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Dashboard Builder

Version == 0.4.7

The dashboard-builder is a Python package designed to help you create interactive web dashboards with minimal effort, while still giving you full access to the underlining web framework supporting it - which is Flask. So whether you're looking to visualize datasets, create dynamic reports, or provide interactive analytics, this library streamlines the process, letting you focus on the data and logic, while it takes care of the presentation.

Our intended audience for this tool are python developers or data scientists that needs direct access to the web framework (e.g., Flask) because of large amounts of custom code or required functionality, but still want a simple way of creating dashboards, similar to Streamlit, Dash or Shiny - which make it harder to configure or customize the web framework. Flask is one of the most un-oppinionated web frameworks for python, which makes it a great choice.

Positioning of Dashboard Builder in the Data Visualization Ecosystem

In the vast landscape of data visualization tools, Dashboard Builder has carved out a unique and essential space for developers and data professionals. Dashboard Builder is for those who seek the balance between flexibility and ease-of-use, offering a middle-ground solution that doesn't compromise on power or versatility. Here's how it fits in:

  1. Starting From Scratch: Web Frameworks
    At one end of the spectrum, there are the barebone web frameworks like Flask, Django, or FastAPI. These frameworks provide enormous flexibility, allowing developers to build almost anything they envision. However, this often comes at the cost of starting from scratch. For many, the complexity of setting up, designing, and integrating multiple components is a hurdle, especially when the primary goal is to visualize and interact with data efficiently.

  2. High-level Visualization Tools: Tableau and Power BI
    On the opposite end, there are high-level visualization platforms like Tableau or Power BI. These tools empower users to create dashboards by simply dragging and dropping. But this ease of use can come with limitations. Custom visualizations or interactions might not be feasible, and these platforms can come with hefty price tags.

  3. Middle-Ground Tools: Shiny, Streamlit, Dash, and others
    Somewhere in between, tools like Shiny, Streamlit, Dash, and Gradio have emerged. They offer Python or R developers the ability to quickly create interactive web applications with minimal web development. However, they often abstract away too much of the underlying structure. This abstraction can limit developers from customizing or extending their apps in ways not natively supported by these platforms.

  4. Dashboard Builder: The Goldilocks Zone
    This is where Dashboard Builder shines. It occupies what we like to call the "Goldilocks Zone." It's not as raw and challenging as starting with pure web frameworks, yet it doesn't confine you within rigid structures like high-level tools. At the same time, it offers more control and flexibility than middle-ground tools. With Dashboard Builder, developers retain the ability to modify and customize components to their needs, integrating various visualization libraries and web components. Yet, they don't have to grapple with the foundational setup, making it easier and faster to get started.

Key Features:

Native Visualizations with Familiar Tools:

Dashboard Builder empowers users to craft visuals using the full functionality of industry-standard libraries like Matplotlib, Plotly, and Altair. This means no compromises, no curbed features—just pure, unadulterated visual storytelling as these libraries intended.

No coding for HTML, CSS, or JS

Once you've created your visualization, there's typically the daunting task of embedding it within a web interface, which requires wrangling with HTML, CSS, or even JavaScript. The dashboard builder removes this step, letting you focus solely on Python. With just your Python skills, you can craft a web-responsive, interactive, and visually appealing dashboard. But if you need to, you can still access the HTML, CSS, and JS to customize the dashboard to your needs.

Modern Styling with Tailwind:

Leveraging the power of Tailwind CSS, Dashboard Builder offers dynamic and mobile-responsive layouts that ensure your visuals look vibrant and engaging across all devices. From widescreen monitors to compact mobile views, your dashboards will always adapt gracefully and retain their modern aesthetic appeal.

Growing Component Library:

  • Input Elements:

    • Single select
    • Radio button
    • Slider
    • Free text

  • Output Elements:

    • Visualizations
      • Altair
      • Matplotlib
      • Plotly
    • Markdown
    • Free text
    • Images
    • Text
    • Markdown

  • Container Related Elements:

    • Column
    • Expander

  • Style Themes:

    • Default (light)
    • Dark
    • Pink
    • Blue
    • Red
    • Yellow
    • Green

Alpha Release

Dashboard Builder is currently in Alpha and is not yet ready for production purposes. We are working hard to finalize unit and E2E testing. We expect to have a production ready release by December 1, 2023. Stay tuned.

Installation

To install dashboard-builder, you can use pip:

With pip: 

pip install dashboard-builder

With poetry: 

poetry add dashboard-builder

Quick Start

After installation, you can quickly set up a basic dashboard:

app.py
from dashboard_builder import ComponentManager, DashboardOutput

# Your code to create a dashboard

For more detailed guides, usage examples, and API reference, navigate to the respective sections in the documentation.

Next Steps

  1. Getting Started: Learn the basics of setting up your first dashboard.
  2. Components: Dive deep into the various components and widgets available.
  3. Layouts & Templates: Understand how to customize and layout your dashboards.
  4. Advanced Topics: Dive deeper into more advanced functionalities and custom integrations.

Feel free to reach out for support or suggest features on our GitHub repository.