Maxplotlib

A clean, expressive wrapper around Matplotlib, Plotly, plotext, and tikzfigure for producing publication-quality figures with minimal boilerplate. Swap backends without rewriting your data — render the same canvas as a crisp PNG, an interactive Plotly chart, a terminal-native plotext figure, or camera-ready TikZ code for LaTeX.

Install

pip install maxplotlibx

Showcase

Quickstart

import numpy as np
from maxplotlib import Canvas

x = np.linspace(0, 2 * np.pi, 200)
y = np.sin(x)

canvas, ax = Canvas.subplots()
ax.plot(x, y)

Plot the figure with the default (matplotlib) backend:

canvas.show()

Render the same line graph directly in the terminal with the plotext backend:

terminal_fig = canvas.plot(backend="plotext")
print(terminal_fig.build(keep_colors=False))

Or plot with the TikZ backend:

canvas.show(backend="tikzfigure")

Terminal backend

The plotext backend is designed for terminal-first workflows. It currently supports line plots, scatter plots, bars, filled regions, error bars, reference lines, text/annotations, labels/titles, log axes, layers, matrix-style imshow() rendering, common patches, and multi-subplot canvases.

x = np.linspace(1, 10, 40)

canvas, ax = Canvas.subplots()
ax.plot(x, np.sqrt(x), color="cyan", label="sqrt(x)")
ax.errorbar(x[::8], np.sqrt(x[::8]), yerr=0.15, color="yellow", label="samples")
ax.set_title("Terminal plot")
ax.set_xlabel("x")
ax.set_ylabel("y")
ax.set_xscale("log")
ax.set_legend(True)

canvas.show(backend="plotext")

Examples

Runnable example scripts live in examples/:

python examples/plotly_backend_basic.py
python examples/plotly_backend_parity.py

Layers

x = np.linspace(0, 2 * np.pi, 200)

canvas, ax = Canvas.subplots(width="10cm", ratio=0.55)

ax.plot(x, np.sin(x), color="steelblue", label=r"$\sin(x)$", layer=0)
ax.plot(x, np.cos(x), color="tomato", label=r"$\cos(x)$", layer=1)
ax.plot(
    x,
    np.sin(x) * np.cos(x),
    color="seagreen",
    label=r"$\sin(x)\cos(x)$",
    linestyle="dashed",
    layer=2,
)

ax.set_xlabel("x")
ax.set_legend(True)

Show layer 0 only, then layers 0 and 1, then everything:

canvas.show(layers=[0])

Show all layers:

canvas.show()