After NumPy v2 sprint, next in a row - pyproject migration has nearly reached its final destination, started on 2025-06-29

About 30+ packages left to migrate where the python-build-system (setup.py only build) is in direct use

https://codeberg.org/guix/guix/milestone/20775

#Guix on the way to modernise packaging logic for #Python

The upcoming would be Python 3.11 -> 3.12 -> 3.13 -> 3.14

https://codeberg.org/guix/guix/milestone/35232

Trying to catch up with the cadence with #ScientificPython
https://scientific-python.org/specs/spec-0000/

#guixpythonteam

guix

Transactional package manager, declarative GNU/Linux distribution, reproducible deployment tool, and more!

Codeberg.org

Since last year, I’ve been working on porting PolSARpro from C to Python.
Yesterday, a new version was released, adding several polarimetric decompositions and filters.

It’s still a work in progress, but it’s already usable — and steadily growing.

https://github.com/satim-co/PolSARpro

#PolSAR #SAR #RemoteSensing #EarthObservation #OpenSource #ScientificPython #Radar #InSAR #PythonGeo

GitHub - satim-co/PolSARpro: Re-implementation of selected PolSARpro functions in Python, following the scientific recommendations of PolInSAR 2021 (Work In Progress).

Re-implementation of selected PolSARpro functions in Python, following the scientific recommendations of PolInSAR 2021 (Work In Progress). - GitHub - satim-co/PolSARpro: Re-implementation of selec...

GitHub

I never thought I would end up advocating *against* #SPEC0, yet here we are.

ref: https://scientific-python.org/specs/spec-0000/
#python #scientificpython #dependency #packaging

Scientific Python - SPEC 0 — Minimum Supported Dependencies

Community developed and owned ecosystem for scientific computing

93/97
Yes, we DO believe it's time for beginners to learn about type annotations. It was once considered an advanced topic, especially in #ScientificPython. Well, not anymore!
90/97
The beginner track is evolving! It's not enough to talk about NumPy anymore. Many beginners start right with #dataframes, because more & more #ScientificPython libraries support them out of the box.
89/97
By looking at the tutorials before and after theirs, the beginner track Tutors can build on previous topics and set the stage for what's next, creating a cohesive onboarding experience into #ScientificPython.
64/97
A special note on our 'Education, Diversity & Outreach' track: while talks here don't require deep Python or domain knowledge, they must be relevant to the #ScientificPython community.
1/97
This year, we revamped our CfP categories to better reflect the #ScientificPython landscape. We've created a broad "Computational Tools & Scientific Python Infrastructure" track, consolidating topics like visualization, arrays, and data frames. 💻

🌟 Beginner Tutorial Alert at #EuroSciPy2025:

Deploy your Machine Learning model with FastAPI
📣 With Cheuk Ting Ho

Learn to:
🔹 Build an API for your pre-trained ML model
🔄 Design retraining workflows
🪄 Move from prototype to production-ready service
🛠️ Package in Docker & deploy to the cloud

Perfect for data scientists new to FastAPI or ML deployment.

📍 Kraków | 🗓️ August 18–22
🗓️ https://euroscipy.org/schedule

#FastAPI #Python #MachineLearning #MLOps #DataScience #ScientificPython

Sponsoring

The EuroSciPy meeting is a cross-disciplinary gathering focused on the use and development of the Python language in scientific research.

🚨 Tutorial at #EuroSciPy2025: Skrub – Machine Learning for DataFrames

Skrub bridges the gap between your Pandas/Polars tables and scikit-learn pipelines, making preprocessing of tabular data:

Easier, Consistent, Less error-prone

Presented by Guillaume Lemaitre, Jérôme Dockès & Riccardo Cappuzzo.

📍 Kraków | August 18–22
📆 https://euroscipy.org/schedule
🎟️ https://euroscipy.org/tickets/
#Skrub #DataScience #MachineLearning #ScientificPython

Sponsoring

The EuroSciPy meeting is a cross-disciplinary gathering focused on the use and development of the Python language in scientific research.