sources#
- class AjaxDataSource(*args: Any, id: ID | None = None, **kwargs: Any)[source]#
Bases:
WebDataSource
A data source that can populate columns by making Ajax calls to REST endpoints.
The
AjaxDataSource
can be especially useful if you want to make a standalone document (i.e. not backed by the Bokeh server) that can still dynamically update using an existing REST API.The response from the REST API should match the
.data
property of a standardColumnDataSource
, i.e. a JSON dict that maps names to arrays of values:{ 'x' : [1, 2, 3, ...], 'y' : [9, 3, 2, ...] }
Alternatively, if the REST API returns a different format, a
CustomJS
callback can be provided to convert the REST response into Bokeh format, via theadapter
property of this data source.Initial data can be set by specifying the
data
property directly. This is necessary when used in conjunction with aFactorRange
, even if the columns in data` are empty.A full example can be seen at examples/basic/data/ajax_source.py
JSON Prototype
{ "adapter": null, "content_type": "application/json", "data": { "type": "map" }, "data_url": { "name": "unset", "type": "symbol" }, "default_values": { "type": "map" }, "http_headers": { "type": "map" }, "id": "p62420", "if_modified": false, "js_event_callbacks": { "type": "map" }, "js_property_callbacks": { "type": "map" }, "max_size": null, "method": "POST", "mode": "replace", "name": null, "polling_interval": null, "selected": { "attributes": { "indices": [], "line_indices": [] }, "id": "p62421", "name": "Selection", "type": "object" }, "selection_policy": { "id": "p62422", "name": "UnionRenderers", "type": "object" }, "subscribed_events": { "type": "set" }, "syncable": true, "tags": [] }
- adapter = None#
-
A JavaScript callback to adapt raw JSON responses to Bokeh
ColumnDataSource
format.If provided, this callback is executes immediately after the JSON data is received, but before appending or replacing data in the data source. The
CustomJS
callback will receive theAjaxDataSource
ascb_obj
and will receive the raw JSON response ascb_data.response
. The callback code should return adata
object suitable for a BokehColumnDataSource
(i.e. a mapping of string column names to arrays of data).
- content_type = 'application/json'#
- Type:
Set the “contentType” parameter for the Ajax request.
- data = {}#
- Type:
Mapping of column names to sequences of data. The columns can be, e.g, Python lists or tuples, NumPy arrays, etc.
The .data attribute can also be set from Pandas DataFrames or GroupBy objects. In these cases, the behaviour is identical to passing the objects to the
ColumnDataSource
initializer.
- default_values = {}#
-
Defines the default value for each column.
This is used when inserting rows into a data source, e.g. by edit tools, when a value for a given column is not explicitly provided. If a default value is missing, a tool will defer to its own configuration or will try to let the data source to infer a sensible default value.
- http_headers = {}#
-
Specify HTTP headers to set for the Ajax request.
Example:
ajax_source.headers = { 'x-my-custom-header': 'some value' }
- if_modified = False#
- Type:
Whether to include an
If-Modified-Since
header in Ajax requests to the server. If this header is supported by the server, then only new data since the last request will be returned.
- max_size = None#
-
Maximum size of the data columns. If a new fetch would result in columns larger than
max_size
, then earlier data is dropped to make room.
- method = 'POST'#
- Type:
Enum
(Enumeration(POST, GET))
Specify the HTTP method to use for the Ajax request (GET or POST)
- mode = 'replace'#
- Type:
Enum
(Enumeration(replace, append))
Whether to append new data to existing data (up to
max_size
), or to replace existing data entirely.
- 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.
- polling_interval = None#
-
A polling interval (in milliseconds) for updating data source.
- selected = Selection(id='p62462', ...)#
- Type:
Readonly
An instance of a
Selection
that indicates selected indices on thisDataSource
. This is a read-only property. You may only change the attributes of this object to change the selection (e.g.,selected.indices
).
- selection_policy = UnionRenderers(id='p62466', ...)#
- Type:
An instance of a
SelectionPolicy
that determines how selections are set.
- 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.
- add(data: Sequence[Any], name: str | None = None) str #
Appends a new column of data to the data source.
- 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
- classmethod from_df(data: pd.DataFrame) DataDict #
Create a
dict
of columns from a PandasDataFrame
, suitable for creating aColumnDataSource
.- Parameters:
data (DataFrame) – data to convert
- Returns:
dict[str, np.array]
- classmethod from_groupby(data: pd.core.groupby.GroupBy) DataDict #
Create a
dict
of columns from a PandasGroupBy
, suitable for creating aColumnDataSource
.The data generated is the result of running
describe
on the group.- Parameters:
data (Groupby) – data to convert
- Returns:
dict[str, np.array]
- 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)
- patch(patches: Patches, setter: Setter | None = None) None #
Efficiently update data source columns at specific locations
If it is only necessary to update a small subset of data in a
ColumnDataSource
, this method can be used to efficiently update only the subset, instead of requiring the entire data set to be sent.This method should be passed a dictionary that maps column names to lists of tuples that describe a patch change to apply. To replace individual items in columns entirely, the tuples should be of the form:
(index, new_value) # replace a single column value # or (slice, new_values) # replace several column values
Values at an index or slice will be replaced with the corresponding new values.
In the case of columns whose values are other arrays or lists, (e.g. image or patches glyphs), it is also possible to patch “subregions”. In this case the first item of the tuple should be a whose first element is the index of the array item in the CDS patch, and whose subsequent elements are integer indices or slices into the array item:
# replace the entire 10th column of the 2nd array: +----------------- index of item in column data source | | +--------- row subindex into array item | | | | +- column subindex into array item V V V ([2, slice(None), 10], new_values)
Imagining a list of 2d NumPy arrays, the patch above is roughly equivalent to:
data = [arr1, arr2, ...] # list of 2d arrays data[2][:, 10] = new_data
There are some limitations to the kinds of slices and data that can be accepted.
Negative
start
,stop
, orstep
values for slices will result in aValueError
.In a slice,
start > stop
will result in aValueError
When patching 1d or 2d subitems, the subitems must be NumPy arrays.
New values must be supplied as a flattened one-dimensional array of the appropriate size.
- Parameters:
patches (dict[str, list[tuple]]) – lists of patches for each column
- Returns:
None
- Raises:
Example:
The following example shows how to patch entire column elements. In this case,
source = ColumnDataSource(data=dict(foo=[10, 20, 30], bar=[100, 200, 300])) patches = { 'foo' : [ (slice(2), [11, 12]) ], 'bar' : [ (0, 101), (2, 301) ], } source.patch(patches)
After this operation, the value of the
source.data
will be:dict(foo=[11, 12, 30], bar=[101, 200, 301])
For a more comprehensive example, see examples/server/app/patch_app.py.
- 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(name: str) None #
Remove a column of data.
- Parameters:
name (str) – name of the column to remove
- Returns:
None
Note
If the column name does not exist, a warning is issued.
- 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
- stream(new_data: DataDict, rollover: int | None = None) None #
Efficiently update data source columns with new append-only data.
In cases where it is necessary to update data columns in, this method can efficiently send only the new data, instead of requiring the entire data set to be re-sent.
- Parameters:
a mapping of column names to sequences of new data to append to each column.
All columns of the data source must be present in
new_data
, with identical-length append data.rollover (int, optional) – A maximum column size, above which data from the start of the column begins to be discarded. If None, then columns will continue to grow unbounded (default: None)
- Returns:
None
- Raises:
Example:
source = ColumnDataSource(data=dict(foo=[], bar=[])) # has new, identical-length updates for all columns in source new_data = { 'foo' : [10, 20], 'bar' : [100, 200], } source.stream(new_data)
- 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_df() pd.DataFrame #
Convert this data source to pandas
DataFrame
.- Returns:
DataFrame
- 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 CDSView(*args: Any, id: ID | None = None, **kwargs: Any)[source]#
Bases:
Model
A view into a
ColumnDataSource
that represents a row-wise subset.JSON Prototype
{ "filter": { "id": "p62474", "name": "AllIndices", "type": "object" }, "id": "p62473", "js_event_callbacks": { "type": "map" }, "js_property_callbacks": { "type": "map" }, "name": null, "subscribed_events": { "type": "set" }, "syncable": true, "tags": [] }
- filter = AllIndices(id='p62477', ...)#
-
Defines the subset of indices to use from the data source this view applies to.
By default all indices are used (
AllIndices
filter). This can be changed by using specialized filters likeIndexFilter
,BooleanFilter
, etc. Filters can be composed using set operations to create non-trivial data masks. This can be accomplished by directly using models likeInversionFilter
,UnionFilter
, etc., or by using set operators on filters, e.g.:# filters everything but indexes 10 and 11 cds_view.filter &= ~IndexFilter(indices=[10, 11])
- 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 ColumnDataSource(*args: Any, id: ID | None = None, **kwargs: Any)[source]#
Bases:
ColumnarDataSource
Maps names of columns to sequences or arrays.
The
ColumnDataSource
is a fundamental data structure of Bokeh. Most plots, data tables, etc. will be driven by aColumnDataSource
.If the
ColumnDataSource
initializer is called with a single argument that can be any of the following:A Python
dict
that maps string names to sequences of values, e.g. lists, arrays, etc.data = {'x': [1,2,3,4], 'y': np.array([10.0, 20.0, 30.0, 40.0])} source = ColumnDataSource(data)
Note
ColumnDataSource
only creates a shallow copy ofdata
. Use e.g.ColumnDataSource(copy.deepcopy(data))
if initializing from anotherColumnDataSource.data
object that you want to keep independent.A Pandas
DataFrame
objectsource = ColumnDataSource(df)
In this case the CDS will have columns corresponding to the columns of the
DataFrame
. If theDataFrame
columns have multiple levels, they will be flattened using an underscore (e.g. level_0_col_level_1_col). The index of theDataFrame
will be flattened to anIndex
of tuples if it’s aMultiIndex
, and then reset usingreset_index
. The result will be a column with the same name if the index was named, or level_0_name_level_1_name if it was a namedMultiIndex
. If theIndex
did not have a name or theMultiIndex
name could not be flattened/determined, thereset_index
function will name the index columnindex
, orlevel_0
if the nameindex
is not available.A Pandas
GroupBy
objectgroup = df.groupby(('colA', 'ColB'))
In this case the CDS will have columns corresponding to the result of calling
group.describe()
. Thedescribe
method generates columns for statistical measures such asmean
andcount
for all the non-grouped original columns. The CDS columns are formed by joining original column names with the computed measure. For example, if aDataFrame
has columns'year'
and'mpg'
. Then passingdf.groupby('year')
to a CDS will result in columns such as'mpg_mean'
If the
GroupBy.describe
result has a named index column, then CDS will also have a column with this name. However, if the index name (or any subname of aMultiIndex
) isNone
, then the CDS will have a column generically namedindex
for the index.Note this capability to adapt
GroupBy
objects may only work with Pandas>=0.20.0
.
Note
There is an implicit assumption that all the columns in a given
ColumnDataSource
all have the same length at all times. For this reason, it is usually preferable to update the.data
property of a data source “all at once”.JSON Prototype
{ "data": { "type": "map" }, "default_values": { "type": "map" }, "id": "p62484", "js_event_callbacks": { "type": "map" }, "js_property_callbacks": { "type": "map" }, "name": null, "selected": { "attributes": { "indices": [], "line_indices": [] }, "id": "p62485", "name": "Selection", "type": "object" }, "selection_policy": { "id": "p62486", "name": "UnionRenderers", "type": "object" }, "subscribed_events": { "type": "set" }, "syncable": true, "tags": [] }
- data = {}#
- Type:
Mapping of column names to sequences of data. The columns can be, e.g, Python lists or tuples, NumPy arrays, etc.
The .data attribute can also be set from Pandas DataFrames or GroupBy objects. In these cases, the behaviour is identical to passing the objects to the
ColumnDataSource
initializer.
- default_values = {}#
-
Defines the default value for each column.
This is used when inserting rows into a data source, e.g. by edit tools, when a value for a given column is not explicitly provided. If a default value is missing, a tool will defer to its own configuration or will try to let the data source to infer a sensible default value.
- 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.
- selected = Selection(id='p62499', ...)#
- Type:
Readonly
An instance of a
Selection
that indicates selected indices on thisDataSource
. This is a read-only property. You may only change the attributes of this object to change the selection (e.g.,selected.indices
).
- selection_policy = UnionRenderers(id='p62503', ...)#
- Type:
An instance of a
SelectionPolicy
that determines how selections are set.
- 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.
- __init__(data: DataDict | pd.DataFrame | pd.core.groupby.GroupBy, **kwargs: Any) None [source]#
- __init__(**kwargs: Any) None
If called with a single argument that is a dict or
pandas.DataFrame
, treat that implicitly as the “data” attribute.
- add(data: Sequence[Any], name: str | None = None) str [source]#
Appends a new column of data to the data source.
- 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
- classmethod from_df(data: pd.DataFrame) DataDict [source]#
Create a
dict
of columns from a PandasDataFrame
, suitable for creating aColumnDataSource
.- Parameters:
data (DataFrame) – data to convert
- Returns:
dict[str, np.array]
- classmethod from_groupby(data: pd.core.groupby.GroupBy) DataDict [source]#
Create a
dict
of columns from a PandasGroupBy
, suitable for creating aColumnDataSource
.The data generated is the result of running
describe
on the group.- Parameters:
data (Groupby) – data to convert
- Returns:
dict[str, np.array]
- 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)
- patch(patches: Patches, setter: Setter | None = None) None [source]#
Efficiently update data source columns at specific locations
If it is only necessary to update a small subset of data in a
ColumnDataSource
, this method can be used to efficiently update only the subset, instead of requiring the entire data set to be sent.This method should be passed a dictionary that maps column names to lists of tuples that describe a patch change to apply. To replace individual items in columns entirely, the tuples should be of the form:
(index, new_value) # replace a single column value # or (slice, new_values) # replace several column values
Values at an index or slice will be replaced with the corresponding new values.
In the case of columns whose values are other arrays or lists, (e.g. image or patches glyphs), it is also possible to patch “subregions”. In this case the first item of the tuple should be a whose first element is the index of the array item in the CDS patch, and whose subsequent elements are integer indices or slices into the array item:
# replace the entire 10th column of the 2nd array: +----------------- index of item in column data source | | +--------- row subindex into array item | | | | +- column subindex into array item V V V ([2, slice(None), 10], new_values)
Imagining a list of 2d NumPy arrays, the patch above is roughly equivalent to:
data = [arr1, arr2, ...] # list of 2d arrays data[2][:, 10] = new_data
There are some limitations to the kinds of slices and data that can be accepted.
Negative
start
,stop
, orstep
values for slices will result in aValueError
.In a slice,
start > stop
will result in aValueError
When patching 1d or 2d subitems, the subitems must be NumPy arrays.
New values must be supplied as a flattened one-dimensional array of the appropriate size.
- Parameters:
patches (dict[str, list[tuple]]) – lists of patches for each column
- Returns:
None
- Raises:
Example:
The following example shows how to patch entire column elements. In this case,
source = ColumnDataSource(data=dict(foo=[10, 20, 30], bar=[100, 200, 300])) patches = { 'foo' : [ (slice(2), [11, 12]) ], 'bar' : [ (0, 101), (2, 301) ], } source.patch(patches)
After this operation, the value of the
source.data
will be:dict(foo=[11, 12, 30], bar=[101, 200, 301])
For a more comprehensive example, see examples/server/app/patch_app.py.
- 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(name: str) None [source]#
Remove a column of data.
- Parameters:
name (str) – name of the column to remove
- Returns:
None
Note
If the column name does not exist, a warning is issued.
- 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
- stream(new_data: DataDict, rollover: int | None = None) None [source]#
Efficiently update data source columns with new append-only data.
In cases where it is necessary to update data columns in, this method can efficiently send only the new data, instead of requiring the entire data set to be re-sent.
- Parameters:
a mapping of column names to sequences of new data to append to each column.
All columns of the data source must be present in
new_data
, with identical-length append data.rollover (int, optional) – A maximum column size, above which data from the start of the column begins to be discarded. If None, then columns will continue to grow unbounded (default: None)
- Returns:
None
- Raises:
Example:
source = ColumnDataSource(data=dict(foo=[], bar=[])) # has new, identical-length updates for all columns in source new_data = { 'foo' : [10, 20], 'bar' : [100, 200], } source.stream(new_data)
- 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 ColumnarDataSource(*args: Any, id: ID | None = None, **kwargs: Any)[source]#
Bases:
DataSource
A base class for data source types, which can be mapped onto a columnar format.
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
{ "default_values": { "type": "map" }, "id": "p62510", "js_event_callbacks": { "type": "map" }, "js_property_callbacks": { "type": "map" }, "name": null, "selected": { "attributes": { "indices": [], "line_indices": [] }, "id": "p62511", "name": "Selection", "type": "object" }, "selection_policy": { "id": "p62512", "name": "UnionRenderers", "type": "object" }, "subscribed_events": { "type": "set" }, "syncable": true, "tags": [] }
- default_values = {}#
-
Defines the default value for each column.
This is used when inserting rows into a data source, e.g. by edit tools, when a value for a given column is not explicitly provided. If a default value is missing, a tool will defer to its own configuration or will try to let the data source to infer a sensible default value.
- 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.
- selected = Selection(id='p62522', ...)#
- Type:
Readonly
An instance of a
Selection
that indicates selected indices on thisDataSource
. This is a read-only property. You may only change the attributes of this object to change the selection (e.g.,selected.indices
).
- selection_policy = UnionRenderers(id='p62526', ...)#
- Type:
An instance of a
SelectionPolicy
that determines how selections are set.
- 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 DataSource(*args: Any, id: ID | None = None, **kwargs: Any)[source]#
Bases:
Model
A base class for data source 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": "p62533", "js_event_callbacks": { "type": "map" }, "js_property_callbacks": { "type": "map" }, "name": null, "selected": { "attributes": { "indices": [], "line_indices": [] }, "id": "p62534", "name": "Selection", "type": "object" }, "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.
- selected = Selection(id='p62539', ...)#
- Type:
Readonly
An instance of a
Selection
that indicates selected indices on thisDataSource
. This is a read-only property. You may only change the attributes of this object to change the selection (e.g.,selected.indices
).
- 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 GeoJSONDataSource(*args: Any, id: ID | None = None, **kwargs: Any)[source]#
Bases:
ColumnarDataSource
JSON Prototype
{ "default_values": { "type": "map" }, "geojson": { "name": "unset", "type": "symbol" }, "id": "p62544", "js_event_callbacks": { "type": "map" }, "js_property_callbacks": { "type": "map" }, "name": null, "selected": { "attributes": { "indices": [], "line_indices": [] }, "id": "p62545", "name": "Selection", "type": "object" }, "selection_policy": { "id": "p62546", "name": "UnionRenderers", "type": "object" }, "subscribed_events": { "type": "set" }, "syncable": true, "tags": [] }
- default_values = {}#
-
Defines the default value for each column.
This is used when inserting rows into a data source, e.g. by edit tools, when a value for a given column is not explicitly provided. If a default value is missing, a tool will defer to its own configuration or will try to let the data source to infer a sensible default value.
- geojson = Undefined#
-
GeoJSON that contains features for plotting. Currently
GeoJSONDataSource
can only process aFeatureCollection
orGeometryCollection
.
- 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.
- selected = Selection(id='p62559', ...)#
- Type:
Readonly
An instance of a
Selection
that indicates selected indices on thisDataSource
. This is a read-only property. You may only change the attributes of this object to change the selection (e.g.,selected.indices
).
- selection_policy = UnionRenderers(id='p62563', ...)#
- Type:
An instance of a
SelectionPolicy
that determines how selections are set.
- 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 ServerSentDataSource(*args: Any, id: ID | None = None, **kwargs: Any)[source]#
Bases:
WebDataSource
A data source that can populate columns by receiving server sent events endpoints.
JSON Prototype
{ "adapter": null, "data": { "type": "map" }, "data_url": { "name": "unset", "type": "symbol" }, "default_values": { "type": "map" }, "id": "p62570", "js_event_callbacks": { "type": "map" }, "js_property_callbacks": { "type": "map" }, "max_size": null, "mode": "replace", "name": null, "selected": { "attributes": { "indices": [], "line_indices": [] }, "id": "p62571", "name": "Selection", "type": "object" }, "selection_policy": { "id": "p62572", "name": "UnionRenderers", "type": "object" }, "subscribed_events": { "type": "set" }, "syncable": true, "tags": [] }
- adapter = None#
-
A JavaScript callback to adapt raw JSON responses to Bokeh
ColumnDataSource
format.If provided, this callback is executes immediately after the JSON data is received, but before appending or replacing data in the data source. The
CustomJS
callback will receive theAjaxDataSource
ascb_obj
and will receive the raw JSON response ascb_data.response
. The callback code should return adata
object suitable for a BokehColumnDataSource
(i.e. a mapping of string column names to arrays of data).
- data = {}#
- Type:
Mapping of column names to sequences of data. The columns can be, e.g, Python lists or tuples, NumPy arrays, etc.
The .data attribute can also be set from Pandas DataFrames or GroupBy objects. In these cases, the behaviour is identical to passing the objects to the
ColumnDataSource
initializer.
- default_values = {}#
-
Defines the default value for each column.
This is used when inserting rows into a data source, e.g. by edit tools, when a value for a given column is not explicitly provided. If a default value is missing, a tool will defer to its own configuration or will try to let the data source to infer a sensible default value.
- max_size = None#
-
Maximum size of the data columns. If a new fetch would result in columns larger than
max_size
, then earlier data is dropped to make room.
- mode = 'replace'#
- Type:
Enum
(Enumeration(replace, append))
Whether to append new data to existing data (up to
max_size
), or to replace existing data entirely.
- 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.
- selected = Selection(id='p62597', ...)#
- Type:
Readonly
An instance of a
Selection
that indicates selected indices on thisDataSource
. This is a read-only property. You may only change the attributes of this object to change the selection (e.g.,selected.indices
).
- selection_policy = UnionRenderers(id='p62601', ...)#
- Type:
An instance of a
SelectionPolicy
that determines how selections are set.
- 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.
- add(data: Sequence[Any], name: str | None = None) str #
Appends a new column of data to the data source.
- 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
- classmethod from_df(data: pd.DataFrame) DataDict #
Create a
dict
of columns from a PandasDataFrame
, suitable for creating aColumnDataSource
.- Parameters:
data (DataFrame) – data to convert
- Returns:
dict[str, np.array]
- classmethod from_groupby(data: pd.core.groupby.GroupBy) DataDict #
Create a
dict
of columns from a PandasGroupBy
, suitable for creating aColumnDataSource
.The data generated is the result of running
describe
on the group.- Parameters:
data (Groupby) – data to convert
- Returns:
dict[str, np.array]
- 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)
- patch(patches: Patches, setter: Setter | None = None) None #
Efficiently update data source columns at specific locations
If it is only necessary to update a small subset of data in a
ColumnDataSource
, this method can be used to efficiently update only the subset, instead of requiring the entire data set to be sent.This method should be passed a dictionary that maps column names to lists of tuples that describe a patch change to apply. To replace individual items in columns entirely, the tuples should be of the form:
(index, new_value) # replace a single column value # or (slice, new_values) # replace several column values
Values at an index or slice will be replaced with the corresponding new values.
In the case of columns whose values are other arrays or lists, (e.g. image or patches glyphs), it is also possible to patch “subregions”. In this case the first item of the tuple should be a whose first element is the index of the array item in the CDS patch, and whose subsequent elements are integer indices or slices into the array item:
# replace the entire 10th column of the 2nd array: +----------------- index of item in column data source | | +--------- row subindex into array item | | | | +- column subindex into array item V V V ([2, slice(None), 10], new_values)
Imagining a list of 2d NumPy arrays, the patch above is roughly equivalent to:
data = [arr1, arr2, ...] # list of 2d arrays data[2][:, 10] = new_data
There are some limitations to the kinds of slices and data that can be accepted.
Negative
start
,stop
, orstep
values for slices will result in aValueError
.In a slice,
start > stop
will result in aValueError
When patching 1d or 2d subitems, the subitems must be NumPy arrays.
New values must be supplied as a flattened one-dimensional array of the appropriate size.
- Parameters:
patches (dict[str, list[tuple]]) – lists of patches for each column
- Returns:
None
- Raises:
Example:
The following example shows how to patch entire column elements. In this case,
source = ColumnDataSource(data=dict(foo=[10, 20, 30], bar=[100, 200, 300])) patches = { 'foo' : [ (slice(2), [11, 12]) ], 'bar' : [ (0, 101), (2, 301) ], } source.patch(patches)
After this operation, the value of the
source.data
will be:dict(foo=[11, 12, 30], bar=[101, 200, 301])
For a more comprehensive example, see examples/server/app/patch_app.py.
- 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(name: str) None #
Remove a column of data.
- Parameters:
name (str) – name of the column to remove
- Returns:
None
Note
If the column name does not exist, a warning is issued.
- 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
- stream(new_data: DataDict, rollover: int | None = None) None #
Efficiently update data source columns with new append-only data.
In cases where it is necessary to update data columns in, this method can efficiently send only the new data, instead of requiring the entire data set to be re-sent.
- Parameters:
a mapping of column names to sequences of new data to append to each column.
All columns of the data source must be present in
new_data
, with identical-length append data.rollover (int, optional) – A maximum column size, above which data from the start of the column begins to be discarded. If None, then columns will continue to grow unbounded (default: None)
- Returns:
None
- Raises:
Example:
source = ColumnDataSource(data=dict(foo=[], bar=[])) # has new, identical-length updates for all columns in source new_data = { 'foo' : [10, 20], 'bar' : [100, 200], } source.stream(new_data)
- 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_df() pd.DataFrame #
Convert this data source to pandas
DataFrame
.- Returns:
DataFrame
- 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 WebDataSource(*args: Any, id: ID | None = None, **kwargs: Any)[source]#
Bases:
ColumnDataSource
Base class for web column data sources that can update from data URLs.
Note
This base class is typically not useful to instantiate on its own.
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
{ "adapter": null, "data": { "type": "map" }, "data_url": { "name": "unset", "type": "symbol" }, "default_values": { "type": "map" }, "id": "p62608", "js_event_callbacks": { "type": "map" }, "js_property_callbacks": { "type": "map" }, "max_size": null, "mode": "replace", "name": null, "selected": { "attributes": { "indices": [], "line_indices": [] }, "id": "p62609", "name": "Selection", "type": "object" }, "selection_policy": { "id": "p62610", "name": "UnionRenderers", "type": "object" }, "subscribed_events": { "type": "set" }, "syncable": true, "tags": [] }
- adapter = None#
-
A JavaScript callback to adapt raw JSON responses to Bokeh
ColumnDataSource
format.If provided, this callback is executes immediately after the JSON data is received, but before appending or replacing data in the data source. The
CustomJS
callback will receive theAjaxDataSource
ascb_obj
and will receive the raw JSON response ascb_data.response
. The callback code should return adata
object suitable for a BokehColumnDataSource
(i.e. a mapping of string column names to arrays of data).
- data = {}#
- Type:
Mapping of column names to sequences of data. The columns can be, e.g, Python lists or tuples, NumPy arrays, etc.
The .data attribute can also be set from Pandas DataFrames or GroupBy objects. In these cases, the behaviour is identical to passing the objects to the
ColumnDataSource
initializer.
- default_values = {}#
-
Defines the default value for each column.
This is used when inserting rows into a data source, e.g. by edit tools, when a value for a given column is not explicitly provided. If a default value is missing, a tool will defer to its own configuration or will try to let the data source to infer a sensible default value.
- max_size = None#
-
Maximum size of the data columns. If a new fetch would result in columns larger than
max_size
, then earlier data is dropped to make room.
- mode = 'replace'#
- Type:
Enum
(Enumeration(replace, append))
Whether to append new data to existing data (up to
max_size
), or to replace existing data entirely.
- 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.
- selected = Selection(id='p62635', ...)#
- Type:
Readonly
An instance of a
Selection
that indicates selected indices on thisDataSource
. This is a read-only property. You may only change the attributes of this object to change the selection (e.g.,selected.indices
).
- selection_policy = UnionRenderers(id='p62639', ...)#
- Type:
An instance of a
SelectionPolicy
that determines how selections are set.
- 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.
- add(data: Sequence[Any], name: str | None = None) str #
Appends a new column of data to the data source.
- 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
- classmethod from_df(data: pd.DataFrame) DataDict #
Create a
dict
of columns from a PandasDataFrame
, suitable for creating aColumnDataSource
.- Parameters:
data (DataFrame) – data to convert
- Returns:
dict[str, np.array]
- classmethod from_groupby(data: pd.core.groupby.GroupBy) DataDict #
Create a
dict
of columns from a PandasGroupBy
, suitable for creating aColumnDataSource
.The data generated is the result of running
describe
on the group.- Parameters:
data (Groupby) – data to convert
- Returns:
dict[str, np.array]
- 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)
- patch(patches: Patches, setter: Setter | None = None) None #
Efficiently update data source columns at specific locations
If it is only necessary to update a small subset of data in a
ColumnDataSource
, this method can be used to efficiently update only the subset, instead of requiring the entire data set to be sent.This method should be passed a dictionary that maps column names to lists of tuples that describe a patch change to apply. To replace individual items in columns entirely, the tuples should be of the form:
(index, new_value) # replace a single column value # or (slice, new_values) # replace several column values
Values at an index or slice will be replaced with the corresponding new values.
In the case of columns whose values are other arrays or lists, (e.g. image or patches glyphs), it is also possible to patch “subregions”. In this case the first item of the tuple should be a whose first element is the index of the array item in the CDS patch, and whose subsequent elements are integer indices or slices into the array item:
# replace the entire 10th column of the 2nd array: +----------------- index of item in column data source | | +--------- row subindex into array item | | | | +- column subindex into array item V V V ([2, slice(None), 10], new_values)
Imagining a list of 2d NumPy arrays, the patch above is roughly equivalent to:
data = [arr1, arr2, ...] # list of 2d arrays data[2][:, 10] = new_data
There are some limitations to the kinds of slices and data that can be accepted.
Negative
start
,stop
, orstep
values for slices will result in aValueError
.In a slice,
start > stop
will result in aValueError
When patching 1d or 2d subitems, the subitems must be NumPy arrays.
New values must be supplied as a flattened one-dimensional array of the appropriate size.
- Parameters:
patches (dict[str, list[tuple]]) – lists of patches for each column
- Returns:
None
- Raises:
Example:
The following example shows how to patch entire column elements. In this case,
source = ColumnDataSource(data=dict(foo=[10, 20, 30], bar=[100, 200, 300])) patches = { 'foo' : [ (slice(2), [11, 12]) ], 'bar' : [ (0, 101), (2, 301) ], } source.patch(patches)
After this operation, the value of the
source.data
will be:dict(foo=[11, 12, 30], bar=[101, 200, 301])
For a more comprehensive example, see examples/server/app/patch_app.py.
- 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(name: str) None #
Remove a column of data.
- Parameters:
name (str) – name of the column to remove
- Returns:
None
Note
If the column name does not exist, a warning is issued.
- 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
- stream(new_data: DataDict, rollover: int | None = None) None #
Efficiently update data source columns with new append-only data.
In cases where it is necessary to update data columns in, this method can efficiently send only the new data, instead of requiring the entire data set to be re-sent.
- Parameters:
a mapping of column names to sequences of new data to append to each column.
All columns of the data source must be present in
new_data
, with identical-length append data.rollover (int, optional) – A maximum column size, above which data from the start of the column begins to be discarded. If None, then columns will continue to grow unbounded (default: None)
- Returns:
None
- Raises:
Example:
source = ColumnDataSource(data=dict(foo=[], bar=[])) # has new, identical-length updates for all columns in source new_data = { 'foo' : [10, 20], 'bar' : [100, 200], } source.stream(new_data)
- 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_df() pd.DataFrame #
Convert this data source to pandas
DataFrame
.- Returns:
DataFrame
- 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)