jt_b

Astro is nice, but its a different model than Nuxt, more suited to static sites.

Feels like Cloudflare would have been a much better alignment, given they had some great integrations already.

Hope they are able to maintain some level of autonomy.

Fortunately there are a lot of great alternatives to the ESRI lock-in, and FOSS has a long and rich tradition in Geo.

oh-my-zsh default prompt mode for git branches is for me! super clean. need to familiarize myself with some more of their shorthand commands.

I think they probably like having an GDP 25x larger than North Korea's. Gets a lot harder to export your products around the world when you're squared off against the US.

Not sure about petabytes, but pretty sure Brandon Liu of Protomaps is hosting all the daily protomaps extracts via R2. Not sure what the egress usage is.

document.querySelector(".my-auto").setAttribute("style", "text-align: left;");

I'm actually having fun reading it after applying that.

HN's aesthetic has grown on me honestly!

They're the ones you can't comment on.

I've seen (but not used) this tool recently, which seems like it does a similar thing. Curious if it is any better experience.

https://github.com/bahdotsh/wrkflw

I haven't/wouldn't use it because I have a decent K8S ollama/open-webui setup, but docker announced this a month ago: https://www.docker.com/blog/introducing-docker-model-runner

I'm not sure if they are "apps" per se, but both are these are running python code via pyodide in the browser:

https://marimo.app/ https://pydantic.run/

don't see any looping expression functionality in the PEP

Perfect use case for https://github.com/urchade/GLiNER

Prefect is amazing. Built out an ETL pipeline system with it at last job and would love to get it incorporated in the current one, but unfortunately have a lot of legacy stuff in Airflow. Being able to debug stuff locally was amazing and super clean integration with K8S.

they are great little devices. Has its own tailscale app too and can be used as an exit node! useful for me as the TV is pretty close to the fiber box on the wall.

Love Go (and async python, for different reasons) but miss me with the gRPC unless you are building hardened internal large enterprise systems. We adopted it at a late stage startup for a microservices architecture, and the pain is immense.

So many issues with type duplication due to weird footguns around the generated types. Lots of places where we needed to essentially duplicate a model due to the generated types not allowing us to modify or copy parts of a generated type's value and so forth.

Can you talk more about what an implementation of such a semantic layer would look like?

You want a shape that can represent an approximately equal area, anywhere on a 3 dimensional surface.

Polars seems cool, but not willing to invest in adoption until Geo support is more mature. I find I'm preferring to run most operations I'd use dataframe libraries for in local SQL via DuckDB anyways.

> The problem with Parquet is it’s static. Not good for use cases that involve continuous writes and updates. Although I have had good results with DuckDB and Parquet files in object storage. Fast load times.

You can use glob patterns in DuckDB to query remote parquets though to get around this? Maybe break things up using a hive partitioning scheme or similar.

I thought about this some more and did some research - and found an indexing approach using HNSW, serialized to parquet, and queried from the browser here:

https://github.com/jasonjmcghee/portable-hnsw

Opens up efficient query patterns for larger datasets for RAG projects where you may not have the resources to run an expensive vector database

I have tinkered with using DuckDB as a poor man's vector database for a POC and had great results.

One thing I'd love to see is being able to do some sort of row group level metadata statistics for embeddings within a parquet file - something that would allow various readers to push predicates down to an HTTP request metadata level and completely avoid loading in non-relevant rows to the database from a remote file - particularly one stored on S3 compatible storage that supports byte-range requests. I'm not sure what the implementation would look like to define sorting the algorithm to organize the "close" rows together, how the metadata would be calculated, or what the reader implementation would look like, but I'd love to be able to implement some of the same patterns with vector search as with geoparquet.

I think they're talking about using it to power inference for self hosted user facing applications.

Nice, thanks for the suggestion. I got it set up just before leaving town for a few days, so have been doing a little tinkering with it. I was hoping to have a setup with LM Studio, where my laptop could use the API Server from the mini over the TS network. Unfortunately doesn't seem to be the case, so I'll set up a configuration like you mentioned to just have a global client from any device on the netowrk.

It's very cool to be able to have access to such a high horsepower machine from anywhere though. Next step is figuring out the networking interface to be able access the host GPU/ollama API from pods running in a Colima VM/k3s cluster setup.

Thanks for all your writing on these topics Simon! It has turned me from a bit of a naysayer to an optimist around this tooling, especially being able running stuff locally with access to tools. Have an M4 Pro mac mini arriving this week to have a similar self hosted setup over tailscale.

Not FOSS, but this is kind of what Zenhub was/is, right?

The pattern can be useful for multiple parties, for different reasons, some nefarious. Some users are definitely interested in higher "signal" content, especially when you follow enough accounts that consuming even a small fraction of the content isn't feasible.

> Static or infrequently updated vector tiles can be generated from OSM data by a number of tools, but those most popular right now are https://github.com/systemed/tilemaker and https://github.com/onthegomap/planetiler

this is the first I've seen of these alternative tools compared to using Tippecanoe(https://github.com/felt/tippecanoe). Are they considered to be higher performance?

Thanks for this reminder. The Robert Solomon scene in Waking Life re: Sartre had a profound impact upon upon me as a teenager and spurred my interest in Kierkegaard, but it has been several years since I have considered him.

Great to see that many of his lectures are available online.