IPython GUI Support Notes

IPython allows GUI event loops to be run in an interactive IPython session. This is done using Python's PyOS_InputHook hook which Python calls when the :func:`raw_input` function is called and waiting for user input. IPython has versions of this hook for wx, pyqt4 and pygtk.

When a GUI program is used interactively within IPython, the event loop of the GUI should not be started. This is because, the PyOS_Inputhook itself is responsible for iterating the GUI event loop.

IPython has facilities for installing the needed input hook for each GUI toolkit and for creating the needed main GUI application object. Usually, these main application objects should be created only once and for some GUI toolkits, special options have to be passed to the application object to enable it to function properly in IPython.

We need to answer the following questions:

• Who is responsible for creating the main GUI application object, IPython or third parties (matplotlib, enthought.traits, etc.)?
• What is the proper way for third party code to detect if a GUI application object has already been created? If one has been created, how should the existing instance be retrieved?
• In a GUI application object has been created, how should third party code detect if the GUI event loop is running. It is not sufficient to call the relevant function methods in the GUI toolkits (like IsMainLoopRunning) because those don't know if the GUI event loop is running through the input hook.
• We might need a way for third party code to determine if it is running in IPython or not. Currently, the only way of running GUI code in IPython is by using the input hook, but eventually, GUI based versions of IPython will allow the GUI event loop in the more traditional manner. We will need a way for third party code to distinguish between these two cases.

Here is some sample code I have been using to debug this issue:

from matplotlib import pyplot as plt

from enthought.traits import api as traits

class Foo(traits.HasTraits):
    a = traits.Float()

f = Foo()
f.configure_traits()

plt.plot(range(10))