glyphx 1.2.9

"A next-gen Python plotting library with SVG-first rendering, interactivity, themes, and clean defaults — better than matplotlib.pyplot"

GlyphX

A Better, Faster, and Simpler Python Visualization Library

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GlyphX is a modern alternative to matplotlib.pyplot with interactive, SVG-based charts that automatically display in:

• Jupyter notebooks
• CLI environments
• IDEs

It provides simplicity, high-quality rendering, built-in tooltips, zoom/pan, and export options — without ever needing plt.show().

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Features

Feature	GlyphX	Matplotlib
Auto-display	✅	❌
Interactive tooltips	✅	❌
Zoom / pan (in browser)	✅	❌
Built-in export buttons	✅ SVG/PNG/JPG	❌
Multi-plot grid layout	✅	✅
Seaborn-style charts	✅ (lmplot, pairplot, etc.)	Partial
Hover highlighting	✅	❌
Colorblind-friendly mode	✅	❌
Shared axes support	✅	✅
Font & theme customization	✅	✅

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Installation

pip install glyphx

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Quick Example

from glyphx import plot

fig = plot(x=[1, 2, 3], y=[2, 4, 6], kind="line", label="Demo")
# No need for fig.show(); it auto-displays in Jupyter or saves via fig.save()

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Chart Types

• Line chart
• Bar chart (including grouped bars)
• Scatter plot
• Pie / Donut chart
• Box plot
• Histogram
• Swarm plot
• Violin plot
• Count plot
• lmplot, jointplot, pairplot
• Faceted charts (FacetGrid, facet_plot)

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Interactivity

All charts support:

• Mouseover tooltips
• Zoom / pan (mouse wheel + drag)
• Click-to-download buttons (SVG, PNG, JPG)

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Export Options

fig.save("my_chart.png")
fig.save("my_chart.svg")

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Grid Layout

from glyphx.layout import grid

charts = [plot(...), plot(...), plot(...)]
html = grid(charts, cols=2)

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Theming

from glyphx.themes import themes
theme = themes["dark"]

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Comparison with Matplotlib

📈 Line Plot

Matplotlib	GlyphX
import matplotlib.pyplot as plt <p>plt.plot([1, 2, 3], [4, 5, 6]) plt.title("Simple Line Plot") plt.xlabel("X Axis") plt.ylabel("Y Axis") plt.show()	from glyphx import plot</p> <p>plot(x=[1, 2, 3], y=[4, 5, 6], kind="line", title="Simple Line Plot", xlabel="X Axis", ylabel="Y Axis")

📊 Bar Chart

Matplotlib	GlyphX
import matplotlib.pyplot as plt <p>plt.bar(["A", "B", "C"], [5, 3, 7]) plt.title("Bar Chart") plt.xlabel("Categories") plt.ylabel("Values") plt.show()	from glyphx import plot</p> <p>plot(x=["A", "B", "C"], y=[5, 3, 7], kind="bar", title="Bar Chart", xlabel="Categories", ylabel="Values")

🔵 Scatter Plot

Matplotlib	GlyphX
import matplotlib.pyplot as plt <p>plt.scatter([1, 2, 3, 4], [4, 1, 3, 5]) plt.title("Scatter Plot") plt.xlabel("X Axis") plt.ylabel("Y Axis") plt.show()	from glyphx import plot</p> <p>plot(x=[1, 2, 3, 4], y=[4, 1, 3, 5], kind="scatter", title="Scatter Plot", xlabel="X Axis", ylabel="Y Axis")

🥧 Pie Chart

Matplotlib	GlyphX
import matplotlib.pyplot as plt <p>labels = ["A", "B", "C"] sizes = [30, 45, 25] plt.pie(sizes, labels=labels) plt.title("Pie Chart") plt.show()	from glyphx import plot</p> <p>plot(data=[30, 45, 25], kind="pie", labels=["A", "B", "C"], title="Pie Chart")

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Subplot Grid Example

from glyphx import Figure, series, themes <p>fig = Figure(rows=2, cols=2, theme=themes["dark"])</p> <p>ax1 = fig.add_axes(0, 0) ax1.add(series.LineSeries([1, 2], [3, 4], label="Line")) ax1.legend_pos = "right"</p> <p>ax2 = fig.add_axes(1, 0) ax2.add(series.ScatterSeries([1, 2, 3, 4], [4, 1, 3, 5], label="Scatter")) ax2.legend_pos = "right"</p> <p>ax3 = fig.add_axes(0, 1) ax3.add(series.BarSeries(x=["A", "B", "C"], y=[5, 3, 7], label="Bar")) ax3.legend_pos = "right"</p> <p>ax4 = fig.add_axes(1, 1) ax4.add(series.PieSeries(values=[30, 45, 25], labels=["A", "B", "C"]))</p> <p>fig.plot()

import matplotlib.pyplot as plt import numpy as np <p>fig, axs = plt.subplots(2, 2, figsize=(10, 8))</p> <p>axs[0, 0].plot([1, 2], [3, 4]) axs[0, 0].set_title("Line")</p> <p>axs[1, 0].scatter([1, 2, 3, 4], [4, 1, 3, 5]) axs[1, 0].set_title("Scatter")</p> <p>axs[0, 1].bar(["A", "B", "C"], [5, 3, 7]) axs[0, 1].set_title("Bar")</p> <p>axs[1, 1].pie([30, 45, 25], labels=["A", "B", "C"]) axs[1, 1].set_title("Pie")</p> <p>plt.tight_layout() plt.show()

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License

MIT License
(c) 2025 GlyphX contributors