Peter Bittner

@peterbittner
28 Followers
45 Following
131 Posts
Developer of people, companies and code. Older tweets on https://x.com/peterbittner
memberfsfe.org,python.it,python.org
PyClean v3.6.0 released! Fixes the ignore flag to be considered when used in combination with erase. Try it with #conda or #uv now! `uvx pyclean`. https://pypi.org/project/pyclean/ #python #bytecode #debris #cleanup #development #python3 #cpython #pypy #Linux #macOS #Windows
pyclean

Pure Python cross-platform pyclean. Clean up your Python bytecode.

PyPI
Steuererklärung im Kanton #Thurgau mit eFisc auf #NixOS. Geht nicht, weil der #Kanton #TG nur #Ubuntu und #SuSE unterstützt? Seit heute kein Problem mehr. #eFisc installieren mit dem #Nix #Package von @painless_software. https://gitlab.com/painless-software/efisc-nix #Switzerland #Swiss #tax #Linux #Java #Abraxas
painless-software / efisc-nix · GitLab

Nix Packages für die eFisc Steuererklärungssoftware des Kanton Thurgau (TG), Schweiz

GitLab
Looks like the next-generation low-JavaScript coding solution has arrived. Django LiveView, the HTMX competitor that passes HTML via WebSocket. Looking forward to getting my hands dirty with it! 😍 🐍 🐴 https://django-liveview.andros.dev/ by @andros #django #python #lowjs #htmx #websocket
Django LiveView

Framework for creating Realtime SPAs using HTML over the Wire technology.

PyClean v3.5.0 released last week! Adds Complexipy debris removal. Try it with #conda or #uv now! `uvx pyclean`. https://pypi.org/project/pyclean/ #python #bytecode #debris #cleanup #development #python3 #cpython #pypy #Linux #macOS #Windows #complexipy
pyclean

Pure Python cross-platform pyclean. Clean up your Python bytecode.

PyPI

Das war in der agilen Community los (Woche vom 05.12. – 12.12.)

Wir hinterfragen, ob wir uns mit "Sprints" eigentlich nur kaputt rennen, lachen (oder weinen) über Teams mit 17% Zielerreichung und diskutieren, ob Agile im Zeitalter der "Enshittification" überhaupt noch eine Chance hat. Wenig Theorie, viel schmerzhafte Praxis.

Hier die Highlights 👇

1/4

#Agile #AgilePuls #Scrum #Enshittification

RE: https://mastodon.social/@painless_software/115667386959330889

I'm working in a team that just completed a sprint with 17%(!) completion of the planned work. Almost *everything* is spilled over to the next sprint. It's ridiculous.

Large organizations fill sprints to prove they are busy. But what are sprints designed for? To give #confidence! You can't give confidence when you're constantly spilling over.

Just use a #Kanban board to show off how busy you are. Don't engage in #enshittification of #Scrum, treating "spillover" as a chic, must-use word. #agile

How to modernise your requests-based API consumption code in #Python as if it were 2025. https://dev.to/dentedlogic/what-modern-python-uses-for-async-api-calls-httpx-taskgroups-3e4e #httpx #asyncio #requests
What Modern Python Uses for Async API Calls: HTTPX & TaskGroups

Multiple API calls in Python are usually written in a way that makes them slow You’ve...

DEV Community

RE: https://mastodon.social/@nicklockwood/115553420045122380

Mind-blowing explanation of the current state of #AI and the false promise of #vibe #coding. Read all 10 posts in this enlightening thread! 💡🤯

But the idea that natural language makes it easier for non-programmers to program is a misunderstanding

Programming is not about transcribing English to code, it's the art of turning vague requirements into concrete ones - identifying and filling in the blanks so that an imprecise spec becomes precise

When you "vibe code" you are asking an LLM to do that work - and they are remarkably good at it - but that is not *programming*, because you are not identifying and eliminating those ambiguities

A great write-up on #async vs #multiprocessing in #Python. Many teams face that problem for data science tasks with external data consumption (e.g. using #Kafka), but don't understand the underlying mechanics. There's no magic bullet; engineering is a #discipline. https://pythonspeed.com/articles/two-thread-pools/ by @itamarst #datascience #threadpools #performance #optimization
Two kinds of threads pools, and why you need both

How big should your thread pool be? It depends on your use case.

Python⇒Speed