Source code for panel.models.vega
"""
Defines custom VegaPlot bokeh model to render Vega json plots.
"""
from bokeh.core.properties import (
Any, Bool, Dict, Enum, Instance, Int, List, Nullable, String,
)
from bokeh.events import ModelEvent
from bokeh.models import ColumnDataSource, LayoutDOM
from ..config import config
from ..io.resources import bundled_files
from ..util import classproperty
[docs]class VegaEvent(ModelEvent):
event_name = 'vega_event'
def __init__(self, model, data=None):
self.data = data
super().__init__(model=model)
[docs]class VegaPlot(LayoutDOM):
"""
A Bokeh model that wraps around a Vega plot and renders it inside
a Bokeh plot.
"""
__javascript_raw__ = [
f"{config.npm_cdn}/vega@5",
f"{config.npm_cdn}/vega-lite@5",
f"{config.npm_cdn}/vega-embed@6"
]
@classproperty
def __javascript__(cls):
return bundled_files(cls)
@classproperty
def __js_skip__(cls):
return {
'vega': cls.__javascript__[:1],
'vegaLite': cls.__javascript__[1:2],
'vegaEmbed': cls.__javascript__[2:]
}
__js_require__ = {
'paths': {
"vega-embed": f"{config.npm_cdn}/vega-embed@6/build/vega-embed.min",
"vega-lite": f"{config.npm_cdn}/vega-lite@5/build/vega-lite.min",
"vega": f"{config.npm_cdn}/vega@5/build/vega.min"
},
'exports': {'vega-embed': 'vegaEmbed', 'vega': 'vega', 'vega-lite': 'vl'}
}
data = Nullable(Dict(String, Any))
data_sources = Dict(String, Instance(ColumnDataSource))
events = List(String)
show_actions = Bool(False)
theme = Nullable(Enum('excel', 'ggplot2', 'quartz', 'vox', 'fivethirtyeight', 'dark',
'latimes', 'urbaninstitute', 'googlecharts', default=None))
throttle = Dict(String, Int)