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Advanced usage

This section is aimed at Python dabblers and hackers who want to get into the more involved features of Shoebot.

Using Shoebot as a Python module

Shoebot can be easily loaded as a module inside a Python script.

import shoebot

# set up a canvas
bot = shoebot.create_bot(outputfile="output.svg")

# size() needs to be called first
bot.size(400,400)

# now we can draw!
bot.rect(10,10,100,100)

# finish() should be called after all drawing commands
bot.finish()

Take a snapshot of the current state:

bot.snapshot("snap.png")

Run a Shoebot/Nodebox script:

bot.run("example.bot")

Running with PyPy

To get better performance, you can run Shoebot using PyPy, which is experimental.

When installing Shoebot, you have to point to PyPy when creating your virtualenv. Instead of the first command in the :ref:`Virtualenvwrapper install example <virtualenvwrapper-install>`, do:

mkvirtualenv shoebot -p `which pypy`

For the plain virtualenv approach, try:

virtualenv .env -p `which pypy`

Using with Django

See the shoebot-django for an example of integrating Shoebot into a Django application.

Shoebox Virtual Machine

Shoebox is a ready-to-use VirtualBox image that we use for Shoebot workshops. It's a lightweight Xubuntu-based system, with some components stripped for size. Shoebot and its Gedit plugin are installed and working out of the box.

It is the easiest way to get non-GNU/Linux systems running Shoebot. Even for GNU/Linux systems, it's the best choice if you don't want to add yet another package to your system, but aren't comfortable with virtualenvs.

To try this, Download VirtualBox, and then get the Shoebox appliance file (1.5 GB), import it into VirtualBox through File > Import Appliance, and launch your new Shoebox.