Overview#

Simplify your workflow with `vsk`#

vsketch includes a CLI tool called vsk that aims to automate every part of your workflow, from initial creation to final export, with the overarching objective of minimising the friction in the creative process. The following paragraphs demonstrate how vsk is typically used for various phases in a sketch project life-cycle.

Creating a sketch with `vsk init`#

Basic use:

$ vsk init my_project

The page size and orientation can be directly provided:

$ vsk init -p a4 -l my_project

A custom template can be provided:

$ vsk init --template path/to/template my_project

The template path may point to a file or a git repository. Templating is based on the cookiecutter project. The default template can be forked to serve as a basis. If the environment variable VSK_TEMPLATE is defined, it will be used as template by default.

Running a sketch with `vsk run`#

This commands execute the sketch script and displays the interactive viewer:

$ vsk run my_project

The viewer refreshes the display every time the sketch script is saved or parameters are modified in the interface.

If a second screen is available, it can be automatically used for the viewer:

$ vsk run --fullscreen my_project

This can ben permanently enabled by setting the VSK_FULLSCREEN environment variable.

If the --editor option is passed, it will be used to open the sketch script in the corresponding editor:

$ vsk run --editor charm my_project

Most popular IDE and editors have such a command (e.g. charm for PyCharm, code for VSCode, mate for TextMate, etc.). Again, setting the VSK_EDITOR environment variable enables this feature permanently.

Exporting SVG with `vsk save`#

Basic use (uses a random seed):

$ vsk save my_project

The random number generator seed can be specified:

$ vsk save --seed 10 my_project

Alternatively, a range of seeds can be specified:

$ vsk save --seed 0..99 my_project

In this case, all CPU cores are used to export SVG for every seed value within the provided range. This can be controlled with the --multiprocessing / --no-multiprocessing options and the VSK_MULTIPROCESSING environment variable.

If configurations have been saved using vsk run, they can be used for exporting as well:

$ vsk save --config my_config my_project

Shortcuts#

‘s’ to like the sketch
‘r’ to generate a new seed

Beyond the basics?#

Every single feature of vsk is documented in the integrated help. You can access the global help as follows:

$ vsk --help

This will list the available commands as well as the global options.

Each command has its dedicated help section as well. For example, you can access the vsk run command as follows:

$ vsk run --help

Write sketches with the vsketch API#

Sketches are made of code and vsketch API makes this code familiar, concise and easy-to-learn. The following paragraphs provides an overview of how a sketch is made.

Sketch structure#

Sketch scripts are used by the vsk CLI tool. They always have the same structure:

import vsketch

class MySketch(vsketch.SketchClass):
    def draw(self, vsk: vsketch.Vsketch) -> None:
        vsk.size("a4", landscape=False)

    def finalize(self, vsk: vsketch.Vsketch) -> None:
        vsk.vpype("linemerge linesimplify reloop linesort")


if __name__ == "__main__":
    MySketch().display()

This skeleton is generally created using the vsk init command.

Your sketch is encapsulated in a subclass of SketchClass which must implement two functions:

SketchClass.draw() implements the bulk of the sketch’s content.

SketchClass.finalize() implements the potentially CPU-heavy optimisations that are not required for display purposes.

For display purposes, vsk only calls SketchClass.draw(). However, when it exports a sketch to a SVG file, it also calls SketchClass.finalize(). This enables a fast refresh of the display when the sketch or its parameters change while ensuring that any SVG output is ready to plot.

Using vsketch as a regular package#

vsketch can also be used as a regular Python package, without relying on the vsk CLI tool. This is useful to work, for example, in Jupyter or Colab notebooks.

This is done by simply creating an instance of vsketch.Vsketch:

import vsketch

vsk = vsketch.Vsketch()
vsk.size("a4", landscape=True)
# ...

Primitives#

The usual primitives are available:

vsk.line(0, 0, 10, 20)
vsk.rect(10, 10, 5, 8)
vsk.circle(2, 2, radius=3)
vsk.triangle(0, 0, 1, 1, 0, 1)

So are the less usual primitives:

vsk.bezier(1, 1, 3, 1, 3, 3, 1, 3)

Units#

By default, vsketch uses CSS pixels as unit, just like SVG. If you’d rather work in some other unit, just start your sketch with a scale factor:

vsk.scale("1cm")
vsk.line(0, 0, 21, 29.7)  # this line will span an entire A4 page

Strokes, fills and layers#

Colors do not really make sense when preparing files for plotters. vsketch instead uses layers which are intended to be plotted with different pens each:

# by default, layer 1 is current
vsk.line(0, 0, 5, 5)

# the current layer can be changed
vsk.stroke(2)
vsk.circle(14, 8, 3)

Stroke can be made thicker with configurable join style:

# set pen width for layer 1
vsk.penWidth("0.5mm", 1)

# set current stroke layer to 1
vsk.stroke(1)

# make a thick stroke -- it will be drawn 5 times using the pen width as offset
vsk.strokeWeight(5)

# choose the join style: "round" (default), "mitre", or "bevel"
vsk.strokeJoin("mitre")

No reason plotters should miss on the “fill” party! This works just as you didn’t dare to expect:

# let's use a pen width of 0.5mm for layer 2
vsk.penWidth("0.5mm", 2)

# this circle will be stroked in layer 1 and and filled in layer 2
vsk.stroke(1)
vsk.fill(2)
vsk.circle(0, 0, 5)

Using Shapely#

Shapely is a computational geometry library that is often very useful for generative plotter art. vsketch directly accepts Shapely objects:

from shapely.geometry import Point

vsk.geometry(Point(0, 0).buffer(2).union(Point(1.5, 0).buffer(1.5)))

Transforms#

Transformation matrices are fully supported:

for i in range(5):
    with vsk.pushMatrix():
        vsk.rotate(i * 5, degrees=True)
        vsk.rect(-2, -2, 2, 2)

    vsk.translate(5, 0)

Internally, vsketch approximates all curves with segments. The level of detail (i.e. the maximum length of individual segment) can be adjusted. vsketch tries to be smart about this:

vsk.detail("0.1mm")

# this circle is made of segment 0.1mm-long or less
vsk.circle(0, 0, radius=1)

vsk.scale(100)

# because it is bigger, this circle will be made of many more segments than the previous one
vsk.circle(0, 0, radius=1)

Random numbers and seed#

vsketch offers two functions to generate pseudorandom numbers. Vsketch.random() returns a random number between specified bounds:

# with a single argument the range is between 0 and the value given
>>> vsk.random(15)
7.805739629734665

# with two arguments the range is between the two values
>>> vsk.random(3,4)
3.641185534728005

Vsketch.randomGaussian() returns a random number fitting a gaussian distribution with a mean of 0 and a standard deviation of 1.0:

# randomGaussian() takes no arguments
>>> vsk.randomGaussian()
0.981842376792542

By default vsketch will initialize the random number generator with a random seed, producing different results each time you run the sketch. If you prefer, you can set the seed using Vsketch.randomSeed() which will produce random but predictable results:

>>> vsk.randomSeed(349872)
>>> vsk.random(15)
5.705844347182719
>>> vsk.random(100, 200)
151.53912704762564

# if you set the seed to the same value and request the same random values, you'll get the same results
>>> vsk.randomSeed(349872)
>>> vsk.random(15)
5.705844347182719
>>> vsk.random(100, 200)
151.53912704762564

The seed can be read from Vsketch.random_seed:

>>> vsk.random_seed
1230026887

>>> vsk.randomSeed(234870)
>>> vsk.random_seed
234870

Perlin noise#

The noise() is a vectorized implementation of Perlin noise that can sample a random space of up to 3 dimensions. This example illustrate the case of a vectorised sampling of a 2D noise space:

num_lines = 250
x_coords = np.linspace(0., 250., 1000)
perlin = vsk.noise(x_coords * 0.1, np.linspace(0, 5., num_lines))
for j in range(num_lines):
    vsk.polygon(x_coords, j + perlin[:, j] * 6)

Using sub-sketches#

Multiple sketches can be created and used as reusable sub-sketches:

# create a sub-sketch
sub_sketch = vsketch.Vsketch()
sub_sketch.square(0, 0, 1)
sub_sketch.square(0.5, 0.5, 1)

# add the sub-sketch
vsk.sketch(sub_sketch)
vsk.translate(10, 10)
vsk.rotate(45, degrees=True)
vsk.sketch(sub_sketch)  # the transformation matrix is applied on the sub-sketch

Using vpype#

The power of vpype can be unleashed with a single call:

vsk.vpype("linesimplify linemerge reloop linesort")

Displaying and saving#

vsk generally takes care of running, displaying and exporting your sketch as SVG. When using vsketch as a standalone package, this must be done manually.

Displaying is done as follows:

vsk.display()

And saving a ready-to-plot SVG as follows:

vsk.save("my_file.svg")

Beyond the basics?#

The entire API is documented here.

Exploring the examples included with vsketch is a good way to learn about its API. If you have a local copy of vsketch’s repository, you can run any example with the following command:

$ vsk run examples/quick_draw

You may also check the author’s personal collection of sketches.

Overview#

Simplify your workflow with vsk#

Creating a sketch with vsk init#

Running a sketch with vsk run#

Exporting SVG with vsk save#

Shortcuts#

Beyond the basics?#

Write sketches with the vsketch API#

Sketch structure#

Using vsketch as a regular package#

Primitives#

Units#

Strokes, fills and layers#

Using Shapely#

Transforms#

Random numbers and seed#

Perlin noise#

Using sub-sketches#

Using vpype#

Displaying and saving#

Beyond the basics?#

Simplify your workflow with `vsk`#

Creating a sketch with `vsk init`#

Running a sketch with `vsk run`#

Exporting SVG with `vsk save`#