dash-prism 0.3.1

Prism: Powerful multi-panel workspace manager for Plotly Dash

Dash Prism

A multi-panel workspace manager for Plotly Dash applications.

Documentation: https://ludwigaj.github.io/dash-prism/ · PyPI: https://pypi.org/project/dash-prism/

What is Dash Prism?

Dash Prism provides a unified workspace where multiple Dash layouts coexist as tabs within resizable, splittable panels. Users arrange their workspace via drag-and-drop while developers focus on building content.

The Problem

Building dashboards with Plotly Dash typically means:

• Fragmented applications - Each dashboard lives in isolation, requiring users to switch between browser tabs or navigate complex menus.
• Repetitive UI work - Developers spend time on layout scaffolding, tab systems, and panel management instead of business logic.
• One-size-fits-all layouts - Users get a fixed arrangement that may not match their workflow.
• No personalization - Workspaces reset on every visit; users cannot save their preferred view.

The Solution

Dash Prism addresses these issues by providing:

• Unified workspace - Register any number of layouts; users open them as tabs in a single interface.
• User-driven design - Drag tabs to split panels, resize areas, and rearrange freely. Developers define content; users define structure.
• Persistence - Workspace state saves to localStorage, sessionStorage, or memory so users return to exactly where they left off.
• Minimal boilerplate - A decorator-based API keeps layout registration concise and readable.

Features

• User-Driven Layout - Users style tabs with colors and icons, reorder them freely, and drag to panel edges to split the view. You create the content; they make the dashboard.
• Favorites & Search - Find layouts instantly with the integrated search bar. Mark frequently-used ones as favorites to pin them at the top.
• On-Demand Loading - Tab content loads dynamically when selected, keeping initial page load fast even with many registered layouts.
• Parameterized Layouts - Capture user options before loading a layout, minimizing server round-trips and delivering exactly what the user wants.
• Custom Actions - Add status bar buttons that trigger Dash callbacks for saving workspaces, exporting data, or any custom functionality.
• Persistence & Workspace State - State saves to localStorage, sessionStorage, or memory. Use readWorkspace and updateWorkspace for programmatic backup, restore, or team sharing.
• Context Menus - Right-click tabs to rename, duplicate, lock, style, or generate a shareable link to send a specific tab to someone else.
• Keyboard Shortcuts - Full keyboard navigation: new tab, close, rename, undo close, switch tabs, and more.
• Error Resilience - Errors are captured at the tab level, guarding against crashes that would otherwise take down the workspace. Retry with one click.

Installation

Requirements: Python 3.10+, Dash 3.1.1+

pip install dash-prism

Quick Start

import dash
from dash import html
import dash_prism

app = dash.Dash(__name__)

@dash_prism.register_layout(id='home', name='Home')
def home():
    return html.Div('Welcome to Dash Prism')

@dash_prism.register_layout(id='analytics', name='Analytics')
def analytics():
    return html.Div('Analytics content here')

app.layout = html.Div([
    dash_prism.Prism(id='workspace', persistence=True)
])

dash_prism.init('workspace', app)

if __name__ == '__main__':
    app.run(debug=True)

Development

Setup

# Clone and enter the project
git clone https://github.com/LudwigAJ/dash-prism.git
cd dash-prism

# Create a virtual environment
python -m venv .venv
source .venv/bin/activate  # Windows: .venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt
npm install

# Build
npm run build

Using Just

If you have just installed:

just install   # Install Python and npm dependencies
just build     # Build the package
just test      # Run tests

Contributing

Contributions are welcome. Please:

1. Fork the repository.
2. Create a feature branch.
3. Write tests for new functionality.
4. Ensure all tests pass (pytest).
5. Submit a pull request.

See the Contributing Guide in the documentation for more details.

License

Apache License 2.0. See LICENSE for details.