sea-nymph 1.1.0

A matplotlib-style Python library for generating Mermaid diagrams

sea-nymph

Do you want to show plots in your documentation? Do you want to avoid committing PNGs to git? Do you have an (un)reasonable dislike for SVG files? Look no further!

sea-nymph generates Mermaid charts from Python — plain text that renders natively on GitHub, GitLab, and most modern documentation tools. No image files, no binary blobs, no xml.

The API is modelled after seaborn: pass a DataFrame, name your columns, get a chart.

sea-nymph uses narwhals under the hood, so it accepts any DataFrame library — pandas, polars, PySpark, and more. Generate your markdown charts with distributed computing.

Installation

pip install sea-nymph

High-level API

import polars as pl
from sea_nymph import barplot, lineplot, countplot, histplot, kdeplot

df = pl.DataFrame({
    "month": ["Jan", "Feb", "Mar", "Apr"],
    "revenue": [10, 40, 30, 50],
    "region": ["North", "North", "South", "South"],
})

fig = barplot(df, x="month", y="revenue")
print(fig.render())

xychart-beta
    x-axis [Jan, Feb, Mar, Apr]
    y-axis "Revenue" 0 --> 50
    bar [10, 40, 30, 50]

Available plot functions

Function	Description
barplot	Bar chart with optional aggregation
lineplot	Line chart with optional aggregation
countplot	Count (or proportion/percent) of categorical values
histplot	Histogram with configurable bins and statistics
kdeplot	Kernel density estimate using Silverman's rule

All functions support a hue parameter for grouped series, hue_order and order for controlling category ordering, and palette for custom colours.

Hue

fig = barplot(df, x="month", y="revenue", hue="region", palette=["#4e79a7", "#f28e2b"])

Stat

countplot and histplot accept a stat parameter:

countplot(df, x="month", stat="percent")   # "count" | "percent" | "proportion" | "probability"
histplot(df, x="revenue", stat="density")  # "count" | "frequency" | "probability" | "proportion" | "percent" | "density"

Horizontal charts

Pass y instead of x to flip the orientation:

countplot(df, y="region")
kdeplot(df, y="revenue")

Low-level API

For full control, use XYChart from sea_nymph.mermaidplotlib directly:

from sea_nymph.mermaidplotlib import XYChart

months = ["Jan", "Feb", "Mar", "Apr"]
fig = XYChart()
fig.bar(months, [10, 40, 30, 50])
fig.line(months, [15, 35, 25, 45])
fig.xlabel("Month")
fig.ylabel("Revenue (k)")
fig.ylim(0, 60)
fig.title("Sales 2024")
print(fig.render())

xychart-beta
    title "Sales 2024"
    x-axis "Month" [Jan, Feb, Mar, Apr]
    y-axis "Revenue (k)" 0 --> 60
    bar [10, 40, 30, 50]
    line [15, 35, 25, 45]

Limitations

Mermaid's xychart-beta places all data points equidistantly on the axis. This means:

• Line charts require evenly-spaced numeric x values — sea-nymph raises an error if they are not.
• Histograms require equal-width bins for the same reason — unequal bin widths are rejected.