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
andmantissas=[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": "p56106", "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": [] }
- desired_num_ticks = 6#
- Type:
A desired target number of major tick positions to generate across the plot range.
- max_interval = None#
-
The largest allowable interval between two adjacent ticks.
Note
To specify an unbounded interval, set to
None
.
- name = None#
-
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:
The number of minor tick positions to generate between adjacent major tick values.
- syncable = True#
- Type:
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 anyon_change()
callbacks on this object from triggering. However, any JS-side callbacks will still work.
- tags = []#
- Type:
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() HasProps #
Duplicate a HasProps object.
This creates a shallow clone of the original model, i.e. any mutable containers or child models will not be duplicated.
- classmethod dataspecs() dict[str, DataSpec] #
Collect the names of all
DataSpec
properties on this class.This method always traverses the class hierarchy and includes properties defined on any parent classes.
- classmethod descriptors() list[bokeh.core.property.descriptors.PropertyDescriptor[Any]] #
List of property descriptors in the order of definition.
- equals(other: HasProps) bool #
Structural equality of models.
- Parameters:
other (HasProps) – the other instance to compare to
- Returns:
True, if properties are structurally equal, otherwise False
- js_link(attr: str, other: Model, other_attr: str, attr_selector: int | str | None = None) None #
Link two Bokeh model properties using JavaScript.
This is a convenience method that simplifies adding a
CustomJS
callback to update one Bokeh model property whenever another changes value.- Parameters:
Added in version 1.1
- Raises:
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:
- Returns:
descriptor for property named
name
- Return type:
- 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[inspect.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.
- 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.
- 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:
- references() set[bokeh.model.model.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 #
- 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)
- 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": "p56116", "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": [] }
- desired_num_ticks = 6#
- Type:
A desired target number of major tick positions to generate across the plot range.
- max_interval = None#
-
The largest allowable interval between two adjacent ticks.
Note
To specify an unbounded interval, set to
None
.
- name = None#
-
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:
The number of minor tick positions to generate between adjacent major tick values.
- syncable = True#
- Type:
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 anyon_change()
callbacks on this object from triggering. However, any JS-side callbacks will still work.
- tags = []#
- Type:
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() HasProps #
Duplicate a HasProps object.
This creates a shallow clone of the original model, i.e. any mutable containers or child models will not be duplicated.
- classmethod dataspecs() dict[str, DataSpec] #
Collect the names of all
DataSpec
properties on this class.This method always traverses the class hierarchy and includes properties defined on any parent classes.
- classmethod descriptors() list[bokeh.core.property.descriptors.PropertyDescriptor[Any]] #
List of property descriptors in the order of definition.
- equals(other: HasProps) bool #
Structural equality of models.
- Parameters:
other (HasProps) – the other instance to compare to
- Returns:
True, if properties are structurally equal, otherwise False
- js_link(attr: str, other: Model, other_attr: str, attr_selector: int | str | None = None) None #
Link two Bokeh model properties using JavaScript.
This is a convenience method that simplifies adding a
CustomJS
callback to update one Bokeh model property whenever another changes value.- Parameters:
Added in version 1.1
- Raises:
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:
- Returns:
descriptor for property named
name
- Return type:
- 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[inspect.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.
- 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.
- 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:
- references() set[bokeh.model.model.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 #
- 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)
- 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": "p56126", "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#
-
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#
-
The number of major tick positions to show or “auto” to use the number of bins provided by the mapper.
- syncable = True#
- Type:
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 anyon_change()
callbacks on this object from triggering. However, any JS-side callbacks will still work.
- tags = []#
- Type:
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() HasProps #
Duplicate a HasProps object.
This creates a shallow clone of the original model, i.e. any mutable containers or child models will not be duplicated.
- classmethod dataspecs() dict[str, DataSpec] #
Collect the names of all
DataSpec
properties on this class.This method always traverses the class hierarchy and includes properties defined on any parent classes.
- classmethod descriptors() list[bokeh.core.property.descriptors.PropertyDescriptor[Any]] #
List of property descriptors in the order of definition.
- equals(other: HasProps) bool #
Structural equality of models.
- Parameters:
other (HasProps) – the other instance to compare to
- Returns:
True, if properties are structurally equal, otherwise False
- js_link(attr: str, other: Model, other_attr: str, attr_selector: int | str | None = None) None #
Link two Bokeh model properties using JavaScript.
This is a convenience method that simplifies adding a
CustomJS
callback to update one Bokeh model property whenever another changes value.- Parameters:
Added in version 1.1
- Raises:
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:
- Returns:
descriptor for property named
name
- Return type:
- 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[inspect.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.
- 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.
- 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:
- references() set[bokeh.model.model.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 #
- 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)
- class CategoricalTicker(*args: Any, id: ID | None = None, **kwargs: Any)[source]#
Bases:
Ticker
Generate ticks for categorical ranges.
JSON Prototype
{ "id": "p56132", "js_event_callbacks": { "type": "map" }, "js_property_callbacks": { "type": "map" }, "name": null, "subscribed_events": { "type": "set" }, "syncable": true, "tags": [] }
- name = None#
-
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:
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 anyon_change()
callbacks on this object from triggering. However, any JS-side callbacks will still work.
- tags = []#
- Type:
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() HasProps #
Duplicate a HasProps object.
This creates a shallow clone of the original model, i.e. any mutable containers or child models will not be duplicated.
- classmethod dataspecs() dict[str, DataSpec] #
Collect the names of all
DataSpec
properties on this class.This method always traverses the class hierarchy and includes properties defined on any parent classes.
- classmethod descriptors() list[bokeh.core.property.descriptors.PropertyDescriptor[Any]] #
List of property descriptors in the order of definition.
- equals(other: HasProps) bool #
Structural equality of models.
- Parameters:
other (HasProps) – the other instance to compare to
- Returns:
True, if properties are structurally equal, otherwise False
- js_link(attr: str, other: Model, other_attr: str, attr_selector: int | str | None = None) None #
Link two Bokeh model properties using JavaScript.
This is a convenience method that simplifies adding a
CustomJS
callback to update one Bokeh model property whenever another changes value.- Parameters:
Added in version 1.1
- Raises:
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:
- Returns:
descriptor for property named
name
- Return type:
- 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[inspect.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.
- 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.
- 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:
- references() set[bokeh.model.model.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 #
- 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)
- class CompositeTicker(*args: Any, id: ID | None = None, **kwargs: Any)[source]#
Bases:
ContinuousTicker
Combine different tickers at different scales.
Uses the
min_interval
andmax_interval
interval attributes of the tickers to select the appropriate ticker at different scales.JSON Prototype
{ "desired_num_ticks": 6, "id": "p56136", "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:
A desired target number of major tick positions to generate across the plot range.
- name = None#
-
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:
The number of minor tick positions to generate between adjacent major tick values.
- syncable = True#
- Type:
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 anyon_change()
callbacks on this object from triggering. However, any JS-side callbacks will still work.
- tags = []#
- Type:
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 = []#
-
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() HasProps #
Duplicate a HasProps object.
This creates a shallow clone of the original model, i.e. any mutable containers or child models will not be duplicated.
- classmethod dataspecs() dict[str, DataSpec] #
Collect the names of all
DataSpec
properties on this class.This method always traverses the class hierarchy and includes properties defined on any parent classes.
- classmethod descriptors() list[bokeh.core.property.descriptors.PropertyDescriptor[Any]] #
List of property descriptors in the order of definition.
- equals(other: HasProps) bool #
Structural equality of models.
- Parameters:
other (HasProps) – the other instance to compare to
- Returns:
True, if properties are structurally equal, otherwise False
- js_link(attr: str, other: Model, other_attr: str, attr_selector: int | str | None = None) None #
Link two Bokeh model properties using JavaScript.
This is a convenience method that simplifies adding a
CustomJS
callback to update one Bokeh model property whenever another changes value.- Parameters:
Added in version 1.1
- Raises:
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:
- Returns:
descriptor for property named
name
- Return type:
- 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[inspect.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.
- 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.
- 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:
- references() set[bokeh.model.model.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 #
- 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)
- 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": "p56143", "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:
A desired target number of major tick positions to generate across the plot range.
- name = None#
-
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:
The number of minor tick positions to generate between adjacent major tick values.
- syncable = True#
- Type:
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 anyon_change()
callbacks on this object from triggering. However, any JS-side callbacks will still work.
- tags = []#
- Type:
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() HasProps #
Duplicate a HasProps object.
This creates a shallow clone of the original model, i.e. any mutable containers or child models will not be duplicated.
- classmethod dataspecs() dict[str, DataSpec] #
Collect the names of all
DataSpec
properties on this class.This method always traverses the class hierarchy and includes properties defined on any parent classes.
- classmethod descriptors() list[bokeh.core.property.descriptors.PropertyDescriptor[Any]] #
List of property descriptors in the order of definition.
- equals(other: HasProps) bool #
Structural equality of models.
- Parameters:
other (HasProps) – the other instance to compare to
- Returns:
True, if properties are structurally equal, otherwise False
- js_link(attr: str, other: Model, other_attr: str, attr_selector: int | str | None = None) None #
Link two Bokeh model properties using JavaScript.
This is a convenience method that simplifies adding a
CustomJS
callback to update one Bokeh model property whenever another changes value.- Parameters:
Added in version 1.1
- Raises:
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:
- Returns:
descriptor for property named
name
- Return type:
- 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[inspect.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.
- 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.
- 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:
- references() set[bokeh.model.model.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 #
- 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)
- 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": "p56149", "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": "p56150", "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": "p56151", "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": "p56152", "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": "p56153", "name": "DaysTicker", "type": "object" }, { "attributes": { "days": [ 1, 4, 7, 10, 13, 16, 19, 22, 25, 28 ] }, "id": "p56154", "name": "DaysTicker", "type": "object" }, { "attributes": { "days": [ 1, 8, 15, 22 ] }, "id": "p56155", "name": "DaysTicker", "type": "object" }, { "attributes": { "days": [ 1, 15 ] }, "id": "p56156", "name": "DaysTicker", "type": "object" }, { "attributes": { "months": [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 ] }, "id": "p56157", "name": "MonthsTicker", "type": "object" }, { "attributes": { "months": [ 0, 2, 4, 6, 8, 10 ] }, "id": "p56158", "name": "MonthsTicker", "type": "object" }, { "attributes": { "months": [ 0, 4, 8 ] }, "id": "p56159", "name": "MonthsTicker", "type": "object" }, { "attributes": { "months": [ 0, 6 ] }, "id": "p56160", "name": "MonthsTicker", "type": "object" }, { "id": "p56161", "name": "YearsTicker", "type": "object" } ] }
- desired_num_ticks = 6#
- Type:
A desired target number of major tick positions to generate across the plot range.
- name = None#
-
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:
The number of minor tick positions to generate between adjacent major tick values.
- syncable = True#
- Type:
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 anyon_change()
callbacks on this object from triggering. However, any JS-side callbacks will still work.
- tags = []#
- Type:
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='p56240', ...), AdaptiveTicker(id='p56241', ...), AdaptiveTicker(id='p56242', ...), DaysTicker(id='p56243', ...), DaysTicker(id='p56244', ...), DaysTicker(id='p56245', ...), DaysTicker(id='p56246', ...), MonthsTicker(id='p56247', ...), MonthsTicker(id='p56248', ...), MonthsTicker(id='p56249', ...), MonthsTicker(id='p56250', ...), YearsTicker(id='p56251', ...)]#
-
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() HasProps #
Duplicate a HasProps object.
This creates a shallow clone of the original model, i.e. any mutable containers or child models will not be duplicated.
- classmethod dataspecs() dict[str, DataSpec] #
Collect the names of all
DataSpec
properties on this class.This method always traverses the class hierarchy and includes properties defined on any parent classes.
- classmethod descriptors() list[bokeh.core.property.descriptors.PropertyDescriptor[Any]] #
List of property descriptors in the order of definition.
- equals(other: HasProps) bool #
Structural equality of models.
- Parameters:
other (HasProps) – the other instance to compare to
- Returns:
True, if properties are structurally equal, otherwise False
- js_link(attr: str, other: Model, other_attr: str, attr_selector: int | str | None = None) None #
Link two Bokeh model properties using JavaScript.
This is a convenience method that simplifies adding a
CustomJS
callback to update one Bokeh model property whenever another changes value.- Parameters:
Added in version 1.1
- Raises:
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:
- Returns:
descriptor for property named
name
- Return type:
- 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[inspect.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.
- 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.
- 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:
- references() set[bokeh.model.model.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 #
- 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)
- 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": "p56252", "js_event_callbacks": { "type": "map" }, "js_property_callbacks": { "type": "map" }, "name": null, "num_minor_ticks": 0, "subscribed_events": { "type": "set" }, "syncable": true, "tags": [] }
- desired_num_ticks = 6#
- Type:
A desired target number of major tick positions to generate across the plot range.
- name = None#
-
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:
The number of minor tick positions to generate between adjacent major tick values.
- syncable = True#
- Type:
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 anyon_change()
callbacks on this object from triggering. However, any JS-side callbacks will still work.
- tags = []#
- Type:
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() HasProps #
Duplicate a HasProps object.
This creates a shallow clone of the original model, i.e. any mutable containers or child models will not be duplicated.
- classmethod dataspecs() dict[str, DataSpec] #
Collect the names of all
DataSpec
properties on this class.This method always traverses the class hierarchy and includes properties defined on any parent classes.
- classmethod descriptors() list[bokeh.core.property.descriptors.PropertyDescriptor[Any]] #
List of property descriptors in the order of definition.
- equals(other: HasProps) bool #
Structural equality of models.
- Parameters:
other (HasProps) – the other instance to compare to
- Returns:
True, if properties are structurally equal, otherwise False
- js_link(attr: str, other: Model, other_attr: str, attr_selector: int | str | None = None) None #
Link two Bokeh model properties using JavaScript.
This is a convenience method that simplifies adding a
CustomJS
callback to update one Bokeh model property whenever another changes value.- Parameters:
Added in version 1.1
- Raises:
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:
- Returns:
descriptor for property named
name
- Return type:
- 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[inspect.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.
- 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.
- 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:
- references() set[bokeh.model.model.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 #
- 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)
- 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": "p56259", "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:
A desired target number of major tick positions to generate across the plot range.
- name = None#
-
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:
The number of minor tick positions to generate between adjacent major tick values.
- syncable = True#
- Type:
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 anyon_change()
callbacks on this object from triggering. However, any JS-side callbacks will still work.
- tags = []#
- Type:
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() HasProps #
Duplicate a HasProps object.
This creates a shallow clone of the original model, i.e. any mutable containers or child models will not be duplicated.
- classmethod dataspecs() dict[str, DataSpec] #
Collect the names of all
DataSpec
properties on this class.This method always traverses the class hierarchy and includes properties defined on any parent classes.
- classmethod descriptors() list[bokeh.core.property.descriptors.PropertyDescriptor[Any]] #
List of property descriptors in the order of definition.
- equals(other: HasProps) bool #
Structural equality of models.
- Parameters:
other (HasProps) – the other instance to compare to
- Returns:
True, if properties are structurally equal, otherwise False
- js_link(attr: str, other: Model, other_attr: str, attr_selector: int | str | None = None) None #
Link two Bokeh model properties using JavaScript.
This is a convenience method that simplifies adding a
CustomJS
callback to update one Bokeh model property whenever another changes value.- Parameters:
Added in version 1.1
- Raises:
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:
- Returns:
descriptor for property named
name
- Return type:
- 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[inspect.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.
- 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.
- 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:
- references() set[bokeh.model.model.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 #
- 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)
- 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": "p56267", "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": [] }
- desired_num_ticks = 6#
- Type:
A desired target number of major tick positions to generate across the plot range.
- max_interval = None#
-
The largest allowable interval between two adjacent ticks.
Note
To specify an unbounded interval, set to
None
.
- name = None#
-
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:
The number of minor tick positions to generate between adjacent major tick values.
- syncable = True#
- Type:
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 anyon_change()
callbacks on this object from triggering. However, any JS-side callbacks will still work.
- tags = []#
- Type:
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() HasProps #
Duplicate a HasProps object.
This creates a shallow clone of the original model, i.e. any mutable containers or child models will not be duplicated.
- classmethod dataspecs() dict[str, DataSpec] #
Collect the names of all
DataSpec
properties on this class.This method always traverses the class hierarchy and includes properties defined on any parent classes.
- classmethod descriptors() list[bokeh.core.property.descriptors.PropertyDescriptor[Any]] #
List of property descriptors in the order of definition.
- equals(other: HasProps) bool #
Structural equality of models.
- Parameters:
other (HasProps) – the other instance to compare to
- Returns:
True, if properties are structurally equal, otherwise False
- js_link(attr: str, other: Model, other_attr: str, attr_selector: int | str | None = None) None #
Link two Bokeh model properties using JavaScript.
This is a convenience method that simplifies adding a
CustomJS
callback to update one Bokeh model property whenever another changes value.- Parameters:
Added in version 1.1
- Raises:
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:
- Returns:
descriptor for property named
name
- Return type:
- 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[inspect.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.
- 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.
- 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:
- references() set[bokeh.model.model.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 #
- 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)
- 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": "p56277", "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": [] }
- desired_num_ticks = 6#
- Type:
A desired target number of major tick positions to generate across the plot range.
- dimension = None#
-
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.
- max_interval = None#
-
The largest allowable interval between two adjacent ticks.
Note
To specify an unbounded interval, set to
None
.
- name = None#
-
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:
The number of minor tick positions to generate between adjacent major tick values.
- syncable = True#
- Type:
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 anyon_change()
callbacks on this object from triggering. However, any JS-side callbacks will still work.
- tags = []#
- Type:
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() HasProps #
Duplicate a HasProps object.
This creates a shallow clone of the original model, i.e. any mutable containers or child models will not be duplicated.
- classmethod dataspecs() dict[str, DataSpec] #
Collect the names of all
DataSpec
properties on this class.This method always traverses the class hierarchy and includes properties defined on any parent classes.
- classmethod descriptors() list[bokeh.core.property.descriptors.PropertyDescriptor[Any]] #
List of property descriptors in the order of definition.
- equals(other: HasProps) bool #
Structural equality of models.
- Parameters:
other (HasProps) – the other instance to compare to
- Returns:
True, if properties are structurally equal, otherwise False
- js_link(attr: str, other: Model, other_attr: str, attr_selector: int | str | None = None) None #
Link two Bokeh model properties using JavaScript.
This is a convenience method that simplifies adding a
CustomJS
callback to update one Bokeh model property whenever another changes value.- Parameters:
Added in version 1.1
- Raises:
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:
- Returns:
descriptor for property named
name
- Return type:
- 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[inspect.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.
- 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.
- 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:
- references() set[bokeh.model.model.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 #
- 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)
- 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": "p56288", "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:
A desired target number of major tick positions to generate across the plot range.
- name = None#
-
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:
The number of minor tick positions to generate between adjacent major tick values.
- syncable = True#
- Type:
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 anyon_change()
callbacks on this object from triggering. However, any JS-side callbacks will still work.
- tags = []#
- Type:
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() HasProps #
Duplicate a HasProps object.
This creates a shallow clone of the original model, i.e. any mutable containers or child models will not be duplicated.
- classmethod dataspecs() dict[str, DataSpec] #
Collect the names of all
DataSpec
properties on this class.This method always traverses the class hierarchy and includes properties defined on any parent classes.
- classmethod descriptors() list[bokeh.core.property.descriptors.PropertyDescriptor[Any]] #
List of property descriptors in the order of definition.
- equals(other: HasProps) bool #
Structural equality of models.
- Parameters:
other (HasProps) – the other instance to compare to
- Returns:
True, if properties are structurally equal, otherwise False
- js_link(attr: str, other: Model, other_attr: str, attr_selector: int | str | None = None) None #
Link two Bokeh model properties using JavaScript.
This is a convenience method that simplifies adding a
CustomJS
callback to update one Bokeh model property whenever another changes value.- Parameters:
Added in version 1.1
- Raises:
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:
- Returns:
descriptor for property named
name
- Return type:
- 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[inspect.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.
- 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.
- 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:
- references() set[bokeh.model.model.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 #
- 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)
- class SingleIntervalTicker(*args: Any, id: ID | None = None, **kwargs: Any)[source]#
Bases:
BaseSingleIntervalTicker
Generate evenly spaced ticks at a fixed interval regardless of scale.
JSON Prototype
{ "desired_num_ticks": 6, "id": "p56295", "interval": { "name": "unset", "type": "symbol" }, "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:
A desired target number of major tick positions to generate across the plot range.
- name = None#
-
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:
The number of minor tick positions to generate between adjacent major tick values.
- syncable = True#
- Type:
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 anyon_change()
callbacks on this object from triggering. However, any JS-side callbacks will still work.
- tags = []#
- Type:
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() HasProps #
Duplicate a HasProps object.
This creates a shallow clone of the original model, i.e. any mutable containers or child models will not be duplicated.
- classmethod dataspecs() dict[str, DataSpec] #
Collect the names of all
DataSpec
properties on this class.This method always traverses the class hierarchy and includes properties defined on any parent classes.
- classmethod descriptors() list[bokeh.core.property.descriptors.PropertyDescriptor[Any]] #
List of property descriptors in the order of definition.
- equals(other: HasProps) bool #
Structural equality of models.
- Parameters:
other (HasProps) – the other instance to compare to
- Returns:
True, if properties are structurally equal, otherwise False
- js_link(attr: str, other: Model, other_attr: str, attr_selector: int | str | None = None) None #
Link two Bokeh model properties using JavaScript.
This is a convenience method that simplifies adding a
CustomJS
callback to update one Bokeh model property whenever another changes value.- Parameters:
Added in version 1.1
- Raises:
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:
- Returns:
descriptor for property named
name
- Return type:
- 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[inspect.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.
- 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.
- 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:
- references() set[bokeh.model.model.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 #
- 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)
- class Ticker(*args: Any, id: ID | None = None, **kwargs: Any)[source]#
Bases:
Model
A base class for all 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
{ "id": "p56302", "js_event_callbacks": { "type": "map" }, "js_property_callbacks": { "type": "map" }, "name": null, "subscribed_events": { "type": "set" }, "syncable": true, "tags": [] }
- name = None#
-
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:
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 anyon_change()
callbacks on this object from triggering. However, any JS-side callbacks will still work.
- tags = []#
- Type:
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() HasProps #
Duplicate a HasProps object.
This creates a shallow clone of the original model, i.e. any mutable containers or child models will not be duplicated.
- classmethod dataspecs() dict[str, DataSpec] #
Collect the names of all
DataSpec
properties on this class.This method always traverses the class hierarchy and includes properties defined on any parent classes.
- classmethod descriptors() list[bokeh.core.property.descriptors.PropertyDescriptor[Any]] #
List of property descriptors in the order of definition.
- equals(other: HasProps) bool #
Structural equality of models.
- Parameters:
other (HasProps) – the other instance to compare to
- Returns:
True, if properties are structurally equal, otherwise False
- js_link(attr: str, other: Model, other_attr: str, attr_selector: int | str | None = None) None #
Link two Bokeh model properties using JavaScript.
This is a convenience method that simplifies adding a
CustomJS
callback to update one Bokeh model property whenever another changes value.- Parameters:
Added in version 1.1
- Raises:
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:
- Returns:
descriptor for property named
name
- Return type:
- 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[inspect.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.
- 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.
- 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:
- references() set[bokeh.model.model.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 #
- 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)
- class YearsTicker(*args: Any, id: ID | None = None, **kwargs: Any)[source]#
Bases:
BaseSingleIntervalTicker
Generate ticks spaced apart even numbers of years.
JSON Prototype
{ "desired_num_ticks": 6, "id": "p56306", "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:
A desired target number of major tick positions to generate across the plot range.
- name = None#
-
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:
The number of minor tick positions to generate between adjacent major tick values.
- syncable = True#
- Type:
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 anyon_change()
callbacks on this object from triggering. However, any JS-side callbacks will still work.
- tags = []#
- Type:
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() HasProps #
Duplicate a HasProps object.
This creates a shallow clone of the original model, i.e. any mutable containers or child models will not be duplicated.
- classmethod dataspecs() dict[str, DataSpec] #
Collect the names of all
DataSpec
properties on this class.This method always traverses the class hierarchy and includes properties defined on any parent classes.
- classmethod descriptors() list[bokeh.core.property.descriptors.PropertyDescriptor[Any]] #
List of property descriptors in the order of definition.
- equals(other: HasProps) bool #
Structural equality of models.
- Parameters:
other (HasProps) – the other instance to compare to
- Returns:
True, if properties are structurally equal, otherwise False
- js_link(attr: str, other: Model, other_attr: str, attr_selector: int | str | None = None) None #
Link two Bokeh model properties using JavaScript.
This is a convenience method that simplifies adding a
CustomJS
callback to update one Bokeh model property whenever another changes value.- Parameters:
Added in version 1.1
- Raises:
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:
- Returns:
descriptor for property named
name
- Return type:
- 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[inspect.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.
- 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.
- 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:
- references() set[bokeh.model.model.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 #
- 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)