tickers#

Models for computing good tick locations on different kinds of plots.

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

Bases: ContinuousTicker

Generate “nice” round ticks at any magnitude.

Creates ticks that are “base” multiples of a set of given mantissas. For example, with base=10 and mantissas=[1, 2, 5], the ticker will generate the sequence:

..., 0.1, 0.2, 0.5, 1, 2, 5, 10, 20, 50, 100, ...
JSON Prototype
{
  "base": 10.0, 
  "desired_num_ticks": 6, 
  "id": "p60480", 
  "js_event_callbacks": {
    "type": "map"
  }, 
  "js_property_callbacks": {
    "type": "map"
  }, 
  "mantissas": [
    1, 
    2, 
    5
  ], 
  "max_interval": null, 
  "min_interval": 0.0, 
  "name": null, 
  "num_minor_ticks": 5, 
  "subscribed_events": {
    "type": "set"
  }, 
  "syncable": true, 
  "tags": []
}
base = 10.0#
Type:

Float

The multiplier to use for scaling mantissas.

desired_num_ticks = 6#
Type:

Int

A desired target number of major tick positions to generate across the plot range.

mantissas = [1, 2, 5]#
Type:

Seq(Float)

The acceptable list numbers to generate multiples of.

max_interval = None#
Type:

Nullable(Float)

The largest allowable interval between two adjacent ticks.

Note

To specify an unbounded interval, set to None.

min_interval = 0.0#
Type:

Float

The smallest allowable interval between two adjacent ticks.

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.

num_minor_ticks = 5#
Type:

Int

The number of minor tick positions to generate between adjacent major tick values.

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(**overrides: Any) Self#

Duplicate a HasProps object.

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

classmethod dataspecs() dict[str, DataSpec]#

Collect the names of all DataSpec properties on this class.

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

Returns:

names of DataSpec properties

Return type:

set[str]

classmethod descriptors() list[PropertyDescriptor[Any]]#

List of property descriptors in the order of definition.

destroy() None#

Clean up references to the document and property

equals(other: HasProps) bool#

Structural equality of models.

Parameters:

other (HasProps) – the other instance to compare to

Returns:

True, if properties are structurally equal, otherwise False

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

Bases: AdaptiveTicker

Generate ticks on a linear scale.

Note

This class may be renamed to LinearTicker in the future.

JSON Prototype
{
  "base": 10.0, 
  "desired_num_ticks": 6, 
  "id": "p60490", 
  "js_event_callbacks": {
    "type": "map"
  }, 
  "js_property_callbacks": {
    "type": "map"
  }, 
  "mantissas": [
    1, 
    2, 
    5
  ], 
  "max_interval": null, 
  "min_interval": 0.0, 
  "name": null, 
  "num_minor_ticks": 5, 
  "subscribed_events": {
    "type": "set"
  }, 
  "syncable": true, 
  "tags": []
}
base = 10.0#
Type:

Float

The multiplier to use for scaling mantissas.

desired_num_ticks = 6#
Type:

Int

A desired target number of major tick positions to generate across the plot range.

mantissas = [1, 2, 5]#
Type:

Seq(Float)

The acceptable list numbers to generate multiples of.

max_interval = None#
Type:

Nullable(Float)

The largest allowable interval between two adjacent ticks.

Note

To specify an unbounded interval, set to None.

min_interval = 0.0#
Type:

Float

The smallest allowable interval between two adjacent ticks.

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.

num_minor_ticks = 5#
Type:

Int

The number of minor tick positions to generate between adjacent major tick values.

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(**overrides: Any) Self#

Duplicate a HasProps object.

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

classmethod dataspecs() dict[str, DataSpec]#

Collect the names of all DataSpec properties on this class.

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

Returns:

names of DataSpec properties

Return type:

set[str]

classmethod descriptors() list[PropertyDescriptor[Any]]#

List of property descriptors in the order of definition.

destroy() None#

Clean up references to the document and property

equals(other: HasProps) bool#

Structural equality of models.

Parameters:

other (HasProps) – the other instance to compare to

Returns:

True, if properties are structurally equal, otherwise False

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

Bases: Ticker

Ticker that aligns ticks exactly at bin boundaries of a scanning color mapper.

JSON Prototype
{
  "id": "p60500", 
  "js_event_callbacks": {
    "type": "map"
  }, 
  "js_property_callbacks": {
    "type": "map"
  }, 
  "mapper": {
    "name": "unset", 
    "type": "symbol"
  }, 
  "name": null, 
  "num_major_ticks": 8, 
  "subscribed_events": {
    "type": "set"
  }, 
  "syncable": true, 
  "tags": []
}
mapper = Undefined#
Type:

Instance(ScanningColorMapper)

A scanning color mapper (e.g. EqHistColorMapper) to use.

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.

num_major_ticks = 8#
Type:

Either(Int, Auto)

The number of major tick positions to show or “auto” to use the number of bins provided by the 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(**overrides: Any) Self#

Duplicate a HasProps object.

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

classmethod dataspecs() dict[str, DataSpec]#

Collect the names of all DataSpec properties on this class.

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

Returns:

names of DataSpec properties

Return type:

set[str]

classmethod descriptors() list[PropertyDescriptor[Any]]#

List of property descriptors in the order of definition.

destroy() None#

Clean up references to the document and property

equals(other: HasProps) bool#

Structural equality of models.

Parameters:

other (HasProps) – the other instance to compare to

Returns:

True, if properties are structurally equal, otherwise False

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

Bases: Ticker

Generate ticks for categorical ranges.

JSON Prototype
{
  "id": "p60506", 
  "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(**overrides: Any) Self#

Duplicate a HasProps object.

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

classmethod dataspecs() dict[str, DataSpec]#

Collect the names of all DataSpec properties on this class.

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

Returns:

names of DataSpec properties

Return type:

set[str]

classmethod descriptors() list[PropertyDescriptor[Any]]#

List of property descriptors in the order of definition.

destroy() None#

Clean up references to the document and property

equals(other: HasProps) bool#

Structural equality of models.

Parameters:

other (HasProps) – the other instance to compare to

Returns:

True, if properties are structurally equal, otherwise False

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

Bases: ContinuousTicker

Combine different tickers at different scales.

Uses the min_interval and max_interval interval attributes of the tickers to select the appropriate ticker at different scales.

JSON Prototype
{
  "desired_num_ticks": 6, 
  "id": "p60510", 
  "js_event_callbacks": {
    "type": "map"
  }, 
  "js_property_callbacks": {
    "type": "map"
  }, 
  "name": null, 
  "num_minor_ticks": 5, 
  "subscribed_events": {
    "type": "set"
  }, 
  "syncable": true, 
  "tags": [], 
  "tickers": []
}
desired_num_ticks = 6#
Type:

Int

A desired target number of major tick positions to generate across the plot range.

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.

num_minor_ticks = 5#
Type:

Int

The number of minor tick positions to generate between adjacent major tick values.

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.

tickers = []#
Type:

Seq(Instance(Ticker))

A list of Ticker objects to combine at different scales in order to generate tick values. The supplied tickers should be in order. Specifically, if S comes before T, then it should be the case that:

S.get_max_interval() < T.get_min_interval()
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(**overrides: Any) Self#

Duplicate a HasProps object.

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

classmethod dataspecs() dict[str, DataSpec]#

Collect the names of all DataSpec properties on this class.

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

Returns:

names of DataSpec properties

Return type:

set[str]

classmethod descriptors() list[PropertyDescriptor[Any]]#

List of property descriptors in the order of definition.

destroy() None#

Clean up references to the document and property

equals(other: HasProps) bool#

Structural equality of models.

Parameters:

other (HasProps) – the other instance to compare to

Returns:

True, if properties are structurally equal, otherwise False

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

Bases: Ticker

A base class for non-categorical ticker 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
{
  "desired_num_ticks": 6, 
  "id": "p60517", 
  "js_event_callbacks": {
    "type": "map"
  }, 
  "js_property_callbacks": {
    "type": "map"
  }, 
  "name": null, 
  "num_minor_ticks": 5, 
  "subscribed_events": {
    "type": "set"
  }, 
  "syncable": true, 
  "tags": []
}
desired_num_ticks = 6#
Type:

Int

A desired target number of major tick positions to generate across the plot range.

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.

num_minor_ticks = 5#
Type:

Int

The number of minor tick positions to generate between adjacent major tick values.

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(**overrides: Any) Self#

Duplicate a HasProps object.

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

classmethod dataspecs() dict[str, DataSpec]#

Collect the names of all DataSpec properties on this class.

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

Returns:

names of DataSpec properties

Return type:

set[str]

classmethod descriptors() list[PropertyDescriptor[Any]]#

List of property descriptors in the order of definition.

destroy() None#

Clean up references to the document and property

equals(other: HasProps) bool#

Structural equality of models.

Parameters:

other (HasProps) – the other instance to compare to

Returns:

True, if properties are structurally equal, otherwise False

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

Bases: CompositeTicker

Generate nice ticks across different date and time scales.

JSON Prototype
{
  "desired_num_ticks": 6, 
  "id": "p60523", 
  "js_event_callbacks": {
    "type": "map"
  }, 
  "js_property_callbacks": {
    "type": "map"
  }, 
  "name": null, 
  "num_minor_ticks": 0, 
  "subscribed_events": {
    "type": "set"
  }, 
  "syncable": true, 
  "tags": [], 
  "tickers": [
    {
      "attributes": {
        "mantissas": [
          1, 
          2, 
          5
        ], 
        "max_interval": 500.0, 
        "num_minor_ticks": 0
      }, 
      "id": "p60524", 
      "name": "AdaptiveTicker", 
      "type": "object"
    }, 
    {
      "attributes": {
        "base": 60, 
        "mantissas": [
          1, 
          2, 
          5, 
          10, 
          15, 
          20, 
          30
        ], 
        "max_interval": 1800000.0, 
        "min_interval": 1000.0, 
        "num_minor_ticks": 0
      }, 
      "id": "p60525", 
      "name": "AdaptiveTicker", 
      "type": "object"
    }, 
    {
      "attributes": {
        "base": 24, 
        "mantissas": [
          1, 
          2, 
          4, 
          6, 
          8, 
          12
        ], 
        "max_interval": 43200000.0, 
        "min_interval": 3600000.0, 
        "num_minor_ticks": 0
      }, 
      "id": "p60526", 
      "name": "AdaptiveTicker", 
      "type": "object"
    }, 
    {
      "attributes": {
        "days": [
          1, 
          2, 
          3, 
          4, 
          5, 
          6, 
          7, 
          8, 
          9, 
          10, 
          11, 
          12, 
          13, 
          14, 
          15, 
          16, 
          17, 
          18, 
          19, 
          20, 
          21, 
          22, 
          23, 
          24, 
          25, 
          26, 
          27, 
          28, 
          29, 
          30, 
          31
        ]
      }, 
      "id": "p60527", 
      "name": "DaysTicker", 
      "type": "object"
    }, 
    {
      "attributes": {
        "days": [
          1, 
          4, 
          7, 
          10, 
          13, 
          16, 
          19, 
          22, 
          25, 
          28
        ]
      }, 
      "id": "p60528", 
      "name": "DaysTicker", 
      "type": "object"
    }, 
    {
      "attributes": {
        "days": [
          1, 
          8, 
          15, 
          22
        ]
      }, 
      "id": "p60529", 
      "name": "DaysTicker", 
      "type": "object"
    }, 
    {
      "attributes": {
        "days": [
          1, 
          15
        ]
      }, 
      "id": "p60530", 
      "name": "DaysTicker", 
      "type": "object"
    }, 
    {
      "attributes": {
        "months": [
          0, 
          1, 
          2, 
          3, 
          4, 
          5, 
          6, 
          7, 
          8, 
          9, 
          10, 
          11
        ]
      }, 
      "id": "p60531", 
      "name": "MonthsTicker", 
      "type": "object"
    }, 
    {
      "attributes": {
        "months": [
          0, 
          2, 
          4, 
          6, 
          8, 
          10
        ]
      }, 
      "id": "p60532", 
      "name": "MonthsTicker", 
      "type": "object"
    }, 
    {
      "attributes": {
        "months": [
          0, 
          4, 
          8
        ]
      }, 
      "id": "p60533", 
      "name": "MonthsTicker", 
      "type": "object"
    }, 
    {
      "attributes": {
        "months": [
          0, 
          6
        ]
      }, 
      "id": "p60534", 
      "name": "MonthsTicker", 
      "type": "object"
    }, 
    {
      "id": "p60535", 
      "name": "YearsTicker", 
      "type": "object"
    }
  ]
}
desired_num_ticks = 6#
Type:

Int

A desired target number of major tick positions to generate across the plot range.

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.

num_minor_ticks = 0#
Type:

Int

The number of minor tick positions to generate between adjacent major tick values.

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.

tickers = [AdaptiveTicker(id='p60614', ...), AdaptiveTicker(id='p60615', ...), AdaptiveTicker(id='p60616', ...), DaysTicker(id='p60617', ...), DaysTicker(id='p60618', ...), DaysTicker(id='p60619', ...), DaysTicker(id='p60620', ...), MonthsTicker(id='p60621', ...), MonthsTicker(id='p60622', ...), MonthsTicker(id='p60623', ...), MonthsTicker(id='p60624', ...), YearsTicker(id='p60625', ...)]#
Type:

Seq(Instance(Ticker))

A list of Ticker objects to combine at different scales in order to generate tick values. The supplied tickers should be in order. Specifically, if S comes before T, then it should be the case that:

S.get_max_interval() < T.get_min_interval()
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(**overrides: Any) Self#

Duplicate a HasProps object.

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

classmethod dataspecs() dict[str, DataSpec]#

Collect the names of all DataSpec properties on this class.

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

Returns:

names of DataSpec properties

Return type:

set[str]

classmethod descriptors() list[PropertyDescriptor[Any]]#

List of property descriptors in the order of definition.

destroy() None#

Clean up references to the document and property

equals(other: HasProps) bool#

Structural equality of models.

Parameters:

other (HasProps) – the other instance to compare to

Returns:

True, if properties are structurally equal, otherwise False

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

Bases: BaseSingleIntervalTicker

Generate ticks spaced apart by specific, even multiples of days.

JSON Prototype
{
  "days": [], 
  "desired_num_ticks": 6, 
  "id": "p60626", 
  "js_event_callbacks": {
    "type": "map"
  }, 
  "js_property_callbacks": {
    "type": "map"
  }, 
  "name": null, 
  "num_minor_ticks": 0, 
  "subscribed_events": {
    "type": "set"
  }, 
  "syncable": true, 
  "tags": []
}
days = []#
Type:

Seq(Int)

The intervals of days to use.

desired_num_ticks = 6#
Type:

Int

A desired target number of major tick positions to generate across the plot range.

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.

num_minor_ticks = 0#
Type:

Int

The number of minor tick positions to generate between adjacent major tick values.

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(**overrides: Any) Self#

Duplicate a HasProps object.

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

classmethod dataspecs() dict[str, DataSpec]#

Collect the names of all DataSpec properties on this class.

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

Returns:

names of DataSpec properties

Return type:

set[str]

classmethod descriptors() list[PropertyDescriptor[Any]]#

List of property descriptors in the order of definition.

destroy() None#

Clean up references to the document and property

equals(other: HasProps) bool#

Structural equality of models.

Parameters:

other (HasProps) – the other instance to compare to

Returns:

True, if properties are structurally equal, otherwise False

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

Bases: ContinuousTicker

Generate ticks at fixed, explicitly supplied locations.

Note

The desired_num_ticks property is ignored by this Ticker.

JSON Prototype
{
  "desired_num_ticks": 6, 
  "id": "p60633", 
  "js_event_callbacks": {
    "type": "map"
  }, 
  "js_property_callbacks": {
    "type": "map"
  }, 
  "minor_ticks": [], 
  "name": null, 
  "num_minor_ticks": 5, 
  "subscribed_events": {
    "type": "set"
  }, 
  "syncable": true, 
  "tags": [], 
  "ticks": []
}
desired_num_ticks = 6#
Type:

Int

A desired target number of major tick positions to generate across the plot range.

minor_ticks = []#
Type:

Seq(Float)

List of minor tick locations.

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.

num_minor_ticks = 5#
Type:

Int

The number of minor tick positions to generate between adjacent major tick values.

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.

ticks = []#
Type:

Seq(Float)

List of major tick locations.

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(**overrides: Any) Self#

Duplicate a HasProps object.

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

classmethod dataspecs() dict[str, DataSpec]#

Collect the names of all DataSpec properties on this class.

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

Returns:

names of DataSpec properties

Return type:

set[str]

classmethod descriptors() list[PropertyDescriptor[Any]]#

List of property descriptors in the order of definition.

destroy() None#

Clean up references to the document and property

equals(other: HasProps) bool#

Structural equality of models.

Parameters:

other (HasProps) – the other instance to compare to

Returns:

True, if properties are structurally equal, otherwise False

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

Bases: AdaptiveTicker

Generate ticks on a log scale.

JSON Prototype
{
  "base": 10.0, 
  "desired_num_ticks": 6, 
  "id": "p60641", 
  "js_event_callbacks": {
    "type": "map"
  }, 
  "js_property_callbacks": {
    "type": "map"
  }, 
  "mantissas": [
    1, 
    5
  ], 
  "max_interval": null, 
  "min_interval": 0.0, 
  "name": null, 
  "num_minor_ticks": 5, 
  "subscribed_events": {
    "type": "set"
  }, 
  "syncable": true, 
  "tags": []
}
base = 10.0#
Type:

Float

The multiplier to use for scaling mantissas.

desired_num_ticks = 6#
Type:

Int

A desired target number of major tick positions to generate across the plot range.

mantissas = [1, 5]#
Type:

Seq(Float)

The acceptable list numbers to generate multiples of.

max_interval = None#
Type:

Nullable(Float)

The largest allowable interval between two adjacent ticks.

Note

To specify an unbounded interval, set to None.

min_interval = 0.0#
Type:

Float

The smallest allowable interval between two adjacent ticks.

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.

num_minor_ticks = 5#
Type:

Int

The number of minor tick positions to generate between adjacent major tick values.

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(**overrides: Any) Self#

Duplicate a HasProps object.

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

classmethod dataspecs() dict[str, DataSpec]#

Collect the names of all DataSpec properties on this class.

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

Returns:

names of DataSpec properties

Return type:

set[str]

classmethod descriptors() list[PropertyDescriptor[Any]]#

List of property descriptors in the order of definition.

destroy() None#

Clean up references to the document and property

equals(other: HasProps) bool#

Structural equality of models.

Parameters:

other (HasProps) – the other instance to compare to

Returns:

True, if properties are structurally equal, otherwise False

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

Bases: BasicTicker

Generate nice lat/lon ticks form underlying WebMercator coordinates.

JSON Prototype
{
  "base": 10.0, 
  "desired_num_ticks": 6, 
  "dimension": null, 
  "id": "p60651", 
  "js_event_callbacks": {
    "type": "map"
  }, 
  "js_property_callbacks": {
    "type": "map"
  }, 
  "mantissas": [
    1, 
    2, 
    5
  ], 
  "max_interval": null, 
  "min_interval": 0.0, 
  "name": null, 
  "num_minor_ticks": 5, 
  "subscribed_events": {
    "type": "set"
  }, 
  "syncable": true, 
  "tags": []
}
base = 10.0#
Type:

Float

The multiplier to use for scaling mantissas.

desired_num_ticks = 6#
Type:

Int

A desired target number of major tick positions to generate across the plot range.

dimension = None#
Type:

Nullable(Enum(LatLon))

Specify whether to generate ticks for Latitude or Longitude.

Projected coordinates are not separable, computing Latitude and Longitude tick locations from Web Mercator requires considering coordinates from both dimensions together. Use this property to specify which result should be returned.

Typically, if the ticker is for an x-axis, then dimension should be "lon" and if the ticker is for a y-axis, then the dimension should be “lat”`.

In order to prevent hard to debug errors, there is no default value for dimension. Using an un-configured MercatorTicker will result in a validation error and a JavaScript console error.

mantissas = [1, 2, 5]#
Type:

Seq(Float)

The acceptable list numbers to generate multiples of.

max_interval = None#
Type:

Nullable(Float)

The largest allowable interval between two adjacent ticks.

Note

To specify an unbounded interval, set to None.

min_interval = 0.0#
Type:

Float

The smallest allowable interval between two adjacent ticks.

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.

num_minor_ticks = 5#
Type:

Int

The number of minor tick positions to generate between adjacent major tick values.

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(**overrides: Any) Self#

Duplicate a HasProps object.

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

classmethod dataspecs() dict[str, DataSpec]#

Collect the names of all DataSpec properties on this class.

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

Returns:

names of DataSpec properties

Return type:

set[str]

classmethod descriptors() list[PropertyDescriptor[Any]]#

List of property descriptors in the order of definition.

destroy() None#

Clean up references to the document and property

equals(other: HasProps) bool#

Structural equality of models.

Parameters:

other (HasProps) – the other instance to compare to

Returns:

True, if properties are structurally equal, otherwise False

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

Bases: BaseSingleIntervalTicker

Generate ticks spaced apart by specific, even multiples of months.

JSON Prototype
{
  "desired_num_ticks": 6, 
  "id": "p60662", 
  "js_event_callbacks": {
    "type": "map"
  }, 
  "js_property_callbacks": {
    "type": "map"
  }, 
  "months": [], 
  "name": null, 
  "num_minor_ticks": 5, 
  "subscribed_events": {
    "type": "set"
  }, 
  "syncable": true, 
  "tags": []
}
desired_num_ticks = 6#
Type:

Int

A desired target number of major tick positions to generate across the plot range.

months = []#
Type:

Seq(Int)

The intervals of months to use.

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.

num_minor_ticks = 5#
Type:

Int

The number of minor tick positions to generate between adjacent major tick values.

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(**overrides: Any) Self#

Duplicate a HasProps object.

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

classmethod dataspecs() dict[str, DataSpec]#

Collect the names of all DataSpec properties on this class.

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

Returns:

names of DataSpec properties

Return type:

set[str]

classmethod descriptors() list[PropertyDescriptor[Any]]#

List of property descriptors in the order of definition.

destroy() None#

Clean up references to the document and property

equals(other: HasProps) bool#

Structural equality of models.

Parameters:

other (HasProps) – the other instance to compare to

Returns:

True, if properties are structurally equal, otherwise False

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