ducker VS ibis

I made a docker image with a number of extensions already installed and enabled so you can start using DuckDB with the lowest friction.

`alias dckr='docker run --rm -it -v $(pwd):/data -w /data duckerlabs/ducker'`

then `dckr` gives you a DuckDB shell with PRQL, httpfs, json, parquet, postgres, sqlite, and substrait enabled.

For example, to get the first 5 lines of a csv file named "albums.csv", you could run it with PRQL

```dckr -c 'from `albums.csv` | take 5;'```

https://github.com/duckerlabs/ducker

I really don't understand the appeal of dbt vs a proper programming language. The templating approach leads to massive spaghetti. I look forward to trying out something like Ibis [0]

0: https://ibis-project.org/

ibis – portable Python dataframe library

The main benefit is that you get a Python (or R, Julia or Rust) interpreter. So you can evaluate code. A good example of the value of this is the Ibis docs which use Quarto: https://ibis-project.org/

Ive found polars quite intuitive, though for python, I lean more towards [ibis](https://ibis-project.org/). The interface is nearly identical, but ibis has the benefit if building sql queries before pulling any actual data (like dbplyr) — whereas polars requires the data to be in-memory (at least for rdb’s, though correct me if Im wrong)

this to me seems like a good argument for only using ibis, but Im happy to be convinced otherwise

Please add Ibis Birdbrain https://ibis-project.github.io/ibis-birdbrain/ to the list. Birdbrain is an AI-powered data bot, built on Ibis and Marvin, supporting more than 18 database backends.

See https://github.com/ibis-project/ibis and https://ibis-project.org for more details.