A Python wrapper for gum.jsx, a language for creating visualizations using a React-like JSX dialect that evaluates to SVG. Designed for general graphics, plots, graphs, and network diagrams.

Head to compendiumlabs.ai/gum for a live demo and documentation on the underlying gum.jsx library.

Installation

pip install gum-jsx

Requires Node.js to be installed for the gum.js backend.

Usage

Create visualizations using Python syntax that generates JSX:

import gum
from gum import C
from gum.gen import Plot, SymLine

# create a simple sine wave plot
plot = Plot(
    SymLine(fy=C.sin, stroke=C.blue, stroke_width=2),
    xlim=(0, 2*C.pi), ylim=(-1, 1), grid=True, margin=0.2, aspect=2,
)

# display in terminal (requires chafa)
gum.display(plot) # or just `plot` if you're in IPython or Jupyter

# or get the SVG string
svg = gum.evaluate(plot)

# or get the JSX code
jsx = str(plot)

If you're in IPython or Jupyter, you don't even need to call display. Just type plot and it will automatically display the visualization inline.

Pandas Integration

Plot DataFrames directly with high-level functions:

import pandas as pd
import numpy as np
from gum import lines, points, bars

# line plot from DataFrame
th = np.linspace(0, 2*np.pi, 100)
df = pd.DataFrame({ 'sin': np.sin(th), 'cos': np.cos(th) })
lines(df, margin=0.15)

# bar chart from Series
bars(pd.Series({'A': 3, 'B': 8, 'C': 5}))

Symbolic Expressions

Use C for constants and V for variables:

from gum import C, V
from gum.gen import Plot, SymLine, SymPoints

# C references gum.js constants and functions
C.sin, C.cos, C.pi, C.blue, C.red

# build symbolic expressions
decay = lambda x: C.exp(-x/2) * C.sin(3*x)

# V creates named variables bound to data
theta = V.theta(np.linspace(0, 2*np.pi, 100))

CLI

Display gum visualizations directly in the terminal using chafa. Requires a terminal with image support, such as ghostty.

# run a built-in demo
python -m gum -d plot -s 50

# pipe JSX code
cat input.jsx | python -m gum

CLI options:

Option	Description	Default
-d, --demo <name>	Run a named demo	-
-s, --size <size>	Terminal display size	50
-t, --theme <theme>	Theme: light or dark	dark

Available demos: plot, barplot, network, symline, grid, stack, text, and more (see gum/dem.py).

Jupyter Support

gum.py automatically renders SVG in IPython console and Jupyter notebooks:

from gum import Plot, SymLine, C

# this will display inline in Jupyter
Plot(
    SymLine(fy=C.sin),
    xlim=(0, 2*C.pi), ylim=(-1, 1), grid=True,
)

Components

gum.py wraps all gum.js components. Key ones include:

Layout: Box, Frame, Stack, HStack, VStack, Grid, Points

Shapes: Rect, Ellipse, Circle, Line, Shape, Spline

Text: Text, TextFrame, Latex, Equation

Plotting: Plot, Graph, Axis, HAxis, VAxis, BarPlot

Symbolic: SymLine, SymPoints, SymShape, SymSpline, SymFill, SymField

Network: Node, Edge, Network, Arrow

See the gum.js documentation for detailed component reference.