spaday-vega 0.1.1

Declarative Vega and Vega-Lite visualizations for spaday.

Usage

VegaChart accepts either grammar through the same typed Python component. Vega-Embed selects the correct runtime from the specification's $schema.

from spaday.backends.starlette import serve
from spaday_vega import VegaChart, package

spec = {
    "$schema": "https://vega.github.io/schema/vega-lite/v6.json",
    "data": {"name": "values"},
    "datasets": {"values": []},
    "mark": "bar",
    "encoding": {
        "x": {"field": "category", "type": "nominal"},
        "y": {"field": "value", "type": "quantitative"},
    },
}
data = {"values": [{"category": "A", "value": 12}, {"category": "B", "value": 21}]}

page = VegaChart(spec=spec, data=data, renderer="svg", actions=False)
app = serve(page, packages=[package], title="Vega-Lite chart")

data maps Vega dataset names to rows and signals maps signal names to values. Updating either property applies the change to the current view, preserving scroll position and chart interaction state. Set signal_listeners to the signal names that should produce vega-signal events; each event contains the signal's name and value in detail.

The bundled <vega-chart> custom element dispatches vega-ready after rendering, vega-update after applying data or signals, and vega-error when either operation fails. It also accepts serializable Vega-Embed options. Updating spec, options, renderer, or actions redraws the visualization and finalizes the previous view.

The element exposes its Vega view property for JavaScript code that needs the rest of the View API.

Theming

Chart defaults follow spaday's shell palette. Set a component token on the chart or any ancestor to theme Vega without changing its specification:

These are Vega configuration defaults. Colors declared by the specification or options.config still win. Python authors can discover the same mapping as spaday_vega.TOKENS and set a token with VegaChart(...).css(spa_vega_mark="#4c78a8").

Browser examples

• Open the chart example (source).

The browser example runs Python through Pyodide, so it needs no install or server. Each timer event travels from the browser to a Python model through Spaday and transports. Python returns three named datasets and a Vega signal, and each chart applies them to its existing view. Hovering a point sends a watched Vega signal back through Spaday and transports. The example includes native Vega and Vega-Lite specifications.

Run the examples locally

python -m pip install -e ".[examples]"
python -m spaday_vega.example

Open http://127.0.0.1:8028 for the example.