Hooking up your own events#

The napari graphical user interface (GUI) operates within an event loop that waits for and responds to user interaction ‘events’. If you are unfamiliar with event loops, see napari event loop for a more detailed introduction.

If you would like to set up a custom event listener then you need to hook into the napari event loop. We offer a couple of convenience decorators to easily connect functions to key and mouse events. You can also connect to native napari events.

If the function you wish to connect takes a long time (e.g., is computationally expensive) you may want to consider multithreading. See Long-running, blocking functions for more.

Listening for keypress events#

One option is to use keybindings, that will listen for keypresses and then call some callback whenever pressed, with the viewer instance passed as an argument to that function. As a basic example, to add a random image to the viewer every time the i key is pressed, and delete the last layer when the k key is pressed:

import numpy as np
import napari

viewer = napari.Viewer()

@viewer.bind_key('i')
def add_layer(viewer):
    viewer.add_image(np.random.random((512, 512)))

@viewer.bind_key('k')
def delete_layer(viewer):
    try:
        viewer.layers.pop(0)
    except IndexError:
        pass

napari.run()

See also this custom key bindings example.

Listening for mouse events#

You can also listen for and react to mouse events, like a click or drag event, as shown here where we update the image with random data every time it is clicked.

import numpy as np
import napari

viewer = napari.Viewer()
layer = viewer.add_image(np.random.random((512, 512)))

@layer.mouse_drag_callbacks.append
def update_layer(layer, event):
    layer.data = np.random.random((512, 512))

napari.run()

As of this writing MouseProviders have 4 list of callbacks that can be registered:

  • mouse_move_callbacks

  • mouse_wheel_callbacks

  • mouse_drag_callbacks

  • mouse_double_click_callbacks

Please look at the documentation of MouseProvider for a more in depth discussion of when each callback is triggered. In particular single click can be registered with mouse_drag_callbacks, and mouse_double_click_callbacks is triggered in addition to mouse mouse_drag_callbacks.

See also the custom mouse functions and mouse drag callback examples.

Connecting functions to native napari events#

If you want something to happen following some event that happens within napari, the trick becomes knowing which native signals any given napari object provides for you to “connect” to. Until we have centralized documentation for all of the events offered by napari objects, the best way to find these is to browse the source code. Take for instance, the base Layer class: you’ll find in the __init__ method a self.events section that looks like this:

self.events = EmitterGroup(
    ...
    data=Event,
    name=Event,
    ...
)

That tells you that all layers are capable of emitting events called data, and name (among many others) that will (presumably) be emitted when that property changes. To provide your own response to that change, you can hook up a callback function that accepts the event object:

def print_layer_name(event):
    print(f"{event.source.name} changed its data!")

layer.events.data.connect(print_layer_name)

Long-running, blocking functions#

An important detail here is that the napari event loop is running in a single thread. This works just fine if the handling of each event is very short, as is usually the case with moving sliders, and pressing buttons. However, if one of the events in the queue takes a long time to process, then every other event must wait!

Take this example in napari:

viewer = napari.Viewer()
# everything is fine so far... but if we trigger a long computation
image = np.random.rand(512, 1024, 1024).mean(0)
viewer.add_image(image)
# the entire interface freezes!

Here we have a long computation (np.random.rand(512, 1024, 1024).mean(0)) that “blocks” the main thread, meaning no button press, key press, or any other event can be processed until it’s done. In this scenario, it’s best to put your long-running function into another thread or process. napari provides a convenience for that, described in Multithreading in napari.