For a variety of reasons I have recently started to study options to write PyQt applications which are directly started from a Python3 notebook in Jupyterlab and are displayed on the Linux desktop.

Without blocking further code execution in other notebook cells and without compromising interactivity both of the notebook and the Qt windows.

Due to the support of QtAgg you do not need any blocking “app.exec_()” statements. You just construct your PyQt windows (with Qt-widgets and integrated Matplotlib figures) and afterward show them on your Linux desktop.

In addition it is rather easy to move activities, objects, methods to background threads controlled by QThread-objects. Worker objects in such threads can communicate with Qt windows and widgets in the foreground via signals, which end up in a thread-safe and serialized way in the Qt event-loop in the main thread. From there they are picked up and handled by callbacks.

I found this a fascinating way on a Linux system with a KDE desktop to use Python in Jupyterlab to create full-fledged Qt-applications and run them under the control of Jupyterlab.

People who are interested find more information in the sister-blog machine-learning.anracom.com.

See the posts

Using PyQt with QtAgg in Jupyterlab – I – a first simple example
Using PyQt with QtAgg in Jupyterlab – II – excursion on threads, signals and events
Using PyQt with QtAgg in Jupyterlab – III – a simple pattern for background threads
Using PyQt with QtAgg in Jupyterlab – IV – simple PyQt and MPL application with background worker and receiver threads