Setting up proper port forwarding for SSH connections, servers or just test purposes is crucial but isn’t as straight forward as your connection should be. This post aims to be a quick guide for different use cases.
Python and pandas are a great team for data science. But what if you need to deliver a script to a Windows client who does not have Python installed?
This is a quick tutorial for converting Python scripts (
.py) to standalone, one-file Windows executables (
Get a 20Mb exe file that is fully functional on every Windows machine!
Have you ever wondered how HyperLogLog works? Or have you never heard of it at all? In this post I explain the wonderful algorithm of Flajolet et al. from scratch and in a very simple manner.
Flat hunting can be a big pain - particularly for European metropoles. Most flat search platforms already offer good filter options but until now, I didn’t see any with custom geographic filters. Apart from drawing your own area of interest on a map, you seldomly find filters such as “How far is the next metro stop?” or “How close are important facilities?”.
Leaflet-Hexbins is a powerful tool to aggregate data and visualize it quickly on a map. It can size the hexbin radius based on a feature values. But what if we used HyperLogLog data to preserve user-privacy? This post will provide a convenient way to quickly perform on-the-fly HyperLogLog unions for leaflet-hexbins.
No more backend-constraint for HyperLogLog
There are many HyperLogLog implementations out there but few work as well as postgres-hll and js-hll. They can even talk to each other by exchanging hexstrings! Usually postgres-hll is pretty much the standard extension to use, when dealing with HyperLogLog but is obviously bound to a postgres database running somewhere. With js-hll, the backend-constraint for HyperLogLog is gone, just so that users can perform any HyperLogLog action in their frontend!
Querying Postgres with Python Fastapi Backend and Leaflet & Geoman Fronted - Applying Geometry Filters
How to query a database with a user-defined geometry drawn on a Leaflet frontend?
A very common use case for map applications are custom filters. Either thematic, temporal or value-based filters play a significant role but probably in a geographical context the most dominant one might be spatial filtering. In this blog post, I describe a simple boilerplate setup based on postgres, fastapi and geoman.