chartlets 0.0.15

Backend for server-configured charts powered by Vega Altair.

dashi

Dashi is a framework for server-configured panels.

Run demo server

mamba env create
conda activate dashi
python -m dashipy.server 

How to use the framework

1. Implement the possible contributions

Implement the application-specific contributions that users can add to their extensions.

As an example, see panel.py of the demo:

from dashipy import Contribution


class Panel(Contribution):
    """Panel contribution"""

    def __init__(self, name: str, title: str | None = None):
        super().__init__(name, title=title)

2. Define the contributions points

Define the possible contribution points in your application.

As an example, see server.py of the demo:

from dashipy import Extension
from dashipy.demo.contribs import Panel

Extension.add_contrib_point("panels", Panel)

3. Load the extensions

Load the extensions that augment your application.

As an example, see server.py of the demo:

from dashipy import ExtensionContext

ext_ctx = ExtensionContext.load(app_ctx, extension_refs)

4. Publish the extensions

Implement the Dashi API in your application-specific webserver using the controller implementations in dashipy.controllers.

As an example, see server.py of the demo.

5. Consume the extensions

Use JavaScript package dashi in your frontend to implement the contribution lifecycle in your React application.

As an example, see the demo application.