Real-Time Histogram Plots on Unbounded Data

Everyones's data science toolbox contains some base tools. We use them systematically up to the point that we consider their usage for granted. Histograms are one of them. We use them for visualization in the exploration phase, during validation...

Performance And Explainability With EBM

Since ever, one had to choose between efficient models and explainable models. On one side, simple models like logistic regression are interpretable but lag on performances. On the other side complex models like Boosted Trees or Neural Network...

RxPy Explained: Map, Filter, and Scan

Every technology, paradigm, or framework relies on some foundations. ReactiveX is no exception. Whether you are a beginner or fluent in it, you will rely on three base operators: Map, Filter, and Scan. These are the three Musketeers of ReactiveX....

Stream Processing Made Easy

More and more data science use cases are done in real-time: Alerting, defect detection, prediction, automated recovery are some examples. Yet implementing and deploying them can be very challenging. Maki Nage is a framework that aims at...

An Introduction to Reactive Programming in Python

ReactiveX is a wonderful framework that allows to write event based code in a very elegant and readable way. Still, getting started in it can be challenging, and intimidating. In practice once you understand few key principles of ReactiveX, you...

RxPY Cohabitation with AsyncIO

With AsyncIO being more and more popular, and an ecosystem that grows rapidly, we regularly see questions on how RxPY can cohabit with AsyncIO libraries. This post provides some elements of answer on this topic. The RxPY documentation contains an...

The UI Strikes Back

Almost 4 years ago, I thought than after the good adoption rate of edLeak from my colleagues, they would love to have a python API to write their own script. Unfortunately, the success has been... very disappointing. The fact is that developers...