Python-native Mermaid diagram converter – no browser, Node.js, or npm required. Renders diagrams to SVG/PNG/PDF using an embedded QuickJS engine and resvg, perfect for documentation automation and CI/CD pipelines.
Project description
mermaidx — Mermaid Diagram Converter for Python
Convert Mermaid diagrams to SVG, PNG, PDF, or ASCII art — fully offline and fast, just pip install mermaidx.
Completely browserless. No Node.js, no npm, no Chrome, no system packages, nothing to compile. And because there's no browser to boot, mermaidx renders noticeably faster than the official mermaid-cli, which drives a real headless Chrome through Puppeteer for every single diagram — mermaidx uses a fast, embedded JS engine instead.
pip install mermaidx
That's it — SVG, PNG, PDF, and ASCII output all work out of the box; nothing else to install.
Why mermaidx?
The official Mermaid CLI (@mermaid-js/mermaid-cli) works by spinning up a real headless Chrome via Puppeteer for every render. That works, but a full browser is slow to start and heavy to install (~170MB+ of Chromium), which shows up directly in wall-clock time — especially in CI pipelines rendering many diagrams, or anything short-lived like a serverless function.
mermaidx renders the actual, current Mermaid v11 JS library — not a reimplementation, not a subset — but runs it inside a small embedded JavaScript engine instead of a browser. No browser process to spawn, no page to load, no DOM to boot — just the JS engine running Mermaid's own layout code directly. That's the whole speed difference in one sentence: browser vs. no browser.
Quick Start
import mermaidx
d = mermaidx.render("""
graph TD
A[Install] --> B[Import]
B --> C[Convert]
C --> D[Done]
""")
d.save("diagram.svg")
d.save("diagram.png", scale=2.0)
d.save("diagram.pdf", pdf_format="A4")
print(d.ascii())
mermaidx -i diagram.mermaid -o diagram.svg
mermaidx -i diagram.mermaid -o diagram.png --scale 2.0
cat diagram.mermaid | mermaidx -i - -o diagram.pdf
Jupyter
A Diagram displays automatically as the last expression in a cell — no extra code needed, the same way a DataFrame or a matplotlib figure does:
import mermaidx
mermaidx.render("flowchart LR; A-->B-->C") # just shows up
.show() displays it explicitly (e.g. inside a loop) — it always shows exactly what .svg() returns, so what you see is this package's own render output, not a separate re-render through some other engine.
See examples/jupyter_demo.ipynb for a full walkthrough: display, PNG/PDF/ASCII export, themes, and batch rendering.
How It Works
flowchart LR
A[Mermaid source] --> B[QuickJS-ng]
B -->|"mermaid.js v11 (bundled)"| C[SVG]
C --> D[resvg]
D --> E[PNG]
C --> F["hand-written PDF writer<br/>(stdlib only)"]
F --> G[PDF]
H[bundled DejaVu Sans] -.font metrics.-> B
H -.same font, forced.-> D
Everything happens in one process, no subprocess, no I/O:
- SVG — mermaid.js runs inside QuickJS-ng against a minimal fake DOM/SVG implementation. The one thing a fake DOM can't fabricate — real text metrics (
getBBox/getComputedTextLength) — is bridged back into Python, which reads real glyph widths from a bundled font. - PNG — the SVG is rasterized by resvg, forced to use that same bundled font, so what mermaid measured during layout is exactly what gets painted.
- PDF — a small hand-written PDF writer (stdlib
zlib/structonly) embeds the rendered pixels directly. No Pillow, no Cairo, no reportlab — every mainstream "put an image in a PDF" library pulls in Pillow as a transitive dependency; this avoids that entirely. - ASCII — a completely separate, lightweight path via termaid (pure Python, ~700KB, zero dependencies), which parses the Mermaid source itself rather than going through the SVG.
Rendering is CPU-bound, synchronous, single-process — there's no browser or subprocess to wait on, so there's nothing for async to usefully overlap. See mermaidx.render_many() below for real parallelism instead.
Every backend is a small subclass of one shared DiagramBase — Diagram for 'js', DiagramRust for anything from the optional mmdr package. Subclasses only override the private _svg() hook; the public, cached svg()/png()/pdf()/raw()/numpy()/ascii()/save() are all written once in the base class and work identically regardless of which backend produced the SVG.
Python API
render(source, backend=None, **opts) -> Diagram
import mermaidx
d = mermaidx.render("flowchart LR; A-->B-->C")
render() itself does nothing but store the source — every Diagram method below is lazy and cached: nothing is computed until you call it, and calling it again with the same arguments returns the memoized result instead of recomputing.
| Method | Returns | Notes |
|---|---|---|
.svg() |
str |
Computed on first call, cached after |
.png(width?, height?, scale?, background?) |
bytes |
Aspect ratio always preserved |
.pdf(pdf_format?, pdf_landscape?, pdf_margin?, width?, height?, scale?, background?) |
bytes |
pdf_format=None (default) fits the page to the diagram |
.ascii(**opts) |
str |
Renders straight from the Mermaid source, doesn't need .svg() first |
.raw(width?, height?, background?) |
(bytes, w, h) |
Raw RGBA8888, no imaging library involved |
.numpy(width?, height?, background?) |
np.ndarray |
(H, W, 4) uint8; requires numpy |
.save(path, format=None, ...) |
None |
Format from format=, or inferred from the extension otherwise |
._repr_svg_() |
str |
Automatic inline rendering in Jupyter/IPython |
d.svg() is d.svg() # True -- second call is a cache hit, not a re-render
d.png(width=1200, background="#ffffff")
d.raw() # (bytes, width, height) -- RGBA8888
d.numpy() # np.ndarray, no Pillow needed
d.ascii() # ASCII/Unicode box-drawing art
d.save("out.pdf", pdf_format="A4", pdf_margin="1cm")
save(): format from the extension, or forced explicitly
d.save("out.svg") # -> svg
d.save("out.png") # -> png
d.save("out.pdf") # -> pdf
d.save("out.txt") # -> ascii
d.save("out.whatever", format="png") # force a format regardless of extension
Themes, config, CSS
mermaidx.render(source, theme="dark") # "default" | "forest" | "dark" | "neutral"
mermaidx.render(source, config={"flowchart": {"curve": "basis"}})
mermaidx.render(source, css=".node rect { rx: 8; ry: 8; }")
Parallel batch rendering
Rendering is pure CPU work — no I/O to overlap, so real concurrency means real processes, not async:
diagrams = mermaidx.render_many(sources, workers=4, theme="dark")
for d, name in zip(diagrams, output_names):
d.save(name)
Each worker process starts its own persistent engine once and reuses it for every diagram routed to it.
ASCII / terminal output
Works out of the box — termaid (pure Python, ~700KB, zero dependencies of its own) is a core dependency, not an optional extra:
print(mermaidx.render_ascii("graph LR; A-->B-->C"))
# or, equivalently: mermaidx.render("graph LR; A-->B-->C").ascii()
┌───┐ ┌───┐ ┌───┐
│ A ├───►│ B ├───►│ C │
└───┘ └───┘ └───┘
Low-level utilities
Rasterize any SVG string directly, without going through render():
from mermaidx import svg_to_png, svg_to_raw
svg = open("diagram.svg").read()
png = svg_to_png(svg, width=1200, background="#ffffff")
raw, w, h = svg_to_raw(svg)
Additional backends (optional)
pip install mermaidx[rust]
If mmdr (a native-Rust Mermaid renderer) is installed, its backends become available too — same interface either way, and with a bonus: PDF/raw/numpy work even for backends that don't natively support them (mmdr's own Diagram.pdf() raises NotImplementedError; mermaidx's doesn't, for any backend), because every backend shares the same DiagramBase — only svg() differs per backend, everything downstream of it (PNG/PDF/raw/numpy) is the same resvg + PDF-writer pipeline for all of them:
mermaidx.backends()
# ['js'] # mmdr not installed
# ['js', 'merman', 'mermaid-rs-renderer'] # mmdr installed
d = mermaidx.render(source, backend="merman") # svg() comes from mmdr; everything else from mermaidx
d.pdf() # works, even though mmdr's own .pdf() doesn't
CLI
# SVG to stdout (no -o needed)
mermaidx -i diagram.mermaid
cat diagram.mermaid | mermaidx -i -
# save to file (format from extension)
mermaidx -i diagram.mermaid -o diagram.svg
mermaidx -i diagram.mermaid -o diagram.png
mermaidx -i diagram.mermaid -o diagram.pdf
# size
mermaidx -i diagram.mermaid -o diagram.png -w 1200
mermaidx -i diagram.mermaid -o diagram.png --scale 2.0
# theme & background
mermaidx -i diagram.mermaid -o diagram.svg --theme dark
mermaidx -i diagram.mermaid -o diagram.png --background "#f5f5f5"
# PDF options
mermaidx -i diagram.mermaid -o diagram.pdf --pdf-format A4 --landscape --margin 1cm
# config & CSS
mermaidx -i diagram.mermaid -o diagram.svg --config config.json --css style.css
# info — Mermaid library version
mermaidx --info
# list available backends
mermaidx --list-backends
# pick a backend explicitly (requires mermaidx[rust] for anything but 'js')
mermaidx -i diagram.mermaid -o diagram.svg --backend merman
# version
mermaidx --version # or -v
Supported Diagram Types
Everything Mermaid v11 itself supports (this bundles the real library, not a subset): flowcharts, sequence diagrams, class diagrams, state diagrams, ER diagrams, Gantt charts, pie charts, git graphs, and more.
Requirements
- Python 3.9+
quickjs-ng,resvg_py,termaid(installed automatically)- No system packages, no Node.js, no npm, no browser
Testing
pip install -e ".[test]"
pytest tests/ -v
tests/test_online_comparison.py structurally cross-checks output against mermaid.ink (labels + aspect ratio, not pixel-diffing — two different rendering engines never match pixel-for-pixel). It needs outbound internet access and skips itself gracefully if that's unavailable or the service returns a transient error.
History
- mmdc, powered by phasma — the original version of this project. It bundled a real (if small — around 20MB) headless browser, PhantomJS, and exposed an
asyncPython API to match: rendering meant talking to a subprocess, soasync/awaitgenuinely mattered for concurrency. - 0.6.x — a full rewrite: PhantomJS's engine couldn't parse modern Mermaid (v11's ES2022+ syntax) at all, so the whole browser was replaced with mermaid.js running inside QuickJS-ng against a hand-written DOM/SVG shim, with resvg for rasterization. No subprocess left to wait on, so the API became synchronous. Three backends appeared:
js(this engine), plusmermanandmermaid-rs-renderervia the optionalmmdrpackage. - 0.7.x, renamed to mermaidx — same engine, new name. The old name,
mmdc, was identical to the official Mermaid CLI's own binary name (@mermaid-js/mermaid-cliinstalls a command calledmmdc) — a real collision, not just a branding concern. Renamed early, while it still could be.
Acknowledgments
- Mermaid — the actual diagramming library this project renders.
mermaidxwouldn't exist without it; all it does is run the real thing somewhere a browser can't go. - mmdr — a native-Rust Mermaid renderer by the same author, usable as an additional backend here (see Additional backends).
- termaid — powers ASCII/Unicode terminal output.
Contributing
- Fork and create a feature branch
- Add tests for new functionality
- Run
pytest tests/— all must pass - Open a pull request
License
MIT — see LICENSE for details.
If mermaidx saves you from booting a headless Chrome instance a hundred times in CI, consider leaving a ⭐ on the repo — it genuinely helps others find the project.
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