% 50% / 1.0)'

  • a 3-tuple of integers (r, g, b) between 0 and 255

  • a 4-tuple of (r, g, b, a) where r, g, b are integers between 0 and 255, and a is between 0 and 1

  • a 32-bit unsigned integer using the 0xRRGGBBAA byte order pattern

palette = Undefined#
Type:

Seq(Color)

A sequence of colors to use as the target palette for mapping.

This property can also be set as a String, to the name of any of the palettes shown in bokeh.palettes.

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.

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

clone() 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.

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

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 (Union[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: EventCallback) 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

  • json – (JSON-value) : value to set to the attribute to

  • models (dict or None, optional) –

    Mapping of model ids to models (default: None)

    This is needed in cases where the attributes to update also have values that have references.

  • 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)

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

Bases: ScanningColorMapper

JSON Prototype
{
  "bins": 65536, 
  "domain": [], 
  "high": null, 
  "high_color": null, 
  "id": "p58966", 
  "js_event_callbacks": {
    "type": "map"
  }, 
  "js_property_callbacks": {
    "type": "map"
  }, 
  "low": null, 
  "low_color": null, 
  "name": null, 
  "nan_color": "gray", 
  "palette": {
    "name": "unset", 
    "type": "symbol"
  }, 
  "rescale_discrete_levels": false, 
  "subscribed_events": {
    "type": "set"
  }, 
  "syncable": true, 
  "tags": []
}
bins = 65536#
Type:

Int

Number of histogram bins

domain = []#
Type:

List

A collection of glyph renderers to pool data from for establishing data metrics. If empty, mapped data will be used instead.

high = None#
Type:

Nullable(Float)

The maximum value of the range to map into the palette. Values above this are clamped to high. If None, the value is inferred from data.

high_color = None#
Type:

Nullable(Color)

Color to be used if data is higher than high value. If None, values higher than high are mapped to the last color in the palette.

low = None#
Type:

Nullable(Float)

The minimum value of the range to map into the palette. Values below this are clamped to low. If None, the value is inferred from data.

low_color = None#
Type:

Nullable(Color)

Color to be used if data is lower than low value. If None, values lower than low are mapped to the first color in the palette.

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.

nan_color = 'gray'#
Type:

Color

Color to be used if data is NaN or otherwise not mappable.

Acceptable values are:

  • any of the named CSS colors, e.g 'green', 'indigo'

  • RGB(A) hex strings, e.g., '#FF0000', '#44444444'

  • CSS4 color strings, e.g., 'rgba(255, 0, 127, 0.6)', 'rgb(0 127 0 / 1.0)', or 'hsl(60deg 100% 50% / 1.0)'

  • a 3-tuple of integers (r, g, b) between 0 and 255

  • a 4-tuple of (r, g, b, a) where r, g, b are integers between 0 and 255, and a is between 0 and 1

  • a 32-bit unsigned integer using the 0xRRGGBBAA byte order pattern

palette = Undefined#
Type:

Seq(Color)

A sequence of colors to use as the target palette for mapping.

This property can also be set as a String, to the name of any of the palettes shown in bokeh.palettes.

rescale_discrete_levels = False#
Type:

Bool

If there are only a few discrete levels in the values that are color mapped then rescale_discrete_levels=True decreases the lower limit of the span so that the values are rendered towards the top end of the palette.

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.

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

clone() 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.

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

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 (Union[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: EventCallback) 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

  • json – (JSON-value) : value to set to the attribute to

  • models (dict or None, optional) –

    Mapping of model ids to models (default: None)

    This is needed in cases where the attributes to update also have values that have references.

  • 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)

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

Bases: ContinuousColorMapper

Map numbers in a range [low, high] linearly into a sequence of colors (a palette).

For example, if the range is [0, 99] and the palette is ['red', 'green', 'blue'], the values would be mapped as follows:

      x < 0  : 'red'     # values < low are clamped
 0 <= x < 33 : 'red'
33 <= x < 66 : 'green'
66 <= x < 99 : 'blue'
99 <= x      : 'blue'    # values > high are clamped
JSON Prototype
{
  "domain": [], 
  "high": null, 
  "high_color": null, 
  "id": "p58979", 
  "js_event_callbacks": {
    "type": "map"
  }, 
  "js_property_callbacks": {
    "type": "map"
  }, 
  "low": null, 
  "low_color": null, 
  "name": null, 
  "nan_color": "gray", 
  "palette": {
    "name": "unset", 
    "type": "symbol"
  }, 
  "subscribed_events": {
    "type": "set"
  }, 
  "syncable": true, 
  "tags": []
}
domain = []#
Type:

List

A collection of glyph renderers to pool data from for establishing data metrics. If empty, mapped data will be used instead.

high = None#
Type:

Nullable(Float)

The maximum value of the range to map into the palette. Values above this are clamped to high. If None, the value is inferred from data.

high_color = None#
Type:

Nullable(Color)

Color to be used if data is higher than high value. If None, values higher than high are mapped to the last color in the palette.

low = None#
Type:

Nullable(Float)

The minimum value of the range to map into the palette. Values below this are clamped to low. If None, the value is inferred from data.

low_color = None#
Type:

Nullable(Color)

Color to be used if data is lower than low value. If None, values lower than low are mapped to the first color in the palette.

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.

nan_color = 'gray'#
Type:

Color

Color to be used if data is NaN or otherwise not mappable.

Acceptable values are:

  • any of the named CSS colors, e.g 'green', 'indigo'

  • RGB(A) hex strings, e.g., '#FF0000', '#44444444'

  • CSS4 color strings, e.g., 'rgba(255, 0, 127, 0.6)', 'rgb(0 127 0 / 1.0)', or 'hsl(60deg 100% 50% / 1.0)'

  • a 3-tuple of integers (r, g, b) between 0 and 255

  • a 4-tuple of (r, g, b, a) where r, g, b are integers between 0 and 255, and a is between 0 and 1

  • a 32-bit unsigned integer using the 0xRRGGBBAA byte order pattern

palette = Undefined#
Type:

Seq(Color)

A sequence of colors to use as the target palette for mapping.

This property can also be set as a String, to the name of any of the palettes shown in bokeh.palettes.

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.

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

clone() 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.

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

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 (Union[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: EventCallback) 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

  • json – (JSON-value) : value to set to the attribute to

  • models (dict or None, optional) –

    Mapping of model ids to models (default: None)

    This is needed in cases where the attributes to update also have values that have references.

  • 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)

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

Bases: ContinuousColorMapper

Map numbers in a range [low, high] into a sequence of colors (a palette) on a natural logarithm scale.

For example, if the range is [0, 25] and the palette is ['red', 'green', 'blue'], the values would be mapped as follows:

         x < 0     : 'red'     # values < low are clamped
0     <= x < 2.72  : 'red'     # math.e ** 1
2.72  <= x < 7.39  : 'green'   # math.e ** 2
7.39  <= x < 20.09 : 'blue'    # math.e ** 3
20.09 <= x         : 'blue'    # values > high are clamped

Warning

The LogColorMapper only works for images with scalar values that are non-negative.

JSON Prototype
{
  "domain": [], 
  "high": null, 
  "high_color": null, 
  "id": "p58990", 
  "js_event_callbacks": {
    "type": "map"
  }, 
  "js_property_callbacks": {
    "type": "map"
  }, 
  "low": null, 
  "low_color": null, 
  "name": null, 
  "nan_color": "gray", 
  "palette": {
    "name": "unset", 
    "type": "symbol"
  }, 
  "subscribed_events": {
    "type": "set"
  }, 
  "syncable": true, 
  "tags": []
}
domain = []#
Type:

List

A collection of glyph renderers to pool data from for establishing data metrics. If empty, mapped data will be used instead.

high = None#
Type:

Nullable(Float)

The maximum value of the range to map into the palette. Values above this are clamped to high. If None, the value is inferred from data.

high_color = None#
Type:

Nullable(Color)

Color to be used if data is higher than high value. If None, values higher than high are mapped to the last color in the palette.

low = None#
Type:

Nullable(Float)

The minimum value of the range to map into the palette. Values below this are clamped to low. If None, the value is inferred from data.

low_color = None#
Type:

Nullable(Color)

Color to be used if data is lower than low value. If None, values lower than low are mapped to the first color in the palette.

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.

nan_color = 'gray'#
Type:

Color

Color to be used if data is NaN or otherwise not mappable.

Acceptable values are:

  • any of the named CSS colors, e.g 'green', 'indigo'

  • RGB(A) hex strings, e.g., '#FF0000', '#44444444'

  • CSS4 color strings, e.g., 'rgba(255, 0, 127, 0.6)', 'rgb(0 127 0 / 1.0)', or 'hsl(60deg 100% 50% / 1.0)'

  • a 3-tuple of integers (r, g, b) between 0 and 255

  • a 4-tuple of (r, g, b, a) where r, g, b are integers between 0 and 255, and a is between 0 and 1

  • a 32-bit unsigned integer using the 0xRRGGBBAA byte order pattern

palette = Undefined#
Type:

Seq(Color)

A sequence of colors to use as the target palette for mapping.

This property can also be set as a String, to the name of any of the palettes shown in bokeh.palettes.

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.

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

clone() 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.

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

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 (Union[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: EventCallback) 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

  • json – (JSON-value) : value to set to the attribute to

  • models (dict or None, optional) –

    Mapping of model ids to models (default: None)

    This is needed in cases where the attributes to update also have values that have references.

  • 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)

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

Bases: Transform

Base class for mappers.

Note

This is an abstract base class used to help organize the hierarchy of Bokeh model types. It is not useful to instantiate on its own.

JSON Prototype
{
  "id": "p59001", 
  "js_event_callbacks": {
    "type": "map"
  }, 
  "js_property_callbacks": {
    "type": "map"
  }, 
  "name": null, 
  "subscribed_events": {
    "type": "set"
  }, 
  "syncable": true, 
  "tags": []
}
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.

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

clone() 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.

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

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 (Union[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: EventCallback) 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

  • json – (JSON-value) : value to set to the attribute to

  • models (dict or None, optional) –

    Mapping of model ids to models (default: None)

    This is needed in cases where the attributes to update also have values that have references.

  • 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)

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

Bases: ColorMapper

Abstract base class for color mappers that operate on ImageStack glyphs.

These map 3D data arrays of shape (ny, nx, nstack) to 2D RGBA images of shape (ny, nx).

Note

This is an abstract base class used to help organize the hierarchy of Bokeh model types. It is not useful to instantiate on its own.

JSON Prototype
{
  "id": "p59005", 
  "js_event_callbacks": {
    "type": "map"
  }, 
  "js_property_callbacks": {
    "type": "map"
  }, 
  "name": null, 
  "nan_color": "gray", 
  "palette": {
    "name": "unset", 
    "type": "symbol"
  }, 
  "subscribed_events": {
    "type": "set"
  }, 
  "syncable": true, 
  "tags": []
}
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.

nan_color = 'gray'#
Type:

Color

Color to be used if data is NaN or otherwise not mappable.

Acceptable values are:

  • any of the named CSS colors, e.g 'green', 'indigo'

  • RGB(A) hex strings, e.g., '#FF0000', '#44444444'

  • CSS4 color strings, e.g., 'rgba(255, 0, 127, 0.6)', 'rgb(0 127 0 / 1.0)', or 'hsl(60deg 100% 50% / 1.0)'

  • a 3-tuple of integers (r, g, b) between 0 and 255

  • a 4-tuple of (r, g, b, a) where r, g, b are integers between 0 and 255, and a is between 0 and 1

  • a 32-bit unsigned integer using the 0xRRGGBBAA byte order pattern

palette = Undefined#
Type:

Seq(Color)

A sequence of colors to use as the target palette for mapping.

This property can also be set as a String, to the name of any of the palettes shown in bokeh.palettes.

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.

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

clone() 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.

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

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 (Union[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: EventCallback) 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

  • json – (JSON-value) : value to set to the attribute to

  • models (dict or None, optional) –

    Mapping of model ids to models (default: None)

    This is needed in cases where the attributes to update also have values that have references.

  • 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)

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

Bases: StackColorMapper

Maps 3D data arrays of shape (ny, nx, nstack) to 2D RGBA images of shape (ny, nx) using a palette of length nstack.

The mapping occurs in two stages. Firstly the RGB values are calculated using a weighted sum of the palette colors in the nstack direction. Then the alpha values are calculated using the alpha_mapper applied to the sum of the array in the nstack direction.

The RGB values calculated by the alpha_mapper are ignored by the color mapping but are used in any ColorBar that is displayed.

JSON Prototype
{
  "alpha_mapper": {
    "name": "unset", 
    "type": "symbol"
  }, 
  "color_baseline": null, 
  "id": "p59011", 
  "js_event_callbacks": {
    "type": "map"
  }, 
  "js_property_callbacks": {
    "type": "map"
  }, 
  "name": null, 
  "nan_color": "gray", 
  "palette": {
    "name": "unset", 
    "type": "symbol"
  }, 
  "stack_labels": null, 
  "subscribed_events": {
    "type": "set"
  }, 
  "syncable": true, 
  "tags": []
}
alpha_mapper = Undefined#
Type:

Instance(ContinuousColorMapper)

Color mapper used to calculate the alpha values of the mapped data.

color_baseline = None#
Type:

Nullable(Float)

Baseline value used for the weights when calculating the weighted sum of palette colors. If None then the minimum of the supplied data is used meaning that values at this minimum have a weight of zero and do not contribute to the weighted sum. As a special case, if all data for a particular output pixel are at the color baseline then the color is an evenly weighted average of the colors corresponding to all such values, to avoid the color being undefined.

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.

nan_color = 'gray'#
Type:

Color

Color to be used if data is NaN or otherwise not mappable.

Acceptable values are:

  • any of the named CSS colors, e.g 'green', 'indigo'

  • RGB(A) hex strings, e.g., '#FF0000', '#44444444'

  • CSS4 color strings, e.g., 'rgba(255, 0, 127, 0.6)', 'rgb(0 127 0 / 1.0)', or 'hsl(60deg 100% 50% / 1.0)'

  • a 3-tuple of integers (r, g, b) between 0 and 255

  • a 4-tuple of (r, g, b, a) where r, g, b are integers between 0 and 255, and a is between 0 and 1

  • a 32-bit unsigned integer using the 0xRRGGBBAA byte order pattern

palette = Undefined#
Type:

Seq(Color)

A sequence of colors to use as the target palette for mapping.

This property can also be set as a String, to the name of any of the palettes shown in bokeh.palettes.

stack_labels = None#
Type:

Nullable(Seq(String))

An optional sequence of strings to use as labels for the nstack stacks. If set, the number of labels should match the number of stacks and hence also the number of palette colors.

The labels are used in hover tooltips for ImageStack glyphs that use a WeightedStackColorMapper as their color mapper.

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.

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

clone() 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.

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

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 (Union[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: EventCallback) 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

  • json – (JSON-value) : value to set to the attribute to

  • models (dict or None, optional) –

    Mapping of model ids to models (default: None)

    This is needed in cases where the attributes to update also have values that have references.

  • 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)