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Quick start

From Python​

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.jpg", quality=90)       # also .jpeg, .bmp and .tga
d.save("diagram.pdf", pdf_format="A4")
print(d.ascii())

render() returns a Diagram. The SVG is computed once and cached, and every other format is derived from it.

d.svg()                                  # str
d.png(width=1200, background="#ffffff")  # bytes
d.raw()                                  # (bytes, width, height), RGBA8888
d.numpy()                                # numpy array, needs numpy
d.pdf()                                  # bytes

Render many diagrams​

render_many uses a process pool, so it scales across CPU cores:

diagrams = mermaidx.render_many([src1, src2, src3], workers=4, theme="dark")
for d, name in zip(diagrams, ["a.svg", "b.svg", "c.svg"]):
    d.save(name)

From the command line​

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

The full list of options is on the command line page.

In Jupyter​

A Diagram displays itself when it is the last expression in a cell, the same way a DataFrame or a Matplotlib figure does:

mermaidx.render("flowchart LR; A-->B-->C")

Try it in Google Colab.

Choose a backend​

Pass backend= to use another engine. Each backend is described on the backends page.

mermaidx.render("flowchart LR; A-->B", backend="v8")