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PlotDevice is a Macintosh application used for computational graphic design. It provides an interactive Python environment where you can create two-dimensional graphics and output them in a variety of vector, bitmap, and animation formats. It is meant both as a sketch environment for exploring generative design and as a general purpose graphics library for use in external Python programs.

PlotDevice scripts can create images from simple geometric primitives, text, and external vector or bitmap images. Drawing commands provide a thin abstraction over macOS's Quartz graphics engine, providing high-quality rendering of 2D imagery and powerful compositing operations.


The PlotDevice application requires macOS 11 or greater (either on Intel or Apple Silicon) and comes bundled with a Python 3.10 distribution. The module can be installed via pip3 on Python versions ≥3.6 (including the interpreter from the Xcode command line tools and those installed through Homebrew).

Latest changes (July 2022)

Over the years since the last release, progress in both macOS and Python itself led to quite a bit of breakage. Some of the highlights of this maintenance release include:

New Features
  • Runs natively on Intel and Apple Silicon and supports retina displays
  • Python 3 support (including a bundled 3.10 installation in the app)
  • images can now be exported in HEIC format and videos support H.265 (HEVC)
  • SVG files can now be drawn to the canvas using the image() command (thanks to the magical SwiftDraw library)
  • image exports have a configurable zoom to create 2x/3x/etc ‘retina’ images
  • revamped var() command for creating GUIs to modify values via sliders, buttons, toggles, etc.
  • updated text editor with multiple tabs, new themes, and additional key-binding modes emulating Sublime Text and VS Code
  • the module's command line interface is now accessible through python3 -m plotdevice
  • the command line tool has a new --install option to download PyPI packages for use within the app
  • document autosaving is now user-configurable
  • exported images generated on retina machines now have the proper dimensions
  • hex colors can now use lowercase letters
  • automatic variables like WIDTH & HEIGHT correctly support the / operator
  • the Color object's .blend() method is working again
  • the read() command can now handle csv files with spaces in their header row names
  • the translate() command now incorporates non-pixel grid units set via the size() command
  • cmyk exports are working reliably for command line --export and via the export(cmyk=True) method
  • arguments defined using the command line tool's --args options are now passed to the script's sys.argv
Misc. Improvements
  • the command line tool can be exited via ctrl-c in addtion to being Quit from the menu bar
  • simplified unicode handling (and improved support for normalization of user-provided strings)
  • building the module now only requires Xcode command line tools—not a full installation
  • the text() command will always treat its first argument as content (even if it's not a string) unless a str, xml, or src keyword argument is provided
  • the mouse pointer is now visible in full-screen mode (and will auto-hide when inactive)
Unfortunate Casualties
  • The NodeBox Libraries (coreimage, colors, and friends) would require quite a bit of attention to get working properly again. A first pass can be found in the plotdevice-libs repository but they're not ready for prime-time. If you're interested in contributing, this would be a terrific place to start!


PlotDevice supports being built as either a full-fledged Cocoa application, or as a standard Python module to be installed into a virtualenv alongside your source files. In both cases it now includes a command line tool called plotdevice allowing you to run scripts and perform batch exports from the console.

Application builds

The application can be built in Xcode with the PlotDevice.xcodeproj project. It can also be built from the command line by using python3 app (which uses Xcode) or python3 py2app (which uses setuptools).

The resulting binary will appear in the dist subdirectory and can be moved to your Applications folder or any other fixed directory. To install a symlink to the command line tool, launch the app from its installed location and click the Install button in the Preferences window.

Prebuilt application binaries can be downloaded from the PlotDevice site.

Module builds

PlotDevice can also be built as a Python module, allowing you to rely on an external editor and launch scripts from the command line (or from a ‘shebang’ line at the top of your script invoking the plotdevice tool). To install the module and command line tool use python3 install

Easier still, you can install the module directly from PyPI with a simple pip3 install plotdevice. It's a good idea to install the wheel module first since it greatly speeds up installation of the PyObjC libraries PlotDevice depends on.

Alternative Python Interpreters

When using pyenv (or compiling Python from source) you have the option of building the interpreter as a Framework. This gives you access to a GUI interface for running PlotDevice scripts via the python3 -m plotdevice command. Non-framework builds support the command line's --export functionality and will open a viewer window, but will not show an icon in the Dock or give you access to the menu bar.

To set up and run a script using a Framework build, do something along the lines of:

env PYTHON_CONFIGURE_OPTS="--enable-framework" pyenv install 3.10.4
pyenv shell 3.10.4
pip3 install plotdevice
python3 -m plotdevice <script.pv>

Building from source

You can also clone the git repository and build PlotDevice as a module or application from scratch. Consult the build instructions for details.


The PlotDevice Manual provides extensive documentation of the various drawing commands and features sample code for nearly all of them. In addition to a detailed Reference, the manual also contains a number of Tutorial chapters that explain PlotDevice's inner workings concept-by-concept.

Beyond the core API, the Manual also collects documentation for the set of third-party Libraries that were written by the NodeBox community and ported to work with PlotDevice.

Running scripts

Once you have installed PlotDevice and added the plotdevice command to your shell's path, it can be used to run scripts in a window or export graphics to file using one of the supported image/video formats. The command itself is just a shorthand for running the module directly via python3 -m plotdevice (which accepts all the same command line arguments).

Command line usage

plotdevice [-h] [-f] [-b] [-q] [--live] [--cmyk] [--virtualenv PATH] [--args [a [b ...]]]
           [--export FILE] [--frames N or M-N] [--fps N] [--rate N] [--loop [N]] [--install [PACKAGES ...]]
Runtime arguments

-h show the help message then quit
-f run full-screen
-b run PlotDevice in the background (i.e., leave focus in the active application)
-q run a PlotDevice script ‘quietly’ (without opening a window)
--virtualenv PATH path to a virtualenv whose libraries you want to use (this should point to the top-level virtualenv directory)
--args [a [b ...]] arguments to be passed to the script as sys.argv

External editor integration

-b run PlotDevice in the background (i.e., don't switch apps when the script is run)
--live re-render graphics each time the file is saved

Image/animation export

--export FILE a destination filename ending in pdf, eps, png, tiff, jpg, heic, gif, or mov
--zoom PERCENT scale of the output image (100 = regular size) unless specified by a filename ending in @2x/@3x/etc --cmyk convert colors to CMYK before generating images (colors will be RGB if omitted)

Animation options

--frames N or M-N number of frames to render or a range specifying the first and last frames (default 1-150)
--fps N frames per second in exported video (default 30)
--rate N video bitrate in megabits per second (default 1)
--loop [N] number of times to loop an exported animated gif (omit N to loop forever)

Installing Packages from PyPI:

--install [packages ...] Use pip install to download libraries into the ~/Library/Application Support/PlotDevice directory, making them import-able in the application and by scripts run from the command line

Usage examples

# Run a script
plotdevice script.pv

# Run fullscreen
plotdevice -f script.pv

# Save script's output to pdf
plotdevice script.pv --export output.pdf

# Create an animated gif that loops every 2 seconds
plotdevice script.pv --export output.gif --frames 60 --fps 30 --loop

# Create a sequence of numbered png files – one for each frame in the animation
plotdevice script.pv --export output.png --frames 10

# Create a 5 second long H.265 video at 2 megabits/sec
plotdevice script.pv --export --frames 150 --rate 2.0

# Install some useful modules
plotdevice --install urllib3 jinja2 numpy

Using external libraries

Since PlotDevice scripts are pure Python, the entirety of the stdlib and PyPI are available to you. In addition, a wide array of PlotDevice Libraries have been contributed by the community to solve more visualization-specific problems.

Installing PlotDevice Libraries

Libraries’ are Python modules that have been written specifically for PlotDevice. To install a Library, copy its folder to ~/Library/Application Support/PlotDevice and then import it from your script. Libraries can be installed individually or en masse using the archive (35 MB) from the PlotDevice website.

Installing Python modules

The easiest way to use third-party modules from a PlotDevice script is to create a virtualenv and use pip3 to install your dependencies. You can then launch your script with the --virtualenv option to add them to the import path:

$ python3 -m venv env
$ source ./env/bin/activate
(env)$ pip3 install redis
(env)$ plotdevice script.pv --virtualenv ./env

If you're using PlotDevice as a module rather than an application, you have the option of installing it directly into the virtualenv containing your script's other dependencies. This places the plotdevice tool at a known location relative to your script and lets you omit the --virtualenv option:

$ python3 -m venv env
$ source ./env/bin/activate
(env)$ pip3 install plotdevice
(env)$ pip3 install requests envoy bs4 # some other useful packages
(env)$ plotdevice script.pv # uses the tool found at ./env/bin/plotdevice

Using PlotDevice as a module

Though the plotdevice command provides a convenient way to launch scripts with the PlotDevice interpreter, you may prefer to use the module's graphics context and export functions from within your own script (and running whichever python binary your system or virtualenv provides). Importing the plotdevice module's contents initializes your script's namespace with one identical to a script running with the app or command line tool. For instance, the following will draw a few boxes:

#!/usr/bin/env python3
from plotdevice import *
for x, y in grid(10,10,12,12):
    rect(x,y, 10,10)

You can then generate output files using the global export command. It takes a file path as an argument and the format will be determined by the file extension (pdf, eps, png, jpg, gif, or tiff):


If you plan to generate multiple images, be sure to call clear() to erase the canvas in between frames. Depending on the task you may also want to reset the graphics state. Use one of:

clear()    # erases the canvas
clear(all) # erases the canvas and resets colors, transforms, effects, etc.

If you would prefer to avoid import * and keep the PlotDevice API encapsulated in an object, create a Context and access its methods instead. For instance, the previous code snippets are equivalent to:

#!/usr/bin/env python3
from plotdevice.context import Context

ctx = Context()
for x, y in ctx.grid(10,10,12,12):
    ctx.rect(x,y, 10,10)
The export context manager

The export function returns a context manager that encapsulates this clear/draw/save cycle for both single images and animations. By enclosing your drawing code in a with block, you can ensure that the correct sequence of clear and export calls is generated automatically. For instance these two methods of generating a png are equivalent:

from plotdevice import *

# export an image
... # (do some drawing)

# export an image (with the context manager clearing and saving the canvas automatically)
with export('output.png'):
    ... # (do some drawing)

If you specify a filename ending in mov – or gif if you also pass a loop or fps argument – the export context manager will return a Movie object. Each time you call its add method, a new frame with the contents of the canvas will be added to the end of the animation. Once you've added the final frame, you must call finish to wait for the video encoder thread to complete its work.

As with the single-image version of the export call, you can use the with statement in your code to tidy up some of the frame-drawing boilerplate. All three examples are equivalent (note the use of a nested with statement in the final example):

# export a 100-frame movie
movie = export('', fps=50, bitrate=1.8)
for i in xrange(100):
    clear(all)  # erase the previous frame from the canvas
    ...         # (do some drawing)
    movie.add() # add the canvas to the movie
movie.finish()  # wait for i/o to complete
# export a movie (with the context manager finishing the file when done)
with export('', fps=50, bitrate=1.8) as movie:
    for i in xrange(100):
        clear(all)  # erase the previous frame from the canvas
        ...         # (do some drawing)
        movie.add() # add the canvas to the movie
# export a movie (with the context manager finishing the file when done)
# let the movie.frame context manager call clear() and add() for us
with export('', fps=50, bitrate=1.8) as movie:
    for i in xrange(100):
        with movie.frame:
            ... # draw the next frame
Multi-page PDFs

Creating PDF documents works the same way, letting you either manually clear, add and finish the export or take advantage of the with statement to hide the repetitive bits. Note that PDF exports use the page attribute rather than frame:

# export a five-page pdf document
pdf = export('multipage.pdf')
for i in xrange(5):
    clear(all) # erase the previous page's graphics from the canvas
    ...        # (do some drawing)
    pdf.add()  # add the canvas to the pdf as a new page
pdf.finish()   # write the pdf document to disk
# export a pdf document more succinctly
with export('multipage.pdf') as pdf:
    for i in xrange(5):
            ... # draw the next page
Image sequences

If you're generating a series of images, export will automatically give them consecutive names derived from the filename you pass as an argument. If the filename is a simple "name.ext" string, the sequence number will be appended with four characters of padding (yielding "name-0001.ext", "name-0002.ext", etc.).

If the filename contains a number between curly braces (e.g., "name-{4}.ext"), that substring will be replaced with the sequence number and zero padded to the specified number of digits:

# export a sequence of images to output-0001.png, output-0002.png, ...
#                                output-0099.png, output-0100.png
with export('output.png') as img:
    for i in xrange(100):
        with img.frame:
            ... # draw the next image in the sequence
# export a sequence of images to 01-img.png, 02-img.png, ...
#                                99-img.png, 100-img.png
with export('{2}-img.png') as img:
    for i in xrange(100):
        with img.frame:
            ... # draw the next image in the sequence


PlotDevice was derived from NodeBox's 1.9.7 release. Its current maintainer is Christian Swinehart.

NodeBox is a BSD-licensed graphics environment written by Frederik De Bleser.
The NodeBox manual and example code are by Tom De Smedt.

NodeBox is a fork of DrawBot by Just van Rossum.


PlotDevice is released under the MIT license. Use it as you see fit.


The PlotDevice source is available on GitHub:


Create 2D graphics on the Mac with Python code






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