ranges#
Models for describing different kinds of ranges of values in different kinds of spaces (e.g., continuous or categorical) and with options for “auto sizing”.
- class DataRange(*args: Any, id: ID | None = None, **kwargs: Any)[source]#
Bases:
NumericalRange
A base class for all data range 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
{ "end": { "type": "number", "value": "nan" }, "id": "p61753", "js_event_callbacks": { "type": "map" }, "js_property_callbacks": { "type": "map" }, "name": null, "renderers": [], "start": { "type": "number", "value": "nan" }, "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.
- renderers = []#
-
An explicit list of renderers to autorange against. If unset, defaults to all renderers on a plot.
- 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(**overrides: Any) Self #
Duplicate a
HasProps
object.This creates a shallow clone of the original model, i.e. any mutable containers or child models will not be duplicated. Allows to override particular properties while cloning.
- classmethod dataspecs() dict[str, DataSpec] #
Collect the names of all
DataSpec
properties on this class.This method always traverses the class hierarchy and includes properties defined on any parent classes.
- classmethod descriptors() list[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: Callable[[Event], None] | Callable[[], None]) None #
Run callbacks when the specified event occurs on this Model
Not all Events are supported for all Models. See specific Events in bokeh.events for more information on which Models are able to trigger them.
- classmethod parameters() list[Parameter] #
Generate Python
Parameter
values suitable for functions that are derived from the glyph.- Returns:
list(Parameter)
- classmethod properties(*, _with_props: bool = False) set[str] | dict[str, Property[Any]] #
Collect the names of properties on this class.
Warning
In a future version of Bokeh, this method will return a dictionary mapping property names to property objects. To future-proof this current usage of this method, wrap the return value in
list
.- Returns:
property names
- classmethod properties_with_refs() dict[str, Property[Any]] #
Collect the names of all properties on this class that also have references.
This method always traverses the class hierarchy and includes properties defined on any parent classes.
- 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:
- 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 DataRange1d(*args: Any, id: ID | None = None, **kwargs: Any)[source]#
Bases:
DataRange
An auto-fitting range in a continuous scalar dimension.
By default the
start
andend
of the range automatically assume min and max values of the data for associated renderers.JSON Prototype
{ "bounds": null, "default_span": 2.0, "end": { "type": "number", "value": "nan" }, "flipped": false, "follow": null, "follow_interval": null, "id": "p61760", "js_event_callbacks": { "type": "map" }, "js_property_callbacks": { "type": "map" }, "max_interval": null, "min_interval": null, "name": null, "only_visible": false, "range_padding": 0.1, "range_padding_units": "percent", "renderers": [], "start": { "type": "number", "value": "nan" }, "subscribed_events": { "type": "set" }, "syncable": true, "tags": [] }
- bounds = None#
- Type:
The bounds that the range is allowed to go to. Typically used to prevent the user from panning/zooming/etc away from the data.
By default, the bounds will be None, allowing your plot to pan/zoom as far as you want. If bounds are ‘auto’ they will be computed to be the same as the start and end of the
DataRange1d
.Bounds are provided as a tuple of
(min, max)
so regardless of whether your range is increasing or decreasing, the first item should be the minimum value of the range and the second item should be the maximum. Settingmin > max
will result in aValueError
.If you only want to constrain one end of the plot, you can set
min
ormax
toNone
e.g.DataRange1d(bounds=(None, 12))
- default_span = 2.0#
-
A default width for the interval, in case
start
is equal toend
(if used with a log axis, default_span is in powers of 10).
- flipped = False#
- Type:
Whether the range should be “flipped” from its normal direction when auto-ranging.
- follow = None#
-
Configure the data to follow one or the other data extreme, with a maximum range size of
follow_interval
.If set to
"start"
then the range will adjust so thatstart
always corresponds to the minimum data value (or maximum, ifflipped
isTrue
).If set to
"end"
then the range will adjust so thatend
always corresponds to the maximum data value (or minimum, ifflipped
isTrue
).If set to
None
(default), then auto-ranging does not follow, and the range will encompass both the minimum and maximum data values.follow
cannot be used with bounds, and if set, bounds will be set toNone
.
- follow_interval = None#
-
If
follow
is set to"start"
or"end"
then the range will always be constrained to that:abs(r.start - r.end) <= follow_interval
is maintained.
- max_interval = None#
-
The level that the range is allowed to zoom out, expressed as the maximum visible interval. Note that
bounds
can impose an implicit constraint on the maximum interval as well.
- min_interval = None#
-
The level that the range is allowed to zoom in, expressed as the minimum visible interval. If set to
None
(default), the minimum interval is not bound.
- 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.
- only_visible = False#
- Type:
If True, renderers that that are not visible will be excluded from automatic bounds computations.
- range_padding = 0.1#
-
How much padding to add around the computed data bounds.
When
range_padding_units
is set to"percent"
, the span of the range span is expanded to make the rangerange_padding
percent larger.When
range_padding_units
is set to"absolute"
, the start and end of the range span are extended by the amountrange_padding
.
- range_padding_units = 'percent'#
- Type:
Whether the
range_padding
should be interpreted as a percentage, or as an absolute quantity. (default:"percent"
)
- renderers = []#
-
An explicit list of renderers to autorange against. If unset, defaults to all renderers on a plot.
- 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(**overrides: Any) Self #
Duplicate a
HasProps
object.This creates a shallow clone of the original model, i.e. any mutable containers or child models will not be duplicated. Allows to override particular properties while cloning.
- classmethod dataspecs() dict[str, DataSpec] #
Collect the names of all
DataSpec
properties on this class.This method always traverses the class hierarchy and includes properties defined on any parent classes.
- classmethod descriptors() list[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: Callable[[Event], None] | Callable[[], None]) None #
Run callbacks when the specified event occurs on this Model
Not all Events are supported for all Models. See specific Events in bokeh.events for more information on which Models are able to trigger them.
- classmethod parameters() list[Parameter] #
Generate Python
Parameter
values suitable for functions that are derived from the glyph.- Returns:
list(Parameter)
- classmethod properties(*, _with_props: bool = False) set[str] | dict[str, Property[Any]] #
Collect the names of properties on this class.
Warning
In a future version of Bokeh, this method will return a dictionary mapping property names to property objects. To future-proof this current usage of this method, wrap the return value in
list
.- Returns:
property names
- classmethod properties_with_refs() dict[str, Property[Any]] #
Collect the names of all properties on this class that also have references.
This method always traverses the class hierarchy and includes properties defined on any parent classes.
- 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:
- 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 FactorRange(*args: Any, id: ID | None = None, **kwargs: Any)[source]#
Bases:
Range
A Range of values for a categorical dimension.
In addition to supplying
factors
as a keyword argument to theFactorRange
initializer, you may also instantiate with a sequence of positional arguments:FactorRange("foo", "bar") # equivalent to FactorRange(factors=["foo", "bar"])
Users will normally supply categorical values directly:
p.circle(x=["foo", "bar"], ...)
BokehJS will create a mapping from
"foo"
and"bar"
to a numerical coordinate system called synthetic coordinates. In the simplest cases, factors are separated by a distance of 1.0 in synthetic coordinates, however the exact mapping from factors to synthetic coordinates is affected by the padding properties as well as whether the number of levels the factors have.Users typically do not need to worry about the details of this mapping, however it can be useful to fine tune positions by adding offsets. When supplying factors as coordinates or values, it is possible to add an offset in the synthetic coordinate space by adding a final number value to a factor tuple. For example:
p.circle(x=[("foo", 0.3), ...], ...)
will position the first circle at an
x
position that is offset by adding 0.3 to the synthetic coordinate for"foo"
.JSON Prototype
{ "bounds": null, "end": 0, "factor_padding": 0.0, "factors": [], "group_padding": 1.4, "id": "p61777", "js_event_callbacks": { "type": "map" }, "js_property_callbacks": { "type": "map" }, "max_interval": null, "min_interval": null, "name": null, "range_padding": 0, "range_padding_units": "percent", "start": 0, "subgroup_padding": 0.8, "subscribed_events": { "type": "set" }, "syncable": true, "tags": [] }
- bounds = None#
- Type:
The bounds (in synthetic coordinates) that the range is allowed to go to. Typically used to prevent the user from panning/zooming/etc away from the data.
Note
Synthetic coordinates are only computed in the browser, based on the factors and various padding properties. Some experimentation may be required to arrive at bounds suitable for specific situations.
By default, the bounds will be None, allowing your plot to pan/zoom as far as you want. If bounds are ‘auto’ they will be computed to be the same as the start and end of the
FactorRange
.
- end = 0#
- Type:
Readonly
The end of the range, in synthetic coordinates.
Note
Synthetic coordinates are only computed in the browser, based on the factors and various padding properties. The value of
end
will only be available in situations where bidirectional communication is available (e.g. server, notebook).
- factor_padding = 0.0#
- Type:
How much padding to add in between all lowest-level factors. When
factor_padding
is non-zero, every factor in every group will have the padding value applied.
- factors = []#
- Type:
FactorSeq
A sequence of factors to define this categorical range.
Factors may have 1, 2, or 3 levels. For 1-level factors, each factor is simply a string. For example:
FactorRange(factors=["sales", "marketing", "engineering"])
defines a range with three simple factors that might represent different units of a business.
For 2- and 3- level factors, each factor is a tuple of strings:
FactorRange(factors=[ ["2016", "sales"], ["2016", "marketing"], ["2016", "engineering"], ["2017", "sales"], ["2017", "marketing"], ["2017", "engineering"], ])
defines a range with six 2-level factors that might represent the three business units, grouped by year.
Note that factors and sub-factors may only be strings.
- group_padding = 1.4#
- Type:
How much padding to add in between top-level groups of factors. This property only applies when the overall range factors have either two or three levels. For example, with:
FactorRange(factors=[["foo", "1"], ["foo", "2"], ["bar", "1"]])
The top level groups correspond to
"foo"
and"bar"
, and the group padding will be applied between the factors["foo", "2"]
and["bar", "1"]
- max_interval = None#
-
The level that the range is allowed to zoom out, expressed as the maximum visible interval in synthetic coordinates.. Note that
bounds
can impose an implicit constraint on the maximum interval as well.The default “width” of a category is 1.0 in synthetic coordinates. However, the distance between factors is affected by the various padding properties and whether or not factors are grouped.
- min_interval = None#
-
The level that the range is allowed to zoom in, expressed as the minimum visible interval in synthetic coordinates. If set to
None
(default), the minimum interval is not bounded.The default “width” of a category is 1.0 in synthetic coordinates. However, the distance between factors is affected by the various padding properties and whether or not factors are grouped.
- 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.
- range_padding = 0#
- Type:
How much padding to add around the outside of computed range bounds.
When
range_padding_units
is set to"percent"
, the span of the range span is expanded to make the rangerange_padding
percent larger.When
range_padding_units
is set to"absolute"
, the start and end of the range span are extended by the amountrange_padding
.
- range_padding_units = 'percent'#
- Type:
Whether the
range_padding
should be interpreted as a percentage, or as an absolute quantity. (default:"percent"
)
- start = 0#
- Type:
Readonly
The start of the range, in synthetic coordinates.
Note
Synthetic coordinates are only computed in the browser, based on the factors and various padding properties. The value of
start
will only be available in situations where bidirectional communication is available (e.g. server, notebook).
- subgroup_padding = 0.8#
- Type:
How much padding to add in between mid-level groups of factors. This property only applies when the overall factors have three levels. For example with:
FactorRange(factors=[ ['foo', 'A', '1'], ['foo', 'A', '2'], ['foo', 'A', '3'], ['foo', 'B', '2'], ['bar', 'A', '1'], ['bar', 'A', '2'] ])
This property dictates how much padding to add between the three factors in the [‘foo’, ‘A’] group, and between the two factors in the [bar]
- 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(**overrides: Any) Self #
Duplicate a
HasProps
object.This creates a shallow clone of the original model, i.e. any mutable containers or child models will not be duplicated. Allows to override particular properties while cloning.
- classmethod dataspecs() dict[str, DataSpec] #
Collect the names of all
DataSpec
properties on this class.This method always traverses the class hierarchy and includes properties defined on any parent classes.
- classmethod descriptors() list[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: Callable[[Event], None] | Callable[[], None]) None #
Run callbacks when the specified event occurs on this Model
Not all Events are supported for all Models. See specific Events in bokeh.events for more information on which Models are able to trigger them.
- classmethod parameters() list[Parameter] #
Generate Python
Parameter
values suitable for functions that are derived from the glyph.- Returns:
list(Parameter)
- classmethod properties(*, _with_props: bool = False) set[str] | dict[str, Property[Any]] #
Collect the names of properties on this class.
Warning
In a future version of Bokeh, this method will return a dictionary mapping property names to property objects. To future-proof this current usage of this method, wrap the return value in
list
.- Returns:
property names
- classmethod properties_with_refs() dict[str, Property[Any]] #
Collect the names of all properties on this class that also have references.
This method always traverses the class hierarchy and includes properties defined on any parent classes.
- 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:
- 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 Range(*args: Any, id: ID | None = None, **kwargs: Any)[source]#
Bases:
Model
A base class for all range 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": "p61792", "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(**overrides: Any) Self #
Duplicate a
HasProps
object.This creates a shallow clone of the original model, i.e. any mutable containers or child models will not be duplicated. Allows to override particular properties while cloning.
- classmethod dataspecs() dict[str, DataSpec] #
Collect the names of all
DataSpec
properties on this class.This method always traverses the class hierarchy and includes properties defined on any parent classes.
- classmethod descriptors() list[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: Callable[[Event], None] | Callable[[], None]) None #
Run callbacks when the specified event occurs on this Model
Not all Events are supported for all Models. See specific Events in bokeh.events for more information on which Models are able to trigger them.
- classmethod parameters() list[Parameter] #
Generate Python
Parameter
values suitable for functions that are derived from the glyph.- Returns:
list(Parameter)
- classmethod properties(*, _with_props: bool = False) set[str] | dict[str, Property[Any]] #
Collect the names of properties on this class.
Warning
In a future version of Bokeh, this method will return a dictionary mapping property names to property objects. To future-proof this current usage of this method, wrap the return value in
list
.- Returns:
property names
- classmethod properties_with_refs() dict[str, Property[Any]] #
Collect the names of all properties on this class that also have references.
This method always traverses the class hierarchy and includes properties defined on any parent classes.
- 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:
- 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 Range1d(*args: Any, id: ID | None = None, **kwargs: Any)[source]#
Bases:
NumericalRange
A fixed, closed range [start, end] in a continuous scalar dimension.
In addition to supplying
start
andend
keyword arguments to theRange1d
initializer, you can also instantiate with the convenience syntax:Range(0, 10) # equivalent to Range(start=0, end=10)
JSON Prototype
{ "bounds": null, "end": 1, "id": "p61796", "js_event_callbacks": { "type": "map" }, "js_property_callbacks": { "type": "map" }, "max_interval": null, "min_interval": null, "name": null, "reset_end": null, "reset_start": null, "start": 0, "subscribed_events": { "type": "set" }, "syncable": true, "tags": [] }
- bounds = None#
- Type:
The bounds that the range is allowed to go to. Typically used to prevent the user from panning/zooming/etc away from the data.
If set to
'auto'
, the bounds will be computed to the start and end of the Range.Bounds are provided as a tuple of
(min, max)
so regardless of whether your range is increasing or decreasing, the first item should be the minimum value of the range and the second item should be the maximum. Setting min > max will result in aValueError
.By default, bounds are
None
and your plot to pan/zoom as far as you want. If you only want to constrain one end of the plot, you can set min or max to None.Examples:
Range1d(0, 1, bounds='auto') # Auto-bounded to 0 and 1 (Default behavior) Range1d(start=0, end=1, bounds=(0, None)) # Maximum is unbounded, minimum bounded to 0
- max_interval = None#
-
The level that the range is allowed to zoom out, expressed as the maximum visible interval. Can be a
TimeDelta
. Note thatbounds
can impose an implicit constraint on the maximum interval as well.
- min_interval = None#
-
The level that the range is allowed to zoom in, expressed as the minimum visible interval. If set to
None
(default), the minimum interval is not bound. Can be aTimeDelta
.
- 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.
- reset_end = None#
-
The end of the range to apply when resetting. If set to
None
defaults to theend
value during initialization.
- reset_start = None#
-
The start of the range to apply after reset. If set to
None
defaults to thestart
value during initialization.
- 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(**overrides: Any) Self #
Duplicate a
HasProps
object.This creates a shallow clone of the original model, i.e. any mutable containers or child models will not be duplicated. Allows to override particular properties while cloning.
- classmethod dataspecs() dict[str, DataSpec] #
Collect the names of all
DataSpec
properties on this class.This method always traverses the class hierarchy and includes properties defined on any parent classes.
- classmethod descriptors() list[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: Callable[[Event], None] | Callable[[], None]) None #
Run callbacks when the specified event occurs on this Model
Not all Events are supported for all Models. See specific Events in bokeh.events for more information on which Models are able to trigger them.
- classmethod parameters() list[Parameter] #
Generate Python
Parameter
values suitable for functions that are derived from the glyph.- Returns:
list(Parameter)
- classmethod properties(*, _with_props: bool = False) set[str] | dict[str, Property[Any]] #
Collect the names of properties on this class.
Warning
In a future version of Bokeh, this method will return a dictionary mapping property names to property objects. To future-proof this current usage of this method, wrap the return value in
list
.- Returns:
property names
- classmethod properties_with_refs() dict[str, Property[Any]] #
Collect the names of all properties on this class that also have references.
This method always traverses the class hierarchy and includes properties defined on any parent classes.
- 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:
- 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)