HiPlot - High dimensional Interactive Plotting

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Community-maintained fork: This is a community-maintained fork of Facebook Research's HiPlot, which has been archived. We aim to keep the project alive with bug fixes, security updates, and new features.

HiPlot is a lightweight interactive visualization tool to help AI researchers discover correlations and patterns in high-dimensional data using parallel plots and other graphical ways to represent information.

Try a demo now with sweep data or upload your CSV or

There are several modes to HiPlot:

As a web-server (if your data is a CSV for instance)
In a jupyter notebook (to visualize python data), or in Streamlit apps
In CLI to render standalone HTML

Quick Start

# Render a CSV to interactive HTML (no install needed)
uvx hiplot-mm data.csv > output.html

# Or start an interactive server
uvx --from 'hiplot-mm[server]' hiplot --port 8765

Installation

# Core package (HTML export, CLI rendering)
pip install hiplot-mm

# With Jupyter notebook support
pip install hiplot-mm[notebook]

# With web server support (hiplot command)
pip install hiplot-mm[server]

# With Streamlit support
pip install hiplot-mm[streamlit]

# Everything
pip install hiplot-mm[all]

If you have a Jupyter notebook, you can get started with something as simple as:

import hiplot as hip
data = [{'dropout':0.1, 'lr': 0.001, 'loss': 10.0, 'optimizer': 'SGD'},
        {'dropout':0.15, 'lr': 0.01, 'loss': 3.5, 'optimizer': 'Adam'},
        {'dropout':0.3, 'lr': 0.1, 'loss': 4.5, 'optimizer': 'Adam'}]
hip.Experiment.from_iterable(data).display()

See the live result

Result

Development

To build from source:

# Install dependencies
bun install
uv sync --all-extras

# Build JavaScript bundles
bun run build

# Build Python package
uv build

# Or use the all-in-one build script
./build.sh

Output directories:

npm-dist/ - NPM package artifacts
dist/ - Python wheel and sdist
hiplot/static/built/ - JS bundle included in Python package

Run the dev server:

uv run --extra server hiplot --port 8765

Citing

@misc{hiplot,
    author = {Haziza, D. and Rapin, J. and Synnaeve, G.},
    title = {{Hiplot, interactive high-dimensionality plots}},
    year = {2020},
    publisher = {GitHub},
    journal = {GitHub repository},
    howpublished = {\url{https://github.com/facebookresearch/hiplot}},
}

Credits

Inspired by and based on code from Kai Chang, Mike Bostock and Jason Davies.

External contributors (please add your name when you submit your first pull request):

License

HiPlot is MIT licensed, as found in the LICENSE file.

Metadata

Release files for hiplot-mm 0.0.3

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for hiplot-mm 0.0.3
File	Size	Uploaded
hiplot_mm-0.0.3.tar.gz	893.2 kB	Feb 3, 2026	Details

Built distribution (wheel)

Table of built distributions (wheels) for hiplot-mm 0.0.3
File	Interpreter	ABI	Platform	Reset
hiplot_mm-0.0.3-py3-none-any.whl 903.2 kB Feb 3, 2026	Python 3	none	any	Details

Total release size: 1.8 MB

Release files / hiplot_mm-0.0.3.tar.gz

Download URL	hiplot_mm-0.0.3.tar.gz
Size	893.2 kB
Tags	Source
SHA-256 checksum How to use checksums	`3a304afb2492b643798635b03ef435b7075b80b550c7c3aa81b93b9e4fea0564`
BLAKE2b-256 checksum How to use checksums	`00591951f570294f60602bea32ca3fa992bea571184683b7995711e116520b9c`
Upload date	Feb 3, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/6.1.0 CPython/3.13.7`

Provenance

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Identity

Publishing platform: GitHub Actions
Publishing repository: github.com/mindthemath/hiplot
Publishing commit: github.com/mindthemath/hiplot/tree/eb450ecf28bb086d85dcce814a9a9a03c5311ea0

Workflow

Publishing configuration: github.com/mindthemath/hiplot/blob/eb450ecf28bb086d85dcce814a9a9a03c5311ea0/.github/workflows/release.yml
Publishing logs: github.com/mindthemath/hiplot/actions/runs/21647358719/attempts/1

Artifact

Subject: hiplot_mm-0.0.3.tar.gz
SHA-256 checksum: 3a304afb2492b643798635b03ef435b7075b80b550c7c3aa81b93b9e4fea0564 Verifying attestations

Release files / hiplot_mm-0.0.3-py3-none-any.whl

Download URL	hiplot_mm-0.0.3-py3-none-any.whl
Size	903.2 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`4a9f9090c5461f96acff3570117cb602ad946b93c5916127843290e52f0900ba`
BLAKE2b-256 checksum How to use checksums	`d5fe32feb5097fc00b8d12896f83dca040407d1e9e48b312f713913f56ca4c46`
Upload date	Feb 3, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/6.1.0 CPython/3.13.7`

Provenance

Identity

Publishing platform: GitHub Actions
Publishing repository: github.com/mindthemath/hiplot
Publishing commit: github.com/mindthemath/hiplot/tree/eb450ecf28bb086d85dcce814a9a9a03c5311ea0

Workflow

Publishing configuration: github.com/mindthemath/hiplot/blob/eb450ecf28bb086d85dcce814a9a9a03c5311ea0/.github/workflows/release.yml
Publishing logs: github.com/mindthemath/hiplot/actions/runs/21647358719/attempts/1

Artifact

Subject: hiplot_mm-0.0.3-py3-none-any.whl
SHA-256 checksum: 4a9f9090c5461f96acff3570117cb602ad946b93c5916127843290e52f0900ba Verifying attestations