Hi all,

TL;DR: NumPy should endorse some or all of the new SPECs if we like
them.  If you don't or do like them, please discuss, otherwise I
suspect we will propose and endorsing them soon and do it if a few core
maintainers agree.

---


The Scientific Python project has the SPEC process to write up helpful
tips/patterns [1] with the idea that projects "endorse" them to
indicate that we think following the SPEC is a good idea.

One example probably known best is SPEC 0, which is NEP 27 (the
suggested minimum supported versions for dependencies, e.g.
Python/library versions).

There has been a lot of work recently to write some new SPECs, and the
following ones are up for endorsement by NumPy:

* 1 -- Lazy Loading of Submodules and Functions
  https://scientific-python.org/specs/spec-0001
* 6 -- Keys to the Castle
  https://scientific-python.org/specs/spec-0006/
* 7 -- Seeding Pseudo-Random Number Generation
  https://scientific-python.org/specs/spec-0007/
* 8 -- Securing the Release Process
  https://scientific-python.org/specs/spec-0008/

Endorsing them means we think they are good guidance for projects, not
necessarily strictly following them [2].

Without input, I suspect we may endorse them soon (if a few maintainers
give a thumbs up).  But of course it would be great to discuss and
maybe improve the SPECs in the progress!

SPEC 7 is important, because it describes how we would like other
libraries to use the new random number generation API in the future
(but actually doesn't apply directly).

Cheers,

Sebastian



[1] The SPECs are not necessarily fixed.  If you think they are missing
a note/solution, we can modify them.

[2] With it's flat namespace, I am not sure e.g. lazy-loading is of
much use to NumPy (just like we have longer compatibility than SPEC 0).

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