An Introduction to the Event Loop in napari

Brief summary

It is not necessary to have a deep understanding of Qt or event loops to use napari. napari attempts to use “sane defaults” for most scenarios. Here are the most important details:

In IPython or Jupyter Notebook

napari will detect if you are running an IPython or Jupyter shell, and will automatically use the IPython GUI event loop. As of version 0.4.7, it is no longer necessary to call %gui qt manually. Just create a viewer:

In [1]: import napari

In [2]: viewer = napari.Viewer()  # Viewer will show in a new window

In [3]: ... # Continue interactive usage


If you would prefer that napari did not start the interactive event loop for you in IPython, then you can disable it with:

from napari.utils import SETTINGS

SETTINGS.application.ipy_interactive = False

… but then you will have to start the program yourself as described below.

In a script

Outside of IPython, you must tell napari when to “start the program” using This will block execution of your script at that point, show the viewer, and wait for any user interaction. When the last viewer closes, execution of the script will proceed.

import napari

viewer = napari.Viewer()
...  # Continue setting  up your program

# Start the program, show the viewer, wait for GUI interaction. 

# Anything below here will execute only after the viewer is closed.

More in depth…

Like most applications with a graphical user interface (GUI), napari operates within an event loop that waits for – and responds to – events triggered by the user’s interactions with the interface. These events might be something like a mouse click, or a keypress, and usually correspond to some specific action taken by the user (e.g. “user moved the gamma slider”).

At its core, an event loop is rather simple. It amounts to something that looks like this (in pseudo-code):

event_queue = Queue()

while True:  # infinite loop!
    if not event_queue.is_empty():
        event = get_next_event()
        if event.value == 'Quit':

Actions taken by the user add events to the queue (e.g. “button pressed”, “slider moved”, etc…), and the event loop handles them one at a time.

Qt Applications and Event Loops

Currently, napari uses Qt as its GUI backend, and the main loop handling events in napari is the Qt EventLoop.

A deep dive into the Qt event loop is beyond the scope of this document, but it’s worth being aware of two critical steps in the “lifetime” of a Qt Application:

  1. Any program that would like to create a QWidget (the class from which all napari’s graphical elements are subclassed), must create a QApplication instance before instantiating any widgets.

    from qtpy.QtWidgets import QApplication
    app = QApplication([])  # where [] is a list of args passed to the App
  2. In order to actually show and interact with widgets, one must start the application’s event loop:


napari’s QApplication

In napari, the initial step of creating the QApplication is handled by napari.qt.get_app(). (Note however, that napari will do this for you automatically behind the scenes when you create a viewer with napari.Viewer())

The second step – starting the Qt event loop – is handled by

import napari

viewer = napari.Viewer()  # This will create a Application if one doesn't exist  # This will call `app.exec_()` and start the event loop.

What about napari.gui_qt?

napari.gui_qt() was deprecated in version 0.4.8.

The autocreation of the QApplication instance and the function was introduced in PR#2056, and released in version 0.4.3. Prior to that, all napari examples included this gui_qt() context manager:

# deprecated
with napari.gui_qt():
    viewer = napari.Viewer()

On entering the context, gui_qt would create a QApplication, and on exiting the context, it would start the event loop (the two critical steps mentioned above).

Unlike a typical context manager, however, it did not actually destroy the QApplication (since it may still be needed in the same session)… and future calls to gui_qt were only needed to start the event loop. By auto-creating the QApplication during Viewer creation, introducing the explicit function, and using the integrated IPython event loop when applicable, we hope to simplify the usage of napari.

Now that you have an understanding of how napari creates the event loop, you may wish to learn more about hooking up your own actions and callbacks to specific events.