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✨ panel-mosaic

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Interactive, DuckDB-powered Mosaic visualizations for Panel.

Build linked, browser-interactive charts without embedding an entire dataset in the page. Mosaic sends SQL to DuckDB and returns only the results each view needs.

Why panel-mosaic?

  • Declarative charts: Render Mosaic and vgplot specifications directly in a Panel app.
  • DuckDB pushdown: Keep large tables in DuckDB; only query results travel to the browser.
  • Linked exploration: Coordinate multiple charts with selections and cross-filtering.

Installation

The PyPI distribution is named panel-mosaic-viz:

pip install panel-mosaic-viz

Quick start

Create app.py with a small DuckDB table and a stacked bar chart:

import duckdb
import panel as pn

from panel_mosaic import Mosaic

pn.extension(sizing_mode="stretch_width")

con = duckdb.connect()
con.execute("""
    CREATE TABLE monthly_revenue AS
    SELECT * FROM (
        VALUES
            ('Jan', 'North', 48), ('Jan', 'Central', 39), ('Jan', 'South', 42),
            ('Feb', 'North', 55), ('Feb', 'Central', 45), ('Feb', 'South', 49),
            ('Mar', 'North', 46), ('Mar', 'Central', 40), ('Mar', 'South', 44),
            ('Apr', 'North', 61), ('Apr', 'Central', 48), ('Apr', 'South', 52),
            ('May', 'North', 65), ('May', 'Central', 52), ('May', 'South', 56),
            ('Jun', 'North', 58), ('Jun', 'Central', 47), ('Jun', 'South', 50),
            ('Jul', 'North', 72), ('Jul', 'Central', 55), ('Jul', 'South', 58),
            ('Aug', 'North', 66), ('Aug', 'Central', 52), ('Aug', 'South', 54),
            ('Sep', 'North', 79), ('Sep', 'Central', 60), ('Sep', 'South', 64),
            ('Oct', 'North', 89), ('Oct', 'Central', 69), ('Oct', 'South', 70),
            ('Nov', 'North', 74), ('Nov', 'Central', 58), ('Nov', 'South', 60),
            ('Dec', 'North', 85), ('Dec', 'Central', 66), ('Dec', 'South', 69)
    ) AS t(month, region, revenue)
""")

spec = {
    "width": 900,
    "height": 480,
    "marginLeft": 72,
    "marginBottom": 48,
    "xLabel": "Month",
    "yLabel": "Revenue (USD thousands)",
    "yGrid": "#e5e7eb",
    "colorScheme": "Tableau10",
    "plot": [{
        "mark": "barY",
        "data": {"from": "monthly_revenue"},
        "x": "month",
        "y": "revenue",
        "fill": "region",
        "stroke": "white",
        "strokeWidth": 1,
    }],
}

pn.Column(
    "# Monthly revenue dashboard",
    "Explore regional revenue with a Mosaic chart backed by DuckDB.",
    Mosaic(spec, con=con),
).servable()

Run the app:

panel serve app.py --show

Monthly revenue chart rendered with panel-mosaic

How it works

Mosaic is a Panel JSComponent. It renders the declarative chart specification in the browser and services Mosaic's SQL requests through its DuckDB connection. You can either pass an existing DuckDB connection with con= or register in-memory frames with data={"table_name": dataframe}.

See the documentation for API details and more examples.

Development

git clone https://github.com/panel-extensions/panel-mosaic
cd panel-mosaic

For a simple setup use uv:

uv venv
source .venv/bin/activate # on linux. Similar commands for windows and osx
uv pip install -e .[dev]
pre-commit run install
pytest tests

For the full Github Actions setup use pixi:

pixi run pre-commit-install
pixi run postinstall
pixi run test

This repository is based on copier-template-panel-extension (you can create your own Panel extension with it)!

To update to the latest template version run:

pixi exec --spec copier --spec ruamel.yaml -- copier update --defaults --trust

Note: copier will show Conflict for files with manual changes during an update. This is normal. As long as there are no merge conflict markers, all patches applied cleanly.

❤️ Contributing

Contributions are welcome! Please follow these steps to contribute:

  1. Fork the repository.
  2. Create a new branch: git checkout -b feature/YourFeature.
  3. Make your changes and commit them: git commit -m 'Add some feature'.
  4. Push to the branch: git push origin feature/YourFeature.
  5. Open a pull request.

Please ensure your code adheres to the project's coding standards and passes all tests.

Metadata

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