Python 2 to Python 3 in a Django codebase ... may be a full rewrite anyway.

Many people migrated Django projects from 2 -> 3. Certainly something that takes effort, but hardly a rewrite.

Nothing like a full rewrite. I migrated multiple projects, but while there is a significant amount of work involved its a tiny fraction of what a full rewrite would require.

Its fine, I ported quite a few Django libraries to python 3 at the time just because I wanted to use them.

2to3 gets you pretty far and theres not much in the rest.

Did it a couple of times. Not something you can do with your eyes closed, but not even close to the nightmare of upgrading a JS application or upgrading a rails app.

All items had stats / skill changes, no?

Rust, C#, Java, Go and maybe even Erlang would suffice for modern stack and IO heavy and performant workloads.

Every DataFrame library with a significant user base uses function chaining because that's the best workflow for such stuff. Also notebook support / magic cell comments for iterative EDA.

Python: polars-py, pandas, pySpark JVM: Spark R: R

Go can't compete with this even with SIMD support.

They would if they would care.

That's how you get 3 different values for a core KPI in 3 dashboards.

Then you look under the hood of the dashboards, only to see that not a single one follows the official definition of the business.

exactly this.

As a mainly Python guy (Data Engineering so new project for every ETL pipeline = a lot of projects) uv solved every problem I had before with pip, conda, miniconda, pipx etc.

How about fast compilation? :-\

Developer productivity matters...

Yes.

It's a rust library that you can use to run sql queries against a database. It also inspects the database at compile* time to figure out the type of each column in your query so that your code is type-safe.

* Or in your editor as you're writing code.