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What Color is Your Function? – journal.stuffwithstuff.com
What Color is Your Function? – journal.stuffwithstuff.com

An amusing take on async/await being sprinkled all over a language. While this is aimed more at the JavaScript crowd, I think the Python folk can relate too.

There are some good points here, and some good descriptions of the sort of frustration that can be felt. At the same time there are also some not-quite-sensible aspects to it as well.

Still a fun read.

·journal.stuffwithstuff.com·
What Color is Your Function? – journal.stuffwithstuff.com
wyuenho/emacs-pet: Tracks down the correct Python tooling executables from your virtualenvs so you can glue the binaries to Emacs and delete code in init.el
wyuenho/emacs-pet: Tracks down the correct Python tooling executables from your virtualenvs so you can glue the binaries to Emacs and delete code in init.el
What looks to be a module for Emacs that helps find the right venv for a project; I think. Saving this to look at at some point in the future.
·github.com·
wyuenho/emacs-pet: Tracks down the correct Python tooling executables from your virtualenvs so you can glue the binaries to Emacs and delete code in init.el
(How to Write a (Lisp) Interpreter (in Python))
(How to Write a (Lisp) Interpreter (in Python))
This page has two purposes: to describe how to implement computer language interpreters in general, and in particular to build an interpreter for most of the Scheme dialect of Lisp using Python 3 as the implementation language. I call my language and interpreter Lispy (lis.py). Years ago, I showed how to write a semi-practical Scheme interpreter Java and in in Common Lisp). This time around the goal is to demonstrate, as concisely and simply as possible, what Alan Kay called "Maxwell's Equations of Software."
·norvig.com·
(How to Write a (Lisp) Interpreter (in Python))
How to improve Python packaging, or why fourteen tools are at least twelve too many
How to improve Python packaging, or why fourteen tools are at least twelve too many
"Join me on a journey through packaging in Python and elsewhere. We’ll start by describing the classic packaging stack (involving setuptools and friends), the scientific stack (with conda), and some of the modern/alternate tools, such as Pipenv, Poetry, Hatch, or PDM. We’ll also look at some examples of packaging and dependency-related workflows seen elsewhere (Node.js and .NET). We’ll also take a glimpse at a possible future (with a venv-less workflow with PDM), and see if the PyPA agrees with the vision and insights of eight thousand users."
·chriswarrick.com·
How to improve Python packaging, or why fourteen tools are at least twelve too many