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Using PyQt with QtAgg in Jupyterlab – III – a simple pattern for background threads

We can use PyQt to organize output of Machine Learning applications in Qt-windows outside of Jupyterlab notebooks on a Linux desktop. PyQt also provides us with an option to put long running Python code as ML training and evaluation runs into the background of Jupyterlab and redirect graphical and text output to elements of Qt windows. Moving long lasting Python… Read More »Using PyQt with QtAgg in Jupyterlab – III – a simple pattern for background threads

Using PyQt with QtAgg in Jupyterlab – II – excursion on threads, signals and events

In the first post of this series on PyQt Using PyQt with QtAgg in Jupyterlab – I – a first simple example we have studied how to set up a PyQt application in a Jupyterlab notebook. The key to getting a seamless integration was to invoke the QtAgg-backend of Matplotlib. Otherwise we did not need to use any of Matplolib’s… Read More »Using PyQt with QtAgg in Jupyterlab – II – excursion on threads, signals and events

Using PyQt with QtAgg in Jupyterlab – I – a first simple example

As my readers know I presently study how to work with background jobs for plot and information updates in Jupyterlab. The reason for this endeavor is that I want to organize my work with ML- training and long evaluation runs a bit differently in the future. In particular I want to have the freedom of working in other regions (other… Read More »Using PyQt with QtAgg in Jupyterlab – I – a first simple example

Jupyterlab – resolve error messages regarding iopub_data_rate_limit

When I worked with some ML-based text evaluation I had run across an output limit rate on the notebooks output rate: iopub_data_rate_limit : (bytes/sec) Maximum rate at which stream output can be sent on iopub before they are limited. I had changed it by a factor of 10 from the standard value in a file ~/.jupyter/jupyter_notebook_config.py in my home-directory on… Read More »Jupyterlab – resolve error messages regarding iopub_data_rate_limit