What data sources can I connect to?

Lumen supports a wide variety of sources including PostgreSQL, DuckDB, SQLite, CSV, Parquet, Excel, and REST API endpoints.

Is it possible to deploy these dashboards to a production server?

Yes, Lumen dashboards can be served using the 'lumen serve' command or deployed via Docker and standard Python web servers using Panel.

Do I need to know Python to use Lumen Dashboards?

No, Lumen is a declarative framework. While it is built on Python, you define your dashboards using YAML configuration files, making it accessible for those who prefer a no-code approach.

How does Lumen differ from Panel?

Panel is an imperative framework for building custom web apps in Python. Lumen is built on top of Panel but provides a higher-level, declarative YAML interface specifically for standard data dashboards.

Can I perform data transformations within the dashboard?

Yes, Lumen pipelines allow you to define transforms like columns selection, row queries, aggregation, and custom SQL directly in your YAML specification.

Lumen Data Dashboards

Name: Lumen Data Dashboards
Author: robertpelloni

byrobertpelloni

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分析与监控

Builds interactive, no-code data exploration dashboards using declarative YAML specifications for rapid prototyping and deployment.

关于

This skill enables the creation of professional-grade data dashboards and analytics applications without the need for complex imperative coding. By leveraging the Lumen framework, it facilitates the definition of end-to-end data pipelines—spanning multi-source connections, data transforms, and interactive visualizations—all within structured YAML configurations. It is particularly effective for bridging the gap between data engineering and business intelligence, allowing for rapid prototyping, self-service analytics, and the maintenance of reproducible dashboard specifications across diverse environments like PostgreSQL, DuckDB, and REST APIs.

主要功能

Multi-source integration including SQL, Parquet, and REST APIs
Automated data pipelines with filtering and aggregation transforms
3 GitHub stars
Declarative YAML-based dashboard configuration
Extensive visualization library powered by HoloViews and hvPlot
Interactive cross-filtering and responsive UI layouts

使用场景

Building real-time KPI monitors connected to production databases like PostgreSQL
Prototyping internal data exploration tools for stakeholders without writing Python
Creating reproducible visualization templates for standardized reporting across teams

关于

主要功能

Multi-source integration including SQL, Parquet, and REST APIs
Automated data pipelines with filtering and aggregation transforms
3 GitHub stars
Declarative YAML-based dashboard configuration
Extensive visualization library powered by HoloViews and hvPlot
Interactive cross-filtering and responsive UI layouts

使用场景

Building real-time KPI monitors connected to production databases like PostgreSQL
Prototyping internal data exploration tools for stakeholders without writing Python
Creating reproducible visualization templates for standardized reporting across teams