that’s actually a really cool trick — the many with-usages (like locks!) are a huge boon to understandable code.

And while it took me 25 lines of code to implement this with with wisp ( https://hg.sr.ht/~arnebab/wisp/browse/examples/with.w?rev=3447d48e85620c639131c0e1b47308503df5eb81#L12 ) it’s only Python where that’s the default way to do things.

(there is no superfluous with in the previous paragraph ☺)

Being able to add stuff like this to the language cleanly is why I started to move my personal projects from #Python to #Guile #Scheme in 2013, though.

I've turned one of my teaching modules in #Paleontology into an #OER. It's only one single lab, but many more are waiting to be OER-ised... therefore I really need your input to avoid future mistakes.
https://github.com/EmiliaJarochowska/Yankovich_cave/

Thanks to the feedback (shoutout to @leouieda and @JMMaok) I knew this:
✅ Must be editable
✅ Must include rubric
✅ Must include an example: I included a possible solution but without an essay, just the code. Now in #Rlanguage but #Python and #JuliaLang will follow.

The most watershed decision was to use #Quarto for everything to make it editable and renderable using Open Source tools and to make it version control-compatible. For people not familiar with #Quarto this may be a barrier?
Not sure what a good alternative would be. #OpenPedagogy

GitHub - EmiliaJarochowska/Yankovich_cave: Reconstruction of Pleistocene climate based on assemblages of mammal microfossils from a cave in Hungary

Reconstruction of Pleistocene climate based on assemblages of mammal microfossils from a cave in Hungary - GitHub - EmiliaJarochowska/Yankovich_cave: Reconstruction of Pleistocene climate based on ...

^GitHub

(1/2) Timetk for Python 🚀🚀🚀

The timetk, one of the main R packages for time series analysis and forecasting ❤️, by Matt Dancho, is now available in Python 🐍. The package provides a variety of tools for working with time series data and analyzing it. The Python version leverages pandas for processing time series data and plotly for visualization.

#timeseries #python #rstats #forecasting #DataScience

Advice for beginning (#Python and anything else) learners: https://nedbatchelder.com/blog/202309/advice_to_beginners.html

"Write code. Write more code. Get your hands in there, do things and find out what happens. You’ll learn best by doing."

(1/2) Python for Data Science is a new book by Arthur Turrell that focuses on core data science applications with Python 🚀. The book is inspired by the R for Data Science book by Hadley Wickham and Garrett Grolemund and follows a similar structure. The book covers topics such as:
✅ Data wrangling and transformation
✅ Data visualization
✅ Working with spreadsheets, databases, web scraping and APIs
✅ Programming topics such as functions and iteration

#python #DataScience #dataviz #data

PLEASE BOOST for visibility!

The University of Colorado Laboratory for Atmospheric and Space Physics (LASP) is hiring software engineers for science data processing on the Data Systems team. We build satellite borne instruments for studying astrophysics, planetary science, earth science, atmospheric science, and many more disciplines. Data Systems typically does the ground processing of the instrument data from binary packets through to research quality science data products (think netCDF, HDF5, CDF, FITS files). Mostly we use Python but we have some Java systems and C experience is always a plus for making Python faster.

https://jobs.colorado.edu/jobs/JobDetail/Data-Systems-Software-Engineers-II-IV/50810

Lab website:
https://lasp.colorado.edu/

#fedihire #jobsearch #jobs #hiring #planetaryscience #astrophysics #astronomy #physics #python #datascience

Home - Laboratory for Atmospheric and Space Physics

OUR STORY LASP 75th Anniversary OUR EXPERTISE Science Engineering Mission Operations Data Systems Business Facilitation OUR LEGACY Missions Instruments Labs & Facilities OUR PEOPLE Leadership Diversity & Inclusion Staff News Careers Events & Outreach…

^{Laboratory for Atmospheric and Space Physics}

It seems we'll have a lot of "fun" with the #PyPi decision to remove signatures for sdist tarballs (https://blog.pypi.org/posts/2023-05-23-removing-pgp/) going forward.

To scream into the void: Yes, PyPi, someone was using those signatures. Distro package maintainers secured user supply chains with it!

I'm not looking forward to asking dozens of upstreams to host their signatures elsewhere (just stumbled across one case). Meanwhile reproducibility is now broken for those packages.

#ArchLinux #packagerlife #Python

Removing PGP from PyPI - The Python Package Index

PyPI has removed support for uploading PGP signatures with new releases.

^{blog.pypi.org}

We have a new version of the data visualization tutorials written in #Python using #Pandas and #Altair:

https://infovis.fh-potsdam.de/tutorials/

The first tutorials lay the foundation, after which common data types are treated in 3 steps:

🛒 Prepare → 🥒 Process → 🥗 Present

If you have any ideas or suggestions for improvement, or if you're using these tutorials in your own teaching (or learning!), I'd love to hear about it. Many thanks already to @ikyriazi for lots of feedback on this revision!

#DataVis #OER

Data Visualization · FH Potsdam · Summer 2023

Hands-on tutorials for basic visualization techniques and the necessary data processing

^{infovis.fh-potsdam.de}

Grab the Python programming bundle by No Starch Press.

Part of the proceeds go towards the Python Software Foundation!

⏱️ Ends on 22 May.
💸 $1 or more.

https://www.humblebundle.com/books/python-no-starch-books?partner=itsfoss

#python #programming

Humble Tech Book Bundle: Python by No Starch

We’ve teamed up with No Starch Press for our newest bundle. Get books like Python for Kids and Beyond the Basic Stuff with Python. Plus, pay what you want & support charity!

^{Humble Bundle}