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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 functionality. For our first PyQt test application we just used multiple nested Qt-widgets in a QMainWindow to create a simple, but interactive and instructive application… 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 cells) of a Python3 notebook while the long running jobs do their work in the background. This includes that these other cells may also start… 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 my Linux system. When starting Jupyterlab I get error messages of the kind: ‘iopub_data_rate_limit’ has moved from NotebookApp to ServerApp. This config will be passed… Read More »Jupyterlab – resolve error messages regarding iopub_data_rate_limit

Jupyterlab, matplotlib, dynamic plots – II – external Qt-windows and figure updates from foreground jobs

The work on this post series has been delayed a bit. One of my objectives was to use background jobs to directly redraw or to at least trigger a redrawing of Matplotlib figures with backends like Qt5Agg. By using background jobs I wanted to circumvent a blocking of code execution in other further Juypter notebook cells. This would to e.g. perform data analysis tasks in the foreground whilst long running Python jobs are executed in the background (e.g. jobs for training a ML-algorithm). This challenge… Read More »Jupyterlab, matplotlib, dynamic plots – II – external Qt-windows and figure updates from foreground jobs