Introduction

Dash File Cache is a Dash extension library.

Utilities for providing convenient methods to serve cached data in Plotly-Dash or Flask.

The data cache enables the following features:

Load a server-side file dynamically and send the file to users (the frontend).
Support in-memory files (like io.BytesIO()) or on-disk files (specified by a path).
Support different kinds of cache (single-thread, multi-processing, or file-based).
A customized component helping the dashboard trigger a download event from the server side.

The minimal example

The following codes show a minimal example of this package

from typing import Optional

import io

import dash
from dash import html
from dash import Input, Output

from dash_file_cache import ServiceData, CachePlain

app = dash.Dash("demo")
service = ServiceData(CachePlain(1))
service.serve(app)

app.layout = html.Div(
    (
        html.Div(
            html.P(
                (
                    html.Span("Get Image:", style={"paddingRight": "0.5rem"}),
                    html.Button(id="btn", children="Image"),
                )
            )
        ),
        html.Div((html.P("Cache address:"), html.P(id="addr"))),
        html.Div((html.P("Cached Image:"), html.Img(id="cache"))),
    ),
)


@app.callback(
    Output("addr", "children"),
    Input("btn", "n_clicks"),
    prevent_initial_call=True,
)
def click_get_image(
    n_clicks: Optional[int],
):
    if not n_clicks:
        return dash.no_update

    addr = service.register(
        io.StringIO(
            R'<svg height="100" width="100" xmlns="http://www.w3.org/2000/svg">'
            R'<circle r="45" cx="50" cy="50" fill="red" /></svg>'
        ),
        content_type="image/svg+xml",
        mime_type="image/svg+xml",
        one_time_service=True,
    )
    return addr


@app.callback(
    Output("cache", "src"),
    Input("addr", "children"),
    prevent_initial_call=True,
)
def update_cache(addr):
    if not addr:
        return dash.no_update
    return addr


if __name__ == "__main__":
    app.run(host="127.0.0.1", port="8080", debug=True)