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Comment by klreslx | Hacker News Reader

I don't see the point. People who want Jupyter or an IDE know where to find it. Other people who want the basic REPL and mostly use editors anyway are annoyed.

Well, perhaps the usual suspects can get another infoworld self-promotion article out of it.

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There's a tremendous power with defaults and with "batteries included".

The same people removed distutils, which is why at my company we had to update several internal C-extensions.

In these decisions the only thing that matters is if Microsoft, Facebook, Bloomberg or one of their employees is pleased.

>The same people removed distutils

Yes; it's extremely cruft-filled and nobody wanted to / had the skills to keep the standard library version maintained. There's a note in the Setuptools documentation somewhere about how distutils was deemed fundamentally unfixable, and it doesn't come across like the hacks Setuptools was applying on top of distutils were particularly well understood by anyone.

>In these decisions the only thing that matters is if Microsoft, Facebook, Bloomberg or one of their employees is pleased.

I don't think there's good evidence for this, and the current case is certainly not convincing. Why would they want distutils removed - as opposed to that motivation come from the devs who would otherwise be responsible for its bugs?

It looks like a lot of care went in to disclosing this and providing replacements. Can I ask what you were using it for?

https://peps.python.org/pep-0632/

Not the one you are asking, but NumPy literally converted to meson because of the deprecation. There was tons of pain for so many extensions.

This pain generates job security for the bigcorp employees and grief for anyone else.

Super helpful, thanks! The NumPy page on the migration has some details on the differences:

    > ... [Here] are the numpy.distutils features that are not present in setuptools:
      * Nested setup.py files
      * Fortran build support
      * BLAS/LAPACK library support (OpenBLAS, MKL, ATLAS, Netlib LAPACK/BLAS, BLIS, 64-bit ILP interface, etc.)
      * Support for a few other scientific libraries, like FFTW and UMFPACK
      * Better MinGW support
      * Per-compiler build flag customization (e.g. -O3 and SSE2 flags are default)
      * a simple user build config system, see site.cfg.example
      * SIMD intrinsics support
      * Support for the NumPy-specific .src templating format for .c/.h files

https://numpy.org/doc/stable/reference/distutils_status_migr...

I never did understand this. It appears that they were maintaining their own fork of distutils anyway (and if you open up a latest-version wheel today you should still see it included); so why did the standard library removal cause a problem?

Because the "fork" still relied on the presence of the included distutils.

But it's open source. Couldn't they just vendor it? Not like that would noticeably bloat a wheel that's already close to 20 MB on some platforms.

The deprecation of distutils caused a ton of havoc for e.g. FreeCAD

I won't argue with that, but I would like to understand why.

If I'm on the right path with these forum threads, it looks like there were issues with how Debian packages python?

https://forum.freecad.org/viewtopic.php?t=67985

https://github.com/FreeCAD/FreeCAD/pull/6753

https://ffy00.github.io/blog/02-python-debian-and-the-instal...

I don't know the details, all I know is because of that I can't currently install FreeCAD from Fedora repositories which is super annoying, and IMO not the fault of either Fedora or FreeCAD...

If Python is going to include a REPL (which I think it should), it might as well include useful features that people expect from a modern REPL. (That being said, I personally always install ipython...)

They really don't. The Python userbase has a very high percentage of beginners at any time, and trying to move them into Jupyter or an IDE before they understand fundamentals, usually just makes it much harder to help them with programming problems (because they don't know what's language functionality and what comes from their tools; they don't know anything about the virtual environment the tool is managing; they aren't prepared for an IDE to identify problems that are different from what the runtime chokes on; etc.)

The basic REPL causes serious problems for beginners, and the differences in this REPL are (intentionally or not) largely geared towards fixing those problems. Most notably, beginners can't reliably paste in code examples from tutorials. Either there's a use of `input` which eats the next line of code as interactive input, or a blank line inside a block which the REPL interprets as end-of-code (causing the rest of the block to report `IndentationError`s despite being correctly indented for the intent of the code). They also commonly get tripped up by `help` and `exit` being Python callables rather than REPL commands, and get put off by the lack of built-in screen clearing. (Historically - as it turns out from forum discussion - the Python devs have expected that people actually quit the interpreter with ctrl-D/ctrl-Z, and clear the screen with the terminal emulator's functionality for doing so.)

Maaaybe color highlight can annoy some purist, but multiline edit and cursor movement are the bare minimum. Either add these features or get rid of the battery included Repl in favour of third parties.

From my experience working with the default repl in e.g. a docker container is extremely frustrating comparing to ipython, and I don't want to be installing ipython and its multitude of dependencies everywhere

I've never actually used these industrial-strength "containers" before, but I had understood that they're supposed to be primarily for deployment, or at least some automated testing step in a big CI system. Why would the REPL come into play for these use cases?

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