lutopia

Tool-agnostic LUT and colormap management for Python.

Lutopia treats every palette — smooth gradient or legacy 256-step table — as a single unified continuous function. One API, zero fragmentation across visualization ecosystems.

import lutopia as lt

# Matplotlib
from matplotlib.colors import ListedColormap
cmap = ListedColormap(lt.viridis.plt)

# Seaborn
sns.heatmap(data, cmap=lt.viridis.sns)

# Plotly
fig.update_traces(colorscale=lt.viridis.plotly)

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Features

• 297 palettes out of the box — matplotlib's full catalog + the entire colorcet scientific collection
• Unified engine — smooth gradients and legacy step-function LUTs share one interface
• Zero visualization dependencies — runtime package requires only numpy and scipy
• Native consumer outputs — .plt, .mpl, .sns, .plotly return exactly what each library expects, no adapters needed
• Interactive palette picker — uvx lutopia opens a live GUI browser with one-click code generation
• src layout, uv_build backend — modern packaging, ships a clean wheel

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Installation

pip install lutopia
# or
uv add lutopia

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Quick Start

import lutopia as lt

# List all available palettes
print(dir(lt))  # ['accent', 'afmhot', 'autumn', ..., 'viridis', ...]

# Sample raw float values (N × 3 array, values in [0, 1])
arr = lt.viridis.sample(256)   # numpy array, shape (256, 3)

# Get hex strings
hexes = lt.plasma.to_hex_list(64)  # ['#0d0887', '#2d0594', ...]

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Consumer Properties

Every palette exposes three ready-to-use consumer properties. No third-party imports are required by the library itself.

Matplotlib

from matplotlib.colors import ListedColormap
import matplotlib.pyplot as plt
import lutopia as lt

cmap = ListedColormap(lt.inferno.plt)
plt.imshow(data, cmap=cmap)
plt.colorbar()

.plt / .mpl / .matplotlib all return the same (256, 3) float64 NumPy array that ListedColormap and LinearSegmentedColormap accept directly.

Seaborn

import seaborn as sns
import lutopia as lt

sns.heatmap(data, cmap=lt.magma.sns)

.sns / .seaborn return a list of 256 hex strings, which Seaborn accepts for both palette= and cmap= arguments.

Plotly

import plotly.graph_objects as go
import lutopia as lt

fig = go.Figure(go.Heatmap(z=data, colorscale=lt.turbo.plotly))

.plotly returns a native Plotly colorscale — a list of [fraction, "#rrggbb"] pairs spanning [0.0, 1.0].

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Palette Browser

The interactive palette picker is available as an ephemeral tool — no install needed:

uvx lutopia
# or, if already installed:
lutopia

A tkinter window opens showing all 297 palettes as color swatches. Click any palette to open a code snippet dialog:

• Choose your target ecosystem (Matplotlib, Seaborn, Plotly, or Raw Hex)
• Copy the generated snippet directly to your clipboard

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Available Palettes

Lutopia ships with palettes sourced from:

Source	Count	Examples
Matplotlib	~90	viridis, plasma, inferno, magma, cividis, jet, hot, coolwarm, spectral, tab10
Colorcet	~200	fire, rainbow4, bmy, bgyw, isolum, gouldian, kbc, dimgray

All palettes are available immediately after install — no scraping, no network calls.

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How It Works

All palettes are stored as compact JSON anchor files in lutopia/palettes/. A continuous UnifiedPalette engine evaluates them on demand:

• Linear interpolation for smooth gradient maps (e.g. viridis, plasma)
• Nearest-neighbor / step for discrete legacy tables (e.g. ImageJ .lut files)

{
  "name": "viridis",
  "interpolation": "linear",
  "anchors": [
    [0.0,   [68, 1, 84]],
    [0.5,   [33, 145, 140]],
    [1.0,   [253, 231, 37]]
  ]
}

Palettes are loaded lazily on first access and cached for the lifetime of the interpreter session.

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Development

Setup

git clone https://github.com/bryanbarcelona/lutopia.git
cd lutopia
uv sync

Tooling

uv run ruff check .          # lint
uv run ruff format .         # format
uv run ty check src/lutopia  # type check
uv run pytest                # tests

Adding Palettes

From matplotlib / colorcet:

uv run python scripts/scrape_ecosystems.py

Reads upstream colormap libraries, reduces continuous maps to sparse anchor points (max error < 1/255), and writes JSON assets to src/lutopia/palettes/. Run with --overwrite to force regeneration.

From a binary ImageJ / Fiji .lut file:

uv run python scripts/parse_legacy_lut.py path/to/fire.lut [name]

Parses the standard 768-byte RGB block and writes a step-interpolation JSON asset.

After adding palettes, commit the new JSON files and they will be included in the next release.

Releasing

Releases are fully automated via CI. Every merge to main triggers:

1. Commitizen bumps the version and generates a changelog entry
2. uv build produces the wheel and sdist
3. uv publish pushes to PyPI via trusted publishing (OIDC, no API keys)
4. A GitHub Release is created and tagged

Commit messages must follow Conventional Commits:

cz commit

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License

MIT