just-dashboard is an MIT-licensed TypeScript project that renders dashboards from YAML or JSON files, built for developers, analysts and data practitioners who want charts and layout without writing front-end code.

What it is

just-dashboard treats a dashboard as a plain text document. A file holds a named board, written as dashboard "Food":, followed by a tree of layout and content nodes such as - 3 columns:, - rows:, - h1 text:, - h2 text: and - h3 text:. Charts attach to that tree as nodes, for example - pie chart: { "columns": [ ["Protein", 5], ["Sugar", 10] ] }, where each entry pairs a label with a value. The project is written in TypeScript and sits in the D3 ecosystem, and its topics list d3, d3js and data-visualization. Input arrives as YAML or JSON, and the README example renders the macronutrient split of bananas, tofu and peanut butter into a three-column comparison.

The problem it solves is the distance between a data file and a rendered chart. Building that same board by hand means writing layout markup and chart code on top of a visualization library, then repeating the work whenever the numbers move. just-dashboard collapses this into a document: change the values in the YAML or JSON file and the board follows. It replaces the hand-written dashboard code you would otherwise maintain in the D3 stack, and it keeps the definition reviewable as text in version control.

Key capabilities

• Named dashboards declared inside a single file, as in dashboard "Food":.
• Layout control through - 3 columns: and - rows: blocks.
• Text nodes at heading levels, using - h1 text:, - h2 text: and - h3 text:.
• Chart nodes such as - pie chart:, which take a "columns" array of [label, value] pairs.
• Two input formats, YAML and JSON, chosen by file extension.
• Hosting from a public GitHub gist: a file named dashboard.yml or dashboard.json served at http://bottoml.in/e/{Github username}/{Gist ID}.
• A self-hosted path, since the README states you can roll your own backend.

Who uses it and how

• Developers who keep numbers in a repository and want the board committed next to the code that produces them.
• Analysts who need a shareable chart link without deploying infrastructure, using a public gist plus the bottoml.in/e/... address.
• Data engineers and data scientists, reflected in the data-engineering, data-science and big-data topics, producing quick reports without a full business intelligence suite.
• Teams with confidentiality constraints that run their own backend rather than publishing a public gist.

Getting started

The README links dedicated Getting started and Chart types pages. The shortest route is to create a public GitHub gist containing dashboard.yml or dashboard.json and open it at http://bottoml.in/e/{Github username}/{Gist ID}; the README supplies a working example gist.

How it compares

The facts list no paid products that this project replaces, and they name no sibling tools in the same space. In this registry it stands alone in the Data & Analytics / Business Intelligence & Reporting category, so no head-to-head comparison is offered here.

When to use it — and when not to

Choose it when the definition of a board belongs in version control as text and gist hosting is acceptable. A self-hoster must run a backend, because the convenient hosted route depends on the third-party bottoml.in service and a public gist, so confidential data should not travel that path. The README excerpt is thin, mostly badges plus one example, so anyone expecting a packaged install command, access control or a documented deployment and storage story should read the linked documentation first; the last recorded push is 2026-02-21 and 13 issues are open.

dashboard "Food":
  - h1 text: Food
  - h2 text: By caloric content
  - 3 columns:
    - rows:
      - h3 text: Bananas
      - pie chart: {
          "columns": [
            ["Protein", 5], ["Sugar", 10], ["Other carbs", 40], ["Fat", 1]
          ]
        }
    - rows:
      - h3 text: Tofu
      - pie chart: {
          "columns": [
            ["Protein", 30], ["Sugar", 0], ["Other carbs", 40], ["Fat", 3]
          ]
        }
    - rows:
      - h3 text: Peanut butter
      - pie chart: {
          "columns": [
            ["Protein", 20], ["Sugar", 2], ["Other carbs", 20], ["Fat", 50]
          ]
}