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Author = "Daniel C. Jones, Tamas Nagy"


Gadfly supports creating SVG images out of the box through the native Julian renderer in Compose.jl. The PNG, PDF, PS, and PGF formats, however, require Julia's bindings to cairo and fontconfig, which can be installed with


Rendering to a file

In addition to the draw interface presented in the [Tutorial](@ref Tutorial):

p = plot(...)
draw(SVG("foo.svg", 6inch, 4inch), p)

one can more succintly use Julia's function chaining syntax:

p |> SVG("foo.svg", 6inch, 4inch)

If you plan on drawing many figures of the same size, consider setting it as the default:

set_default_plot_size(6inch, 4inch)
p1 |> SVG("foo1.svg")
p2 |> SVG("foo2.svg")
p3 |> SVG("foo3.svg")

Choosing a backend

Drawing to different backends is easy. Simply swap SVG for one of SVGJS, PNG, PDF, PS, or PGF:

# e.g.
p |> PDF("foo.pdf")

Interactive SVGs

The SVGJS backend writes SVG with embedded javascript. There are a couple subtleties with using the output from this backend.

Drawing to the backend works like any other

draw(SVGJS("foo.svg", 6inch, 6inch), p)

If included with an <img> tag, the output will display as a static SVG image though.

<img src="foo.svg"/>

For the [interactive](@ref Interactivity) javascript features to be enabled, it either needs to be included inline in the HTML page, or included with an object tag.

<object data="foo.svg" type="image/svg+xml"></object>

For the latter, a div element must be placed, and the draw function must be passed the id of this element, so it knows where in the document to place the plot.


The IJulia project adds Julia support to Jupyter. This includes a browser based notebook that can inline graphics and plots. Gadfly works out of the box with IJulia, with or without drawing explicity to a backend.

Without an explicit call to draw (i.e. just calling plot without a trailing semicolon), the SVGJS backend is used with the default plot size, which can be changed as described above.