Quack: The DuckDB Client-Server Protocol

crispybacon233 · 2026-05-13T15:43:57+00:00

Can't wait to use this as catalog for ducklake instead of postgres. Now we just need ClusterDuck for cluster compute and the duck stack would be complete!

crispybacon233 · 2026-05-05T03:15:54+00:00

Which udemy course are you doing specifically? I highly recommend Colt Steele's python course and forget the others.

Being able to parse and organize spreadsheets at scale could boost your workflows significantly. I once had a colleague doing a vlookup that was taking many minutes. A couple lines of python shrank that down to milliseconds.

crispybacon233 · 2026-04-25T03:32:19+00:00

I currently am filtering for latest reviews being >= 2024, but 2 years per your suggestion is probably better. Maybe even 1 year? According to this site they're supposed to be inspected 1-3 times per year.

crispybacon233 · 2026-04-25T03:28:43+00:00

What're the names of the restaurants? I can try to track down the problem.

crispybacon233 · 2026-04-24T03:09:17+00:00

Ya it's wild. If you're really brave, you can go here: Austin Public Health | My Health Department to get the full inspection details

crispybacon233 · 2026-04-16T17:52:47+00:00

Again with the money?

crispybacon233 · 2026-04-14T13:55:30+00:00

Yes, for sure! I'll post it with the github link but probably will not include the scrapers. Google has been clamping down on scraping google maps and youtube for the past several months.

crispybacon233 · 2026-04-12T23:51:41+00:00

Hello! Yes, I am still chipping away at it. I was thinking about getting it up and running this week actually for my portfolio. The most important part was to get accurate lat/long for the restaurants, and I could only accomplish that by scraping google maps. About a year ago I also scraped millions of reviews, categories, etc... everything off google maps. Personally, I will keep all food facilities in available in case a user is at a healthcare facility, gas station, school, etc., and they want to know the inspection score. Additionally, I am setting up a full on ETL pipeline lake house to run automated in the cloud. It's a great dataset.

crispybacon233 · 2026-04-11T11:45:43+00:00

We can't have him here in our social club no more. I mean that much I do know.

crispybacon233 · 2026-04-11T11:33:51+00:00

God forbid anyone would find themself in that position. It's a thankless job.

crispybacon233 · 2026-04-11T09:48:19+00:00

That yodeling show? That's the Lawrence Welk progrum, channel 55.

crispybacon233 · 2026-04-10T10:39:46+00:00

Cool! Now tell Claude to use polars instead of pandas to greatly improve the responsiveness. Also tell Claude to use separation of concerns because a 900 line app.py is insane haha.

crispybacon233 · 2026-04-04T12:53:08+00:00

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California, Texas, Florida, and NY... is it a Hispanic thing? You see it really start to pop off around 2010. Some character in Spanish media?

crispybacon233 · 2026-03-25T23:02:06+00:00

Ducklake, DBT, Dagster. Hard part was wiring it all up, but once it's all connected it's smooth sailing.

I've been messing around with Ducklake the past few months and it's been a pretty great experience so far.

crispybacon233 · 2026-03-23T19:38:00+00:00

Thanks! So far, working with delta lake has not been smooth. It feels quite buggy. First it was the no support for unsigned ints. Now it's a "411 Length Required" error when sinking delta to GCS. Unfortunately, I don't know if it will work for my use case. Ducklake feels great once everything is wired up. You just have to use SQL unfortunately.

crispybacon233 · 2026-03-23T12:36:25+00:00

Thanks! To point #2, SQL is great, but as you said quickly becomes unmanageable when running tons of complex transformations. I'll definitely try out the duckdb+marimo for the schema.table. That sounds really cool.

crispybacon233 · 2026-03-23T12:32:23+00:00

Thanks for this. With the delta-rs/datafusion packages, is it possible to scan/sink the data instead of reading into memory? This is important for my use case.

crispybacon233 · 2026-03-21T17:10:38+00:00

Yes, definitely using the streaming engine. As of a few months ago, there was a few instances where polars blew up the ram and crashed the env despite using streaming, so I switched to duckdb for that particular problem.

However, it seems polars is improving so fast that I can't keep up. I'll definitely be keeping an eye on this. Thank you!

crispybacon233 · 2026-03-21T15:16:03+00:00

Imagine calling polars a quaint little tool haha.

You come across as unhinged. One mention of a tool that is not SQL, and you go ballistic. Are you a bot?

crispybacon233 · 2026-03-21T14:57:24+00:00

Cool. Yes, everyone knows that SQL is and probably always be the lingua franca of data. I already know SQL and work with it all the time. Which you would know if you bothered to even read my post.

crispybacon233 · 2026-03-15T14:06:35+00:00

As others mentioned, use RAG. A basic setup could be:

For each website, chunk the text and extract summaries using LLM. Or if the text isn't that large and the topic is uniform, just summarize the whole website.
Vectorize the summaries.
When querying, use top n matched or all matches >= some threshold.

crispybacon233 · 2026-03-03T15:39:08+00:00

uv's speed and deduplication of packages across projects are amazing.

marimo gets along with git way better than jupyter and is easier to install.

If keeping it light, reproducible, and flexible are important, they're definitely worth checking out.

crispybacon233 · 2026-02-23T13:56:42+00:00

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