I was completely unaware of this project until today. CPython is getting a JIT (just-in-time) compiler!

Python 3.15’s JIT is now back on track | Ken Jin’s Blog
https://fidget-spinner.github.io/posts/jit-on-track.html

#PythonLang #Python

Python 3.15’s JIT is now back on track

Python 3.15’s JIT is now back on track

Ken Jin’s Blog
Just got finished setting up sqlc tooling for a monorepo with Go and Python. Now it will generate code for each language based on a single set of *.sql files with query statements. Python support is just beta, but these queries are not complicated.

#GoLang #Python #PythonLang #sqlc #CodeGen
Compile SQL to type-safe code

Compile SQL to type-safe code

sqlc.dev
@tommytang.bsky.social On #ComputerLanguages for #Bioinformatics There is an era of #Bioinformaticians who learned #R #RLang back when #Python #PythonLang wasn't very good at statistics/plotting. More recently, the trend has shifted towards the latter.

Trying to do some data science on the crates.io bulk DB dump.

The following two crates are "fun" for python:

https://crates.io/crates/nan
https://crates.io/crates/NULL

#datascience #rustLang #pandas #pythonLang

crates.io: Rust Package Registry

#RubyLang is an extremely capable programming language. I've always wondered why 99% of the code for #LLM and #AI / #ML is done in #PythonLang and (for no obvious good reason) #JavaScript, #TypeScript, or #ECMAscript.

The on-ramp for Python may be easier, but it's overall less consistent and IMHO more obscure and less capable for introspection, DSLs, and for metaprogramming, so why is its ecosystem bigger for AI/ML? I wish someone would explain that in a non hand-wavey way.

"Rust usage for Python extensions surged 22% in one year as developers choose memory safety and C-level performance over traditional approaches."

https://thenewstack.io/rust-pythons-new-performance-engine/

#rustlanguage #rustlang #rust #pythonlanguage #pythonlang #python

Rust: Python's New Performance Engine

Rust usage for Python extensions surged 22% in one year as developers choose memory safety and C-level performance over traditional approaches.

The New Stack
Como Leer Una API con Python

En este tutorial aprenderás a Como Leer Una API con Python, paso a paso y siguiendo las buenas prácticas de Python.

Blog de Programación y Desarrollo - Nube Colectiva
getting back into Python is weird because like every time I do there's a new fresh hotness to theoretically end all hotnessess re: package installation

and then the next time I get back in people are like, "that was such horseshit,
this is the thing"

"wheel is bad, but poetry: so good!"
"poetry is
shit, something something else is good (I dunno I kinda don't remember the name for this one)"
"we don't need that old one, we have WHEEL!"

motherfuckers

(yes, these are real things)

#techPosting #pythonLang #pythonPackaging

Python at the Speed of Julia - Glass Notebook

The article explores various methods and tools that can be utilized to enhance Python’s execution speed without sacrificing its simplicity and readability.

#Python #JuliaLang #PythonLang #performance #programming #CompSci #ComputerScience

https://glassnotebook.io/r/dxJTYbJBmPR1X3NQUfwXB/99_python_at_the_speed_of_julia.jl

Glass Notebook

There's been recent discussion about #POSIX & the #bash_shell. Some shells are awesome but don't even pretend to follow the POSIX standards. The #fish_shell is a good example.

Portability can be useful, but context matters too. Why deviate from standards? #LSB excludes #RubyLang but specifies #Perl & #PythonLang. #XDG is needlessly confusing. Distros may deviate from the #Linux #FHS because "reasons."

Goals & targets matter more than portability for its own sake.

https://fishshell.com/docs/current/design.html

Design — fish-shell 4.4.0 documentation