@weavejester It is highly depends on your setup and files you are working on. For really big files I use vim too. But for regular software development in #GoLang with gopls as lsp server I have no issues at all. But I heard lsp server for #Python could be very slow.
This post was 5 years in the making, @shazow and I made a bet about whether "six", the #Python 2/3 compatibility shim, would still be a popular package in 2025:
https://sethmlarson.dev/winning-a-bet-about-six-the-python-2-compatibility-shim
๐ Learn Python from scratch!
Step into the world of coding with the Introduction to Python Programming for Beginners ๐๐ป crash course.
Fun, easy, and beginner-friendly!
๐ฅ Watch here: https://www.youtube.com/watch?v=bLSTVnkDfUg
#python #coding #programming #learn #computerscience #code
Following DjangoCon US, people are actively working on two new Django-simple-deploy plugins: one for Render, and one for Python Anywhere. I'm really excited about both of these! (And there are two more that may be progressing as well.)
I've been wondering if django-simple-deploy could define a number of common use cases, and then configure initial deployments on each platform that target that use case.
Hola #fediverso! #TZAG ๐
Se vienen cositas en el blog! ๐
Y como ya tengo el esquema de red andando en #gns3, tambiรฉn saldrรก mini clase para el canal de youtube ๐
Si quieren seguir el canal y no perderse la publicaciรณn, quedan invitados! ๐
https://www.youtube.com/juncotic?sub_confirmation=1
De hecho, si usan #rss y quieren seguir el blog, tambiรฉn pueden ๐๐
#gnu #linux #learning #softwarelibre #codigoabierto #sysadmin #tcpip #wireshark #python #flask #ssh #iptables #scripting #bash #firewall

๐ ๐ฃ๐ฎ๐ฐ๐ธ๐ ๐ถ๐ ๐ฐ๐ฒ๐น๐ฒ๐ฏ๐ฟ๐ฎ๐๐ถ๐ป๐ด ๐ฐ๐ฌ ๐๐ฒ๐ฎ๐ฟ๐ ๐ผ๐ณ ๐๐ ๐ฐ๐ฒ๐น!
From humble spreadsheets in 1985 to powering analytics in the Gen BI era, Microsoft ๐๐ ๐ฐ๐ฒ๐น has ruled data for four decades.
That is why we are marking this milestone with ๐ฐ๐ฌ% ๐ผ๐ณ๐ณ ๐ฏ๐ฒ๐๐๐๐ฒ๐น๐น๐ถ๐ป๐ด ๐ฃ๐ฎ๐ฐ๐ธ๐ ๐๐ ๐ฐ๐ฒ๐น ๐ฒ๐๐ผ๐ผ๐ธ๐.
๐ ๐๐ ๐๐ฒ๐ป๐ฑ๐ถ๐ป๐ด ๐๐ ๐ฐ๐ฒ๐น ๐๐ถ๐๐ต ๐ฃ๐๐๐ต๐ผ๐ป ๐ฎ๐ป๐ฑ ๐ฅ by Steven Paul Sanderson II, MPH, David Kun โ bring analytics languages into Excel for advanced manipulation and visualization. Buy here >> https://lnkd.in/gVSnEfzj
#Excel40 #Microsoft #Excel #R #Python
We had an excellent conference at Perugia @earthmonitororg Global Workshop 2025. If you missed it, we video-recorded ๐ผ all talks: https://www.youtube.com/playlist?list=PLXUoTpMa_9s01Bgg1ju3Jr3-14eilWHTB
Topics covered include: #OpenEO #CDSE #Copernicus monitoring of #deforestation Big vector and gridded data, workshops in #Python data fusion in climate science, hydrology & novel global #soil data sets
๐ง some videos (3-4) unfortunately due to technical problems have poor video/audio quality. 2026 Global Workshop is coming to: Barcelona!
Python - ยซ Libre ร vousโฏ! ยป du 23 septembre 2025 - Podcasts et rรฉfรฉrences https://linuxfr.org/news/python-libre-a-vous-du-23-septembre-2025-podcasts-et-references #radio_cause_commune #libre_ร _vous #Communautรฉ #python
Minimizar al tray un programa hecho en PyQt5 https://myblog.clonbg.es/minimizar-al-tray-un-programa-hecho-en-pyqt5/ #Programaciรณn #PyQT #Python https://clonbg.es

๐ข๐จBlosc2 3.9.1 Released! ๐จ ๐ข
With this release we further extend array API standard (https://data-apis.org/array-api/latest/index.html) compliance, adding around 70 new functions, methods and attributes ๐๐๐ .
This includes:
โข Memory-optimised linear algebra routines: tensordot can be up to 12x ๐
๐๐๐๐๐ than NumPy for large arrays ๐งฑ!
โข Optimised numerical computation routines โฉ : functions like hypot are 10x ๐
๐๐๐๐๐โกthan NumPy!
See here for benchmarks: https://ironarray.io/blog/array-api
#Compute
#Tensor
#LinearAlgebra
#Python

Comparison of Structured output control across popular LLM providers - OpenAI, Gemini, Anthropic, Mistral and AWS Bedrock - with examples in Python
https://www.glukhov.org/post/2025/10/structured-output-comparison-popular-llm-providers/
#llm #Python #ai #OpenAI #google #Gemini #Anthropic #Mistral #AWS
You can track your carbon footprint when training #ML models or running any other type of #python code with #codecarbon
https://github.com/mlco2/codecarbon
Here is a really good tutorial on Colab
How to Track Emissions when Training Machine Learning Models