Bokeh Objects¶

Low-level Object Interface¶

Below is a notional diagram that shows many of the most common kinds of models that comprise the Bokeh object system. To create Bokeh plots, these objects are created and assembled, and then this object graph is serialized to JSON. This JSON representation is consumed by the BokehJS client library, which uses it to render the plot.

Where space permits, the attributes of the model are show inline. Not all objects are shown below; see the Reference Guide for full details.

Models and properties¶

The primary components of the low-level API are models, which are objects that have attributes that can be automatically serialized in a way that lets them be reconstituted as Backbone objects within BokehJS. Technically, models are classes that inherit from HasProps at some point:

from bokeh.properties import HasProps, Int

class Whatever(HasProps):
    """ `Whatever` model. """

Models can derive from other models as well as mixins that provide common sets of properties (e.g. see LineProps, etc. in bokeh.mixins). An example might look like this:

class Another(Whatever, LineProps):
    """ `Another` model. """

Models contain properties, which are class attributes of type Property, e.g:

class IntProps(HasFields):

    prop1 = Int
    prop2 = Int()
    prop3 = Int(10)

The IntProps model represents objects that have three integer values, prop1, prop2, and prop3, that can be automatically serialized from python, and unserialized by BokehJS.

There is wide variety of property types, ranging from primitive types such as:

• Byte
• Int
• Float
• Complex
• String

As well as container-like properties, that take other Properties as parameters:

• List — for a list of one type of objects: List(Int)
• Dict — for a mapping between two type: Dict(String, Double)

and finally some specialized types like

• Instance — to hold a reference to another model: Instance(Plot)
• Enum — to represent enumerated values: Enum("foo", "bar", "baz")
• Either — to create a union type: Either(Int, String)
• Range — to restrict values to a given range: Instance(Plot)

The primary benefit of these property types is that validation can be performed and meaningful error reporting can occur when an attempt is made to assign an invalid type or value.

See bokeh.properties for full details.

An example of a more complex, realistic model might look like this:

class Sample(HasProps, FillProps):
    """ `Sample` model. """

    prop1 = Int(127)
    prop2 = Either(Int, List(Int), Dict(String, List(Int)))
    prop3 = Enum("x", "y", "z")
    prop4 = Range(Float, 0.0, 1.0)
    prop5 = List(Instance(Range1d))

There is a special property-like type named Include, that make it simpler to mix in in properties from a mixin using a prefix, e.g.:

class Includes(HasProps):
    """ `Includes` model. """

    some_props = Include(FillProps)

In this case there is a placeholder property some_props, that will be removed and automatically replaced with all the properties from FillProps, each with some_ appended as a prefix.

Using Include is equivalent to writing:

class ExplicitIncludes(HasProps):
    """ `ExplicitIncludes` model. """

    some_fill_color = ColorSpec(default="gray")
    some_fill_alpha = DataSpec(default=1.0)

Note that you could inherit from FillProps in this case, as well:

class IncludesExtends(HasProps, FillProps):
    """ `IncludesExtends` model. """

    some = String
    some_props = Include(FillProps)

but note that this is equivalent to:

class ExplicitIncludesExtends(HasProps):
    """ `ExplicitIncludesExtends` model. """

    fill_color = ColorSpec(default="gray")
    fill_alpha = DataSpec(default=1.0)
    some = String
    some_fill_color = ColorSpec(default="gray")
    some_fill_alpha = DataSpec(default=1.0)