davidkwast

For that use case we have Tiff with float and lossless compression.

https://gdal.org/en/stable/drivers/raster/gtiff.html

That is true but you can determine a baseline from Tiff.

In the GIS world we have a Cloud Optimized Geo Tiff. It is almost a standard now. This better than go to another format like Jpeg2k or ECW.

Tiff is an extendable format. Bit I am not saying that it can be better than JpegXL. Just a curiosity.

On Linode you can run any Linux for $5/month with 1gb of RAM and 25gb of storage

I just found this video on YouTube now:

https://youtu.be/A8fDr7Rr7yM?is=cHwOQVrli9oXLdqY

Best comment

Rainfall

And at least the forest soil has the same amount of carbon stored.

I usually like to write elegant code using Python and frameworks like Django.

The pleasure comes from the "the only right lines of code" instead of "the most lines of code".

Nice advice

More info here:

https://x.com/ayubio/status/2068195735279923267?s=20

Everyone in Brazil capital cities are receiving extreme alert messages with just the text: "misanthropi"

I would use a hash of the body content (the query) as a URL parameter

/?hash=123456789

So the majority of the hardware should stay on the moon where latency isn't so critical. There the cooling won't be the problem.

It is so simple that I had to look very slowly to understand. Nicely done.

As what we say here in Brazil:

"The world doesn't go round. It flips over!"

Your comment remembered me of ESA normalization value for the Sentinel-2 level-2 satellite image quantization.

Something like this:

Digital Number DN=0 remains the “NO_DATA” value

For a given DN in [1; 1;215-1], the L2A SR reflectance value will be:

L2A_SRi = (L2A_DNi + BOA_ADD_OFFSETi) / QUANTIFICATION_VALUE

https://sentiwiki.copernicus.eu/web/s2-products

All Python versions are LTS if you consider 5-year a good measure.

https://devguide.python.org/versions/

It is the same for me. Predicability is better than any optimization.

"Python 3.14 shipped with a new incremental garbage collector. However, we’ve had a number of reports of significant memory pressure in production environments.

We’ve decided to revert it in both 3.14 and 3.15, and go back to the generational GC from 3.13."

Sounds the right move for me

You can use both. In the mountains I would appreciate redundancy.

RISC-V can be essential for this open future

Still better than my Lenovo

I saw that in the code on the github repo

I think LLMs are accelerating us toward a Dune-like universe, where humans come before AI.

Wow. I saved the link for emergencies. And I sent it to all my team. It is like a diff tool but to advance the schema.

I don't think MariaDB ColumnStore has any kind of advantage. It is just an append-only storage format with some columnar concepts.

https://vettabase.com/mariadb-columnstore-sql-limitations/#I...

This ColumnStore is very simple and just do table scans sequentially on every query. It doesn't support indexes and unique constraints. It is almost an append-only serialization file format, but with some columnar concepts.

Nice

I am hosting user data from the database. It is very easy with this stack: - PostgreSQL with PostGIS - Django with MVT-tiles plugin - MapLibre

I do. The pros are hosting own data and have total control over stack and cloud hosting. The cons are having to code your own stack and do cloud management. I use PostGis to storage and serve vector tiles. And I use a simple backend with AWS S3 to store and serve raster data (GeoTiff COG).