ipydagred3
ipywidgets wrapper around dagre-d3
Decision gist · record as of 2026-08-14
Yes, if you work in JupyterLab and need to visualize or interact with DAGs. The package is actively maintained, has no known vulnerabilities, installs with minimal friction, and carries a permissive Apache License Version 2.0. The last release was 2023-10-31 but recent commit activity on 2026-08-01 indicates ongoing maintenance; verify compatibility with your JupyterLab version before production use.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Installation is straightforward via pip with low friction.
- The package is actively maintained as of 2026-08-01, with recent commit history and no archived status.
- It depends only on ipykernel and ipywidgets, both stable Jupyter ecosystem libraries.
License · maintenance · safety
permissive license (permissive) — Licensed under Apache License Version 2.0 (permissive), which allows free use, modification, and distribution with minimal restrictions—suitable for both open-source and commercial projects as long as license and copyright notices are retained.
last release 2023-10-31 (1018 days) · last repo commit 2026-08-01 · 85 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 423,990 downloads/mo, #6,767 on PyPI
Alternatives
Verify before relying
pip install ipydagred3
from ipydagred3 import Graph
graph = Graph()
graph.add_node('node1', label='Task 1')
graph.add_node('node2', label='Task 2')
graph.add_edge('node1', 'node2')
graph- Whether the package works with the latest JupyterLab versions beyond what the classifiers indicate
- Performance characteristics when rendering large or complex DAGs
- Stability of click event handling and tooltip features in production use
What it is and what it does
ipydagred3 wraps the dagre-d3 graph layout engine as an interactive ipywidgets component for Jupyter notebooks and JupyterLab. It lets you create, modify, and visualize directed acyclic graphs directly from Python code, with support for customizing node colors, shapes, and tooltips. The widget emits click events when users interact with nodes or edges, making it suitable for building interactive graph inspection tools and exploratory workflows within notebooks.
The package is designed for developers working in Jupyter environments who need to visualize DAG structures—such as workflow dependencies, computational graphs, or data lineage—without leaving the notebook. It requires only ipykernel and ipywidgets, both standard Jupyter dependencies, and supports Python 3.8 through 3.12.
Use it for
- Visualizing workflow or task dependency graphs in a notebook for debugging or documentation
- Building interactive node inspectors that respond to clicks on graph elements
- Exploring data lineage or computational DAGs with dynamic node and edge styling
- Prototyping graph-based applications where users need to see and interact with DAG structure
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you work in JupyterLab and need to visualize or interact with DAGs.
The package is actively maintained, has no known vulnerabilities, installs with minimal friction, and carries a permissive Apache License Version 2.0. The last release was 2023-10-31 but recent commit activity on 2026-08-01 indicates ongoing maintenance; verify compatibility with your JupyterLab version before production use.
Install
ipydagred3 on PyPI
Before you install
Installation is straightforward via pip with low friction. The package is actively maintained as of 2026-08-01, with recent commit history and no archived status. It depends only on ipykernel and ipywidgets, both stable Jupyter ecosystem libraries.
License in practice
Licensed under Apache License Version 2.0 (permissive), which allows free use, modification, and distribution with minimal restrictions—suitable for both open-source and commercial projects as long as license and copyright notices are retained.
Quickstart
pip install ipydagred3
from ipydagred3 import Graph
graph = Graph()
graph.add_node('node1', label='Task 1')
graph.add_node('node2', label='Task 2')
graph.add_edge('node1', 'node2')
graphVerify before relying
- Whether the package works with the latest JupyterLab versions beyond what the classifiers indicate
- Performance characteristics when rendering large or complex DAGs
- Stability of click event handling and tooltip features in production use
Package facts
| License | permissive license permissive |
| Python support | Supports the current Python release >=3.8 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 2 packagesipykernelipywidgets |
| Maintenance | Actively maintained 1,018 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 423,990 / month, #6,767 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 4 - BetaFramework :: JupyterFramework :: Jupyter :: JupyterLabLicense :: OSI Approved :: Apache Software LicenseProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.8Programming Language :: Python :: 3.9 |
Evidence: ipydagred3-0.4.1-py3-none-any.whl
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