PyCafe - Vizro - Vizro for PyCafe Data Visualization

app.py
requirements.txt
app.py
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# Vizro is an open-source toolkit for creating modular data visualization applications.
# check out https://github.com/mckinsey/vizro for more info about Vizro
# and checkout https://vizro.readthedocs.io/en/stable/ for documentation.

from pydantic import BeforeValidator, conlist

import vizro.models as vm
import vizro.plotly.express as px
from vizro import Vizro
import dash_bootstrap_components as dbc

from typing import Annotated, Optional, Literal
from vizro.models._models_utils import check_captured_callable_model

from vizro.models.types import ComponentType

iris = px.data.iris()

class AccordionContent(vm.VizroBaseModel):
    """New custom component `Jumbotron`."""

    type: Literal["accordion-with-content"] = "accordion-with-content"
    components: conlist(Annotated[ComponentType, BeforeValidator(check_captured_callable_model)], min_length=1)
    title: Optional[str] = None

    def build(self):
        return dbc.Accordion(
            [dbc.AccordionItem([component.build() for component in self.components], title=self.title)]
)


vm.Page.add_type("components", AccordionContent)


page = vm.Page(
    title="Page with subsections",
    layout=vm.Layout(grid=[[0, 1]]),
    components=[
        AccordionContent(title="Show chart", components=[vm.Container(
            title="Container I",
            components=[vm.Graph(figure=px.box(iris, x="species", y="sepal_length", color="species")),
                        vm.Graph(figure=px.box(iris, x="species", y="sepal_length", color="species"))],
        ),]),
        vm.Container(
            title="Container II",
            components=[vm.Graph(figure=px.box(iris, x="species", y="sepal_length", color="species"))],
        ),
    ],
)

dashboard = vm.Dashboard(pages=[page])
Vizro().build(dashboard).run()
Py.Cafe

components-in-accordion

Vizro for PyCafe Data Visualization
